-861060000Serrano García de Dionisio, F.; Gómez-Carmona, C.D.; Bastida-Castillo, A.; Rojas-Valverde, D.; Pino-Ortega, J. (2020) Slope Influence on the Trail Runner Physical Load: A Case Study. Revista Internacional de Medicina y Ciencias de la Actividad Física y el Deporte vol. 20 (80) pp. 641-658 Http://cdeporte.rediris.es/revista/revista80/artinfluencia1191.htmDOI: https://doi.org/10.15366/rimcafd2020.80.012 Texto en PDFEnglish version PDFXML ORIGINALINFLUENCIA DEL DESNIVEL EN LA CARGA FÍSICA DEL CORREDOR DE MONTAÑA: UN ESTUDIO DE CASOSLOPE INFLUENCE ON THE TRAIL RUNNER PHYSICAL LOAD: A CASE STUDYSerrano García de Dionisio, F.1; Gómez-Carmona, C.D.2; Bastida-Castillo, A.3; Rojas-Valverde, D.4,5 y Pino-Ortega, J.61 Graduado en Ciencias de la Actividad Física y el Deporte. Facultad de Ciencias del Deporte, Universidad de Murcia (España) fsgd92@gmail.com2 Personal investigador con contrato predoctoral en Grupo de Optimización del Entrenamiento y el Rendimiento Deportivo (GOERD). Departamento de Didáctica de la Expresión Musical, Plástica y Corporal. Facultad de Ciencias del Deporte, Universidad de Extremadura (España) cdgomezcarmona@unex.es3 Doctor en Ciencias del Deporte. Departamento de Actividad Física y Deporte. Facultad de Ciencias del Deporte, Universidad de Murcia, España. Profesor Asociado Universidad Isabel I, Burgos (España) alejandro.bastida@um.es4 Estudiante de Doctorado, Grupo de Avances en Entrenamiento Deportivo y Acondicionamiento Físico (GAEDAF), Facultad de Ciencias del Deporte, Universidad de Extremadura, Cáceres (España) 5 Investigador Asociado, Centro de Investigación y Diagnóstico en Salud y Deporte (CIDISAD). Profesor en Escuela de Ciencias del Movimiento Humano y Calidad de Vida. Universidad Nacional de Costa Rica (Costa Rica) drojasv@una.cr6 Doctor en Ciencias de la Actividad Física y el Deporte. Profesor en Facultad de Ciencias de la Actividad Física y del Deporte. Departamento de Actividad Física y Deporte. Universidad de Murcia (España) josepinoortega@um.es FINANCIACIÓNPara la realización de este estudio no se ha recibido ninguna ayuda por parte de la empresa encargada del desarrollo y comercialización de la tecnología utilizada en esta investigación. El autor Carlos D. Gómez Carmona es beneficiario de una beca del Ministerio de Ciencia, Innovación y Universidades (FPU17/00407).Código UNESCO / UNESCO code: 5899 Otras especialidades pedagógicas (Educación Física y Deporte).Clasificación Consejo de Europa / Council of Europe Classification: 17. OTRAS (Análisis de las exigencias deportivas) / OTHER (Sport demands analysis)Recibido 17 de noviembre de 2018 Received November 17, 2018Aceptado 4 de agosto de 2019 Accepted August 4, 2019 RESUMENEste estudio analizó las exigencias de carga interna (Frecuencia cardíaca, FC) y externa (Velocidad; Player Load, PL; Power Metabolic, PM; Stiffness Vertical, KVERT; entropía aproximada, ApEn) producidas en función del desnivel del terreno en una carrera de montaña. Un atleta de nivel nacional (edad: 25.3 años; altura: 172 cm; peso: 67 kg; VO2MAX: 70.2 ml/kg/min) participó en una prueba oficial (Distancia: 27.6 km; Desnivel acumulado: 973 m), siendo analizado en 6 segmentos respecto al desnivel (sin desnivel, positivo y negativo). El registro de datos se realizó mediante un dispositivo inercial WIMU PROTM (RealTrack Systems, Almería, España). Los resultados muestran un aumento de PL/min y PM/min en desnivel negativo y de FCAVG en desnivel positivo. KVERT y ApEn fueron más bajos en desnivel positivo, mientras que la velocidad fue mayor sin desnivel. Se encuentra gran variabilidad en las exigencias en función de la orografía del terreno, siendo importante su análisis para el diseño específico del entrenamiento y la planificación del evento.PALABRAS CLAVE: Carreras de montaña, dispositivos inerciales, frecuencia cardiaca, stiffness vertical, carga neuromuscular, fatiga. ABSTRACTThis study analysed the internal (heart rate, HR) and external load demands (Speed; Player Load, PL; Power Metabolic, PM; Vertical stiffness, KVERT; approximated entropy, ApEn) during a trail running race in relation to the slope. A national-level athlete (age: 25.3 years; height: 172 cm; weight: 67 kg; VO2MAX: 70.2 ml/kg/min) participated in an official race (Distance: 27.6 km; Accumulated slope: 973 m), analysed in 6 segments related to the slope (without, positive and negative slope). Data was registered through an inertial device WIMU PROTM (RealTrack Systems, Almería, Spain). The results show an increase of PL/min and PM/min in negative slope and an increase of HRAVG in positive slope. KVERT and ApEn were lower in positive slope, while velocity was faster without slope. It is found a great variability in the trail runner demands related to terrain orography, being important its analysis to design specific training sessions and race planning.KEYWORDS: Mountain running, inertial devices, heart rate, vertical stiffness, neuromuscular load, fatigue.INTRODUCCIÓNDentro del fenómeno social running se encuentran una diversidad de pruebas atléticas de resistencia entre las que las disciplinas más practicadas son las carreras en ruta (medio maratón y maratón), las carreras de montaña (gran diversidad de terreno y distancias que tienen en común desniveles del terreno) y las carreras de ultra resistencia (por tiempo o por distancia siendo de distintas tipologías: a) senderos, b) dentro de un circuito visible y c) carreras por ciudad) ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"rsr8puru2","properties":{"formattedCitation":"(Consejo Superior de Deportes, 2016)","plainCitation":"(Consejo Superior de Deportes, 2016)","noteIndex":0},"citationItems":[{"id":"jd4YtdFl/M0EpAAMJ","uris":["http://zotero.org/groups/1616292/items/UD56GUWM"],"uri":["http://zotero.org/groups/1616292/items/UD56GUWM"],"itemData":{"id":3218,"type":"book","title":"Encuesta sobre los hábitos deportivos en España (2015)","publisher":"Consejo Superior de Deportes y Centro de Investigaciones Sociológicas","publisher-place":"Madrid","event-place":"Madrid","author":[{"family":"Consejo Superior de Deportes","given":""}],"issued":{"date-parts":[["2016"]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Consejo Superior de Deportes, 2016). Este tipo de competiciones cuenta con una historia muy reciente comparado a otras disciplinas deportivas y ha evolucionado con el tiempo de manera acelerada ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"Lw03S8WN","properties":{"formattedCitation":"(Rojas-Valverde, 2019)","plainCitation":"(Rojas-Valverde, 2019)","noteIndex":0},"citationItems":[{"id":3588,"uris":["http://zotero.org/users/5225985/items/3CIJDZUV"],"uri":["http://zotero.org/users/5225985/items/3CIJDZUV"],"itemData":{"id":3588,"type":"article-journal","title":"Brief historical review of distance and ultradistance runnig in Costa Rica and the world","container-title":"Viref:revista de Educación Física","page":"1-19","volume":"8","issue":"1","source":"Zotero","abstract":"It presents a systematization of historical background on distance and ultra distance races in Costa Rica and the world. While the history of distance events is relatively recent in this country, the social and economic characteristics of these could lead to promotion of active rural community participation, national ecological tourism and rural development. There are events, characters and historical facts worthy to be rescued, as well as the implicit spirit of the events carried out in natural environments in such a green and diverse country, with wide possibilities for the development of this type of activities and their future regulation through national institutions and sports federations.","ISSN":"ISSN: 2322-9411","language":"es","author":[{"family":"Rojas-Valverde","given":"Daniel"}],"issued":{"date-parts":[["2019"]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Rojas-Valverde, 2019) y que tiene cada vez un mayor número de adeptos ya que, como reconocen los propios corredores, suponen un reto personal y les proporcionan un aumento del reconocimiento social de su grupo de iguales ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"12e233a3qf","properties":{"formattedCitation":"(Ruiz-Juan & Zarauz, 2014)","plainCitation":"(Ruiz-Juan & Zarauz, 2014)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":"jd4YtdFl/CEHkuHBD","uris":["http://zotero.org/groups/1616292/items/K477REUT"],"uri":["http://zotero.org/groups/1616292/items/K477REUT"],"itemData":{"id":3220,"type":"article-journal","title":"Revista Latinoamericana de Psicología","container-title":"Revista Latinoamericana de Psicologia","page":"1–11","volume":"46","issue":"1","source":"Google Scholar","author":[{"family":"Ruiz-Juan","given":"Francisco"},{"family":"Zarauz","given":"Antonio"}],"issued":{"date-parts":[["2014"]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Ruiz-Juan y Zarauz, 2014).La especialidad de ultra fondo es una de las actividades más estresantes en las que un ser humano puede participar de forma voluntaria ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"2nc77flub","properties":{"formattedCitation":"(Eich & Metcalfe, 2009)","plainCitation":"(Eich & Metcalfe, 2009)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":"jd4YtdFl/2dwwZ72E","uris":["http://zotero.org/groups/1616292/items/35NIRPZQ"],"uri":["http://zotero.org/groups/1616292/items/35NIRPZQ"],"itemData":{"id":3214,"type":"article-journal","title":"Effects of the stress of marathon running on implicit and explicit memory","container-title":"Psychonomic Bulletin & Review","page":"475-479","volume":"16","issue":"3","source":"CrossRef","DOI":"10.3758/PBR.16.3.475","ISSN":"1069-9384, 1531-5320","language":"en","author":[{"family":"Eich","given":"Teal S."},{"family":"Metcalfe","given":"Janet"}],"issued":{"date-parts":[["2009",6]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Eich y Metcalfe, 2009), debido a la intensidad, la duración y condiciones ambientales que pueden ser adversas y cambiantes, que requieren del deportista un alto grado de preparación física específica y un enorme esfuerzo tanto físico ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"lnAUkFY6","properties":{"formattedCitation":"(Guti\\uc0\\u233{}rrez-Vargas et\\uc0\\u160{}al., 2018; G. Millet, 2011)","plainCitation":"(Gutiérrez-Vargas et al., 2018; G. Millet, 2011)","noteIndex":0},"citationItems":[{"id":3538,"uris":["http://zotero.org/users/5225985/items/IKGCUHNR"],"uri":["http://zotero.org/users/5225985/items/IKGCUHNR"],"itemData":{"id":3538,"type":"article-journal","title":"Biochemical and Muscle Mechanical Postmarathon Changes in Hot and Humid Conditions:","container-title":"Journal of Strength and Conditioning Research","page":"1","source":"Crossref","DOI":"10.1519/JSC.0000000000002746","ISSN":"1064-8011","title-short":"Biochemical and Muscle Mechanical Postmarathon Changes in Hot and Humid Conditions","language":"en","author":[{"family":"Gutiérrez-Vargas","given":"Randall"},{"family":"Martín-Rodríguez","given":"Saúl"},{"family":"Sánchez-Ureña","given":"Braulio"},{"family":"Rodríguez-Montero","given":"Alejandro"},{"family":"Salas-Cabrera","given":"Jorge"},{"family":"Gutiérrez-Vargas","given":"Juan C."},{"family":"Simunic","given":"Bostjan"},{"family":"Rojas-Valverde","given":"Daniel"}],"issued":{"date-parts":[["2018",7]]}}},{"id":"jd4YtdFl/TH4aKTNV","uris":["http://zotero.org/groups/1616292/items/U2WNT6FT"],"uri":["http://zotero.org/groups/1616292/items/U2WNT6FT"],"itemData":{"id":3192,"type":"article-journal","title":"Can Neuromuscular Fatigue Explain Running Strategies and Performance in Ultra-Marathons?: The Flush Model","container-title":"Sports Medicine","page":"489-506","volume":"41","issue":"6","source":"CrossRef","DOI":"10.2165/11588760-000000000-00000","ISSN":"0112-1642","shortTitle":"Can Neuromuscular Fatigue Explain Running Strategies and Performance in Ultra-Marathons?","language":"en","author":[{"family":"Millet","given":"G."}],"issued":{"date-parts":[["2011",6]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Gutiérrez-Vargas et al., 2020; Millet, 2011) como psicológico ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"2hcpftn395","properties":{"formattedCitation":"(Buceta, de la Llave, & others, 2007)","plainCitation":"(Buceta, de la Llave, & others, 2007)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":"jd4YtdFl/JCHYdgv9","uris":["http://zotero.org/groups/1616292/items/W3HFT498"],"uri":["http://zotero.org/groups/1616292/items/W3HFT498"],"itemData":{"id":3216,"type":"article-journal","title":"Intervención psicológica con corredores de maratón: características y valoración del programa aplicado en el maratón de Madrid","container-title":"Revista de Psicología del Deporte","volume":"11","issue":"1","source":"Google Scholar","URL":"http://www.rpd-online.com/article/view/139","shortTitle":"Intervención psicológica con corredores de maratón","author":[{"family":"Buceta","given":"José María"},{"family":"Llave","given":"A. López","non-dropping-particle":"de la"},{"literal":"others"}],"issued":{"date-parts":[["2007"]]},"accessed":{"date-parts":[["2017",8,10]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Buceta, de la Llave, Pérez Llantada, Vallejo y del Pino, 2002).La programación y monitorización del entrenamiento es clave para la obtención de rendimiento, así como para evitar la aparición de diferentes lesiones ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"A8y6ZJnx","properties":{"formattedCitation":"(Halson, 2014)","plainCitation":"(Halson, 2014)","noteIndex":0},"citationItems":[{"id":"jd4YtdFl/WMyksSzT","uris":["http://zotero.org/users/local/beObHR6h/items/4FW7ZX5Z"],"uri":["http://zotero.org/users/local/beObHR6h/items/4FW7ZX5Z"],"itemData":{"id":"KtFFGdW2/tgU8XiO6","type":"article-journal","title":"Monitoring Training Load to Understand Fatigue in Athletes","container-title":"Sports Medicine","page":"139-147","volume":"44","issue":"S2","source":"CrossRef","DOI":"10.1007/s40279-014-0253-z","ISSN":"0112-1642, 1179-2035","language":"en","author":[{"family":"Halson","given":"Shona L."}],"issued":{"date-parts":[["2014",11]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Halson, 2014). La dificultad de la modalidad de las carreras de montaña pasa, precisamente, por la cuantificación para planificar de forma correcta el entrenamiento y la competición ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"f24Bih0P","properties":{"formattedCitation":"(Kerherv\\uc0\\u233{}, Millet, & Solomon, 2015)","plainCitation":"(Kerhervé, Millet, & Solomon, 2015)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":"jd4YtdFl/fHjUC96L","uris":["http://zotero.org/groups/1616292/items/2YV2Y5LH"],"uri":["http://zotero.org/groups/1616292/items/2YV2Y5LH"],"itemData":{"id":6745,"type":"article-journal","title":"The Dynamics of Speed Selection and Psycho-Physiological Load during a Mountain Ultramarathon","container-title":"PLOS ONE","page":"e0145482","volume":"10","issue":"12","source":"DOI.org (Crossref)","abstract":"Background Exercise intensity during ultramarathons (UM) is expected to be regulated as a result of the development of psycho-physiological strain and in anticipation of perceived difficulties (duration, topography). The aim of this study was to investigate the dynamics of speed, heart rate and perceived exertion during a long trail UM in a mountainous setting.\nMethods Fifteen participants were recruited from competitors in a 106 km trail mountain UM with a total elevation gain and loss of 5870 m. Speed and gradient, heart rate (HR) and ratings of perceived exertion (dissociated between the general [RPEGEN] and knee extensor fatigue [RPEKE] and collected using a voice recorder) were measured during the UM. Self-selected speed at three gradients (level, negative, positive), HR, RPEGEN and RPEKE were determined for each 10% section of total event duration (TED).\nResults The participants completed the event in 18.3 ± 3.0 h, for a total calculated distance of 105.6 ± 1.8 km. Speed at all gradients decreased, and HR at all gradients significantly decreased from 10% to 70%, 80% and 90%, but not 100% of TED. RPEGEN and RPEKE increased throughout the event. Speed increased from 90% to 100% of TED at all gradients. Average speed was significantly correlated with total time stopped (r = -.772; p = .001; 95% confidence interval [CI] = -1.15, -0.39) and the magnitude of speed loss (r = .540; p = .038; 95% CI = -1.04, -0.03), but not with the variability of speed (r = -.475; p = .073; 95% CI = -1.00, 0.05).\nConclusions Participants in a mountain UM event combined positive pacing strategies (speed decreased until 70–90% of TED), an increased speed in the last 10% of the event, a decrease in HR at","DOI":"10.1371/journal.pone.0145482","ISSN":"1932-6203","journalAbbreviation":"PLoS ONE","language":"en","author":[{"family":"Kerhervé","given":"Hugo A."},{"family":"Millet","given":"Guillaume Y."},{"family":"Solomon","given":"Colin"}],"editor":[{"family":"Tauler","given":"Pedro"}],"issued":{"date-parts":[["2015",12,21]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Kerhervé, Millet, y Solomon, 2015). Esto se debe, fundamentalmente, a la dificultad que implica la orografía en la que se practica, ya que en un terreno irregular un mismo valor puede ser el resultado de diferentes factores. La cuantificación de la carga está dividida en dos grandes grupos, carga externa y carga interna ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"av2brmgdh4","properties":{"formattedCitation":"(Halson, 2014)","plainCitation":"(Halson, 2014)","noteIndex":0},"citationItems":[{"id":"jd4YtdFl/WMyksSzT","uris":["http://zotero.org/users/local/beObHR6h/items/4FW7ZX5Z"],"uri":["http://zotero.org/users/local/beObHR6h/items/4FW7ZX5Z"],"itemData":{"id":62,"type":"article-journal","title":"Monitoring Training Load to Understand Fatigue in Athletes","container-title":"Sports Medicine","page":"139-147","volume":"44","issue":"S2","source":"CrossRef","DOI":"10.1007/s40279-014-0253-z","ISSN":"0112-1642, 1179-2035","language":"en","author":[{"family":"Halson","given":"Shona L."}],"issued":{"date-parts":[["2014",11]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Halson, 2014). Entre los que miden la carga externa encontramos los que cuantifican la potencia de salida ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"a10eo355r76","properties":{"formattedCitation":"(Jobson, Passfield, Atkinson, Barton, & Scarf, 2009)","plainCitation":"(Jobson, Passfield, Atkinson, Barton, & Scarf, 2009)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":"jd4YtdFl/apRvDdzH","uris":["http://zotero.org/users/local/beObHR6h/items/GR6MMXG8"],"uri":["http://zotero.org/users/local/beObHR6h/items/GR6MMXG8"],"itemData":{"id":64,"type":"article-journal","title":"The analysis and utilization of cycling training data","container-title":"Sports medicine","page":"833–844","volume":"39","issue":"10","source":"Google Scholar","author":[{"family":"Jobson","given":"Simon A."},{"family":"Passfield","given":"Louis"},{"family":"Atkinson","given":"Greg"},{"family":"Barton","given":"Gabor"},{"family":"Scarf","given":"Philip"}],"issued":{"date-parts":[["2009"]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Jobson, Passfield, Atkinson, Barton, y Scarf, 2009), sistemas de análisis del movimiento donde se determinan valores mediante un sistema de medición inercial con sensores de posicionamiento satelital ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"a2ert629sd9","properties":{"formattedCitation":"(Taylor, Chapman, Cronin, Newton, & Gill, 2012)","plainCitation":"(Taylor, Chapman, Cronin, Newton, & Gill, 2012)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":"jd4YtdFl/v7f2UOqb","uris":["http://zotero.org/users/local/beObHR6h/items/XB4D7QUU"],"uri":["http://zotero.org/users/local/beObHR6h/items/XB4D7QUU"],"itemData":{"id":66,"type":"article-journal","title":"Fatigue monitoring in high performance sport: a survey of current trends","container-title":"J Aust Strength Cond","page":"12–23","volume":"20","issue":"1","source":"Google Scholar","shortTitle":"Fatigue monitoring in high performance sport","author":[{"family":"Taylor","given":"K."},{"family":"Chapman","given":"D."},{"family":"Cronin","given":"J."},{"family":"Newton","given":"Michael J."},{"family":"Gill","given":"Nicholas"}],"issued":{"date-parts":[["2012"]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Taylor, Chapman, Cronin, Newton, y Gill, 2012) y medidas derivadas del análisis de la fatiga neuromuscular entre los que destacan el stiffness o fuerzas de reacción durante la carrera (Kvert) y la carga neuromuscular ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"gu7Oc7WW","properties":{"formattedCitation":"(Cormack, Mooney, Morgan, & McGuigan, 2013; Twist & Highton, 2013)","plainCitation":"(Cormack, Mooney, Morgan, & McGuigan, 2013; Twist & Highton, 2013)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":"jd4YtdFl/CxQTqRNK","uris":["http://zotero.org/users/local/beObHR6h/items/XR238B3I"],"uri":["http://zotero.org/users/local/beObHR6h/items/XR238B3I"],"itemData":{"id":70,"type":"article-journal","title":"Influence of neuromuscular fatigue on accelerometer load in elite Australian football players","container-title":"International journal of sports physiology and performance","page":"373–378","volume":"8","issue":"4","source":"Google Scholar","author":[{"family":"Cormack","given":"Stuart J."},{"family":"Mooney","given":"Mitchell G."},{"family":"Morgan","given":"Will"},{"family":"McGuigan","given":"Michael R."}],"issued":{"date-parts":[["2013"]]}}},{"id":"jd4YtdFl/RxdBEUaR","uris":["http://zotero.org/users/local/beObHR6h/items/U4IZDJXI"],"uri":["http://zotero.org/users/local/beObHR6h/items/U4IZDJXI"],"itemData":{"id":68,"type":"article-journal","title":"Monitoring fatigue and recovery in rugby league players","container-title":"International Journal of sports physiology and performance","page":"467–474","volume":"8","issue":"5","source":"Google Scholar","author":[{"family":"Twist","given":"Craig"},{"family":"Highton","given":"Jamie"}],"issued":{"date-parts":[["2013"]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Cormack, Mooney, Morgan, y McGuigan, 2013; Twist y Highton, 2013). Recientes investigaciones han determinado la fatiga neuromuscular como la pérdida de fuerza después de un ejercicio prolongado, provocando alteraciones en el patrón de carrera ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"MOIHOIJq","properties":{"formattedCitation":"{\\rtf (G. Millet, 2011; G. Millet, Martin, Lattier, & Ballay, 2003; Guillaume Millet et\\uc0\\u160{}al., 2011)}","plainCitation":"(G. Millet, 2011; G. 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Diferentes trabajos han analizado el patrón de la carrera durante maratones ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"8uua2qusl","properties":{"formattedCitation":"(Kyr\\uc0\\u246{}l\\uc0\\u228{}inen et\\uc0\\u160{}al., 2000; Martin et\\uc0\\u160{}al., 2010; Nicol, Komi, & Marconnet, 2007)","plainCitation":"(Kyröläinen et al., 2000; Martin et al., 2010; Nicol, Komi, & Marconnet, 2007)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":"jd4YtdFl/aXFA8jry","uris":["http://zotero.org/groups/1616292/items/U2M4KV89"],"uri":["http://zotero.org/groups/1616292/items/U2M4KV89"],"itemData":{"id":3200,"type":"article-journal","title":"Effects of marathon running on running economy and kinematics","container-title":"European journal of applied physiology","page":"297–304","volume":"82","issue":"4","source":"Google Scholar","author":[{"family":"Kyröläinen","given":"H."},{"family":"Pullinen","given":"T."},{"family":"Candau","given":"R."},{"family":"Avela","given":"J."},{"family":"Huttunen","given":"P."},{"family":"Komi","given":"P. 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ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"91ri88405","properties":{"formattedCitation":"(Nicol, Komi, & Marconnet, 2007)","plainCitation":"(Nicol, Komi, & Marconnet, 2007)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":"jd4YtdFl/NPNVj7Fq","uris":["http://zotero.org/groups/1616292/items/8ZRFNFJE"],"uri":["http://zotero.org/groups/1616292/items/8ZRFNFJE"],"itemData":{"id":3204,"type":"article-journal","title":"Effects of marathon fatigue on running kinematics and economy","container-title":"Scandinavian Journal of Medicine & Science in Sports","page":"195-204","volume":"1","issue":"4","source":"CrossRef","DOI":"10.1111/j.1600-0838.1991.tb00296.x","ISSN":"09057188","language":"en","author":[{"family":"Nicol","given":"C."},{"family":"Komi","given":"P. 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V."}],"issued":{"date-parts":[["2000"]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} Kyröläinen et al (2000) reportó de forma significativa un incremento en la frecuencia de zancada. En cambio en ultramaratón, diferentes investigadores han evidenciado cambios en la mecánica de carrera teniendo una mayor frecuencia de zancada y reduciendo la fuerza de reacción vertical en la pisada y la amplitud de la oscilación del centro de masas, con el objetivo de ser más eficientes ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"2dgsd8htuv","properties":{"formattedCitation":"{\\rtf (G. Millet, 2011; Guillaume Y. Millet et\\uc0\\u160{}al., 2009; Jean-Beno\\uc0\\u238{}T Morin, Samozino, & Millet, 2011)}","plainCitation":"(G. Millet, 2011; Guillaume Y. 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Exercise was on a cycle ergometer with work rate incremented from loadless pedaling to exhaustion as a 50-W/min ramp function. Two different mathematical models were studied. One model employed a log-log transformation of [La-] and VO2 to yield [La-] threshold as proposed by Beaver et al. (J. Appl. Physiol. 59: 1936–1940, 1985). The other model was a continuous exponential plus constant of the form La- = a + b[exp(cVO2)]. In 21 of 23 data sets, the mean square error (MSE) of the continuous model was less than that of the log-log model (P less than 0.001). The MSE was on average 3.5 times greater in the log-log model than in the continuous model. The residuals were randomly distributed about the line of best fit for the continuous model. In contrast, the log-log model showed a nonrandom pattern indicating an inappropriate model. As an index of the position of the [La-]-VO2 continuous model, the VO2 at which the rate of increase of [La-] equaled the rate of increase of VO2 (d[La-]/dVO2 = 1) was determined. This VO2 was 2.241 +/- 0.081 l/min, which averaged 64.6% of maximal VO2. It is proposed that this lactate slope index could be used as a relative indicator of fitness instead of the previously applied threshold concept. The change in [La-] could be better described mathematically by a continuous model rather than the threshold model of Beaver et al.</p>","ISSN":"8750-7587, 1522-1601","note":"PMID: 3597269","language":"en","author":[{"family":"Hughson","given":"R. L."},{"family":"Weisiger","given":"K. H."},{"family":"Swanson","given":"G. D."}],"issued":{"date-parts":[["1987",5,1]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Hughson, Weisiger, y Swanson, 1987); variabilidad de la HR en reposo o post-ejercicio para determinar si el sujeto se adapta o no a los estímulos proporcionados ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"1rpb4968oj","properties":{"formattedCitation":"(Pichot et\\uc0\\u160{}al., 2000)","plainCitation":"(Pichot et al., 2000)","noteIndex":0},"citationItems":[{"id":"jd4YtdFl/qHHTpRpg","uris":["http://zotero.org/groups/1616292/items/RUCQQUB6"],"uri":["http://zotero.org/groups/1616292/items/RUCQQUB6"],"itemData":{"id":3304,"type":"article-journal","title":"Relation between heart rate variability and training load in middle-distance runners","container-title":"Medicine and science in sports and exercise","page":"1729–1736","volume":"32","issue":"10","source":"Google Scholar","author":[{"family":"Pichot","given":"Vincent"},{"family":"Roche","given":"Frederic"},{"family":"Gaspoz","given":"Jean-Michel"},{"family":"Enjolras","given":"Franck"},{"family":"Antoniadis","given":"Anestis"},{"family":"Minini","given":"Pascal"},{"family":"Costes","given":"Frederic"},{"family":"Busso","given":"Thierry"},{"family":"Lacour","given":"Jean-Rene"},{"family":"Barthelemy","given":"Jean Claude"}],"issued":{"date-parts":[["2000"]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Pichot et al., 2000), alteraciones mecánicas del músculo ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"U1ezhwTv","properties":{"formattedCitation":"(Guti\\uc0\\u233{}rrez-Vargas et\\uc0\\u160{}al., 2018)","plainCitation":"(Gutiérrez-Vargas et al., 2018)","noteIndex":0},"citationItems":[{"id":3538,"uris":["http://zotero.org/users/5225985/items/IKGCUHNR"],"uri":["http://zotero.org/users/5225985/items/IKGCUHNR"],"itemData":{"id":3538,"type":"article-journal","title":"Biochemical and Muscle Mechanical Postmarathon Changes in Hot and Humid Conditions:","container-title":"Journal of Strength and Conditioning Research","page":"1","source":"Crossref","DOI":"10.1519/JSC.0000000000002746","ISSN":"1064-8011","title-short":"Biochemical and Muscle Mechanical Postmarathon Changes in Hot and Humid Conditions","language":"en","author":[{"family":"Gutiérrez-Vargas","given":"Randall"},{"family":"Martín-Rodríguez","given":"Saúl"},{"family":"Sánchez-Ureña","given":"Braulio"},{"family":"Rodríguez-Montero","given":"Alejandro"},{"family":"Salas-Cabrera","given":"Jorge"},{"family":"Gutiérrez-Vargas","given":"Juan C."},{"family":"Simunic","given":"Bostjan"},{"family":"Rojas-Valverde","given":"Daniel"}],"issued":{"date-parts":[["2018",7]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Gutiérrez-Vargas et al., 2020), cambios en la temperatura de la piel como reflejo de la actividad metabólica ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"wnfMQPmE","properties":{"formattedCitation":"(Guti\\uc0\\u233{}rrez-Vargas et\\uc0\\u160{}al., 2017)","plainCitation":"(Gutiérrez-Vargas et al., 2017)","noteIndex":0},"citationItems":[{"id":3587,"uris":["http://zotero.org/users/5225985/items/72FBIMKH"],"uri":["http://zotero.org/users/5225985/items/72FBIMKH"],"itemData":{"id":3587,"type":"article-journal","title":"La termografía infrarroja como herramienta efectiva para detectar áreas músculares dañadas después de correr una maratón","container-title":"Revista de la Facultad de Medicina","page":"601-607","volume":"65","issue":"4","source":"DOI.org (Crossref)","abstract":"Introduction: Infrared thermography (IT) is an imaging technique that detects heat radiation emitted by an object and collects it to convert it into temperature values. In sports, it is used to identify damage to musculoskeletal structures based on the variation of body temperature in affected anatomical areas.\nObjective: To assess the effectiveness of IT as a tool to detect damaged muscles after running a marathon. Materials and methods: 17 runners were assessed before and after running a marathon (42.196 km) using thermographic equipment.\nResults: Statistically significant temperature differences were found before and after running a marathon. There was a difference between previous and posterior measurement >1°C in the vastus lateralis, vastus medialis, rectus femoris and adductor of the dominant leg, which, based on clinical parameters, indicates damage in these muscles. Increases in temperature were heterogeneous among anatomical areas. Conclusiones. La TI es una herramienta efectiva para detectar zonas musculares dañadas en corredores después de participar en una maratón. Palabras clave: Termografía; Músculos; Carrera; Lesiones (DeCS).\nConclusions: IT is an effective tool for detecting damaged muscle areas in runners after participating in a marathon.","DOI":"10.15446/revfacmed.v65n4.60638","ISSN":"2357-3848, 0120-0011","journalAbbreviation":"Rev. Fac. Med.","language":"es","author":[{"family":"Gutiérrez-Vargas","given":"Randall"},{"family":"Ugalde-Ramírez","given":"José Alexis"},{"family":"Rojas-Valverde","given":"Daniel"},{"family":"Salas-Cabrera","given":"Jorge"},{"family":"Rodríguez-Montero","given":"Alejandro"},{"family":"Gutiérrez-Vargas","given":"Juan Carlos"}],"issued":{"date-parts":[["2017",10,1]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Gutiérrez-Vargas et al., 2017) y análisis de parámetros bioquímicos ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"NUOzg2X2","properties":{"formattedCitation":"(Guti\\uc0\\u233{}rrez-Vargas et\\uc0\\u160{}al., 2018; Urdampilleta, L\\uc0\\u243{}pez-Grueso, Mart\\uc0\\u237{}nez-Sanz, & Mielgo-Ayuso, 2014)","plainCitation":"(Gutiérrez-Vargas et al., 2018; Urdampilleta, López-Grueso, Martínez-Sanz, & Mielgo-Ayuso, 2014)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":3538,"uris":["http://zotero.org/users/5225985/items/IKGCUHNR"],"uri":["http://zotero.org/users/5225985/items/IKGCUHNR"],"itemData":{"id":3538,"type":"article-journal","title":"Biochemical and Muscle Mechanical Postmarathon Changes in Hot and Humid Conditions:","container-title":"Journal of Strength and Conditioning Research","page":"1","source":"Crossref","DOI":"10.1519/JSC.0000000000002746","ISSN":"1064-8011","title-short":"Biochemical and Muscle Mechanical Postmarathon Changes in Hot and Humid Conditions","language":"en","author":[{"family":"Gutiérrez-Vargas","given":"Randall"},{"family":"Martín-Rodríguez","given":"Saúl"},{"family":"Sánchez-Ureña","given":"Braulio"},{"family":"Rodríguez-Montero","given":"Alejandro"},{"family":"Salas-Cabrera","given":"Jorge"},{"family":"Gutiérrez-Vargas","given":"Juan C."},{"family":"Simunic","given":"Bostjan"},{"family":"Rojas-Valverde","given":"Daniel"}],"issued":{"date-parts":[["2018",7]]}}},{"id":"jd4YtdFl/I1ZvwXQc","uris":["http://zotero.org/groups/1616292/items/9EE4WAK9"],"uri":["http://zotero.org/groups/1616292/items/9EE4WAK9"],"itemData":{"id":3306,"type":"article-journal","title":"Parámetros bioquímicos básicos, hematológicos y hormonales para el control de la salud y el estado nutricional en los deportistas","container-title":"Revista Española de Nutrición Humana y Dietética","page":"155–171","volume":"18","issue":"3","source":"Google Scholar","author":[{"family":"Urdampilleta","given":"Aritz"},{"family":"López-Grueso","given":"Raúl"},{"family":"Martínez-Sanz","given":"José Miguel"},{"family":"Mielgo-Ayuso","given":"Juan"}],"issued":{"date-parts":[["2014"]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Gutiérrez-Vargas et al., 2020; Urdampilleta, López-Grueso, Martínez-Sanz y Mielgo-Ayuso, 2014).Para el análisis de estas variables, dispositivos inerciales han sido desarrollados en los últimos años los cuáles sincronizan en el tiempo datos de carga interna y externa a partir de los diferentes sensores de los que disponen (acelerómetros, giróscopos, magnetómetros, GPS, receptores de dispositivos externos mediante tecnología bluetooth y Ant+, entre otros) para su análisis en tiempo real o a posteriori ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"cqojsb99i","properties":{"formattedCitation":"(Gabbett, 2013)","plainCitation":"(Gabbett, 2013)","noteIndex":0},"citationItems":[{"id":90,"uris":["http://zotero.org/groups/729592/items/A8FUATQX"],"uri":["http://zotero.org/groups/729592/items/A8FUATQX"],"itemData":{"id":90,"type":"article-journal","title":"Quantifying the Physical Demands of Collision Sports: Does Microsensor Technology Measure What It Claims to Measure?","container-title":"Journal of Strength and Conditioning Research","page":"2319-2322","volume":"27","issue":"8","source":"CrossRef","DOI":"10.1519/JSC.0b013e318277fd21","ISSN":"1064-8011","title-short":"Quantifying the Physical Demands of Collision Sports","language":"en","author":[{"family":"Gabbett","given":"Tim"}],"issued":{"date-parts":[["2013",8]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Gabbett, 2013). Además, han sido ampliamente utilizados en la literatura para analizar tanto movimientos cíclicos ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"NQVOqWKG","properties":{"formattedCitation":"(Nedergaard et\\uc0\\u160{}al., 2017)","plainCitation":"(Nedergaard et al., 2017)","noteIndex":0},"citationItems":[{"id":329,"uris":["http://zotero.org/groups/729592/items/3H3ZF95F"],"uri":["http://zotero.org/groups/729592/items/3H3ZF95F"],"itemData":{"id":329,"type":"article-journal","title":"The Relationship Between Whole-Body External Loading and Body-Worn Accelerometry During Team-Sport Movements","container-title":"International Journal of Sports Physiology and Performance","page":"18-26","volume":"12","issue":"1","source":"CrossRef","DOI":"10.1123/ijspp.2015-0712","ISSN":"1555-0265, 1555-0273","language":"en","author":[{"family":"Nedergaard","given":"Niels J."},{"family":"Robinson","given":"Mark A."},{"family":"Eusterwiemann","given":"Elena"},{"family":"Drust","given":"Barry"},{"family":"Lisboa","given":"Paulo J."},{"family":"Vanrenterghem","given":"Jos"}],"issued":{"date-parts":[["2017",1]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Nedergaard et al., 2017) como deportes colectivos ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"13evshr7d7","properties":{"formattedCitation":"(Boyd, Ball, & Aughey, 2013; Cormack et\\uc0\\u160{}al., 2013)","plainCitation":"(Boyd, Ball, & Aughey, 2013; Cormack et al., 2013)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":38,"uris":["http://zotero.org/groups/729592/items/NQIP98PB"],"uri":["http://zotero.org/groups/729592/items/NQIP98PB"],"itemData":{"id":38,"type":"article-journal","title":"Quantifying external load in Australian football matches and training using accelerometers","container-title":"Int J Sports Physiol Perform","page":"44–51","volume":"8","issue":"1","source":"Google Scholar","author":[{"family":"Boyd","given":"Luke J."},{"family":"Ball","given":"Kevin"},{"family":"Aughey","given":"Robert J."}],"issued":{"date-parts":[["2013"]]}}},{"id":"jd4YtdFl/CxQTqRNK","uris":["http://zotero.org/users/local/beObHR6h/items/XR238B3I"],"uri":["http://zotero.org/users/local/beObHR6h/items/XR238B3I"],"itemData":{"id":"v5hEChGl/MqOcY2So","type":"article-journal","title":"Influence of neuromuscular fatigue on accelerometer load in elite Australian football players","container-title":"International journal of sports physiology and performance","page":"373–378","volume":"8","issue":"4","source":"Google Scholar","author":[{"family":"Cormack","given":"Stuart J."},{"family":"Mooney","given":"Mitchell G."},{"family":"Morgan","given":"Will"},{"family":"McGuigan","given":"Michael R."}],"issued":{"date-parts":[["2013"]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Boyd, Ball, y Aughey, 2013; Cormack et al., 2013) reportando una alta fiabilidad y validez ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"2ms0uck95b","properties":{"formattedCitation":"(Barrett, Midgley, & Lovell, 2014)","plainCitation":"(Barrett, Midgley, & Lovell, 2014)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":72,"uris":["http://zotero.org/groups/729592/items/W26I9MBR"],"uri":["http://zotero.org/groups/729592/items/W26I9MBR"],"itemData":{"id":72,"type":"article-journal","title":"PlayerLoad™: Reliability, Convergent Validity, and Influence of Unit Position during Treadmill Running","container-title":"International Journal of Sports Physiology and Performance","page":"945-952","volume":"9","issue":"6","source":"CrossRef","DOI":"10.1123/ijspp.2013-0418","ISSN":"1555-0265, 1555-0273","title-short":"PlayerLoad™","language":"en","author":[{"family":"Barrett","given":"Steve"},{"family":"Midgley","given":"Adrian"},{"family":"Lovell","given":"Ric"}],"issued":{"date-parts":[["2014",11]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Barrett, Midgley, y Lovell, 2014).Teniendo en cuenta las dificultades que genera la cuantificación de la carga de las carreras de montaña y la necesidad de una correcta planificación para conseguir el máximo rendimiento evitando el sobreentrenamiento, los objetivos de este estudio son: (a) conocer las exigencias de carga interna y externa que se producen durante una prueba de competición oficial de carrera de montaña y (b) determinar si la orografía es un factor que provoca alteraciones en los distintos parámetros analizados.MÉTODOParticipantesUn atleta de nivel nacional en carreras de montaña que participó voluntariamente en esta investigación (edad: 25,3 años; altura: 172 cm; peso: 67 kg; masa muscular: 59.1 kg; masa grasa: 2.3 kg; VO2MAX: 70.2 ml/kg/min; FCREPOSO: 48 ppm; FCMAX: 198 ppm). El atleta presentó una velocidad aeróbica máxima de 20.2 km/h y una experiencia superior a tres años en la realización de esta modalidad deportiva. El atleta fue informado previamente de los detalles de la investigación y de sus posibles riesgos y beneficios, por lo que para ello se les suministró un consentimiento informado siguiendo el código de ética de la Asociación Médica Mundial (Declaración de Helsinki, 2013). ProcedimientoLa presente investigación se desarrolló durante la temporada 2016-2017, en una prueba de carácter federado dentro del calendario de pruebas oficiales de montaña organizada por la Federación de Montañismo de la Región de Murcia (FMRM). La carrera contaba con un desnivel positivo de 973 metros y con una distancia total del recorrido de 27.6 km. El punto más alto de la prueba se encontraba a 1207 metros y el punto más bajo a 565 metros. En la figura 1 se representa el perfil completo de la prueba y la división de esta en distintos segmentos según la orografía para facilitar el análisis descriptivo del perfil, usando como criterio para la determinación de los distintos desniveles el aumento, descenso o mantenimiento del nivel de altura con respecto al mar. Los segmentos de la prueba son: segmento 1 (sin desnivel 1); segmento 2 (desnivel positivo 1); segmento 3 (sin desnivel 2); segmento 4 (desnivel positivo 2); segmento 5 (desnivel negativo 1); y segmento 6 (desnivel negativo 2).478980511303000Figura 1. Perfil de la prueba y división en los 6 segmentos analizados en función de la pendiente. Eje y (altura), eje x (tiempo).El protocolo de recogida de información se realizó durante tres sesiones en dos semanas. La primera sesión se realizó una evaluación de las características antropométricas del sujeto y la explicación acerca de los objetivos y la monitorización del atleta durante el estudio. La segunda sesión se realizó una familiarización con alta monitorización durante una prueba incremental máxima en tapiz rodante para evaluar el rendimiento del deportista. Finalmente, la segunda semana se realizó el registro de la prueba oficial de carrera de montaña. Para el registro de la segunda y tercera sesión, se citó al deportista 15 minutos previo al inicio de las pruebas para la colocación del material.El dispositivo inercial (WIMU PROTM, RealTrack Systems, Almería, España) se introdujo en un arnés que posteriormente se colocaba al atleta a la altura entre la segunda y cuarta vértebra torácica ajustado anatómicamente. Previamente el dispositivo fue autocalibrado a través de un proceso en la configuración interna del arranque. Para el autocalibrado se tuvo en cuenta tres aspectos: (i) dejar el dispositivo inmóvil durante 30 s, (ii) situarlo en una superficie plana y (iii) sin dispositivos magnéticos alrededor ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"vIwDTHQf","properties":{"formattedCitation":"(Bastida Castillo, G\\uc0\\u243{}mez-Carmona, & Pino Ortega, 2016)","plainCitation":"(Bastida Castillo, Gómez-Carmona, & Pino Ortega, 2016)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":"jd4YtdFl/viigxKa3","uris":["http://zotero.org/users/3024263/items/47X22MH5"],"uri":["http://zotero.org/users/3024263/items/47X22MH5"],"itemData":{"id":49,"type":"article-journal","title":"Efectos del Tipo de Recuperación Sobre la Oxigenación Muscular Durante el Ejercicio de Sentadilla","container-title":"Kronos","page":"1-13","volume":"15","issue":"2","source":"g-se.com","abstract":"El objetivo de esta investigación es comprobar los cambios en la oxigenación muscular del recto anterior durante la realización del ejercicio de sentadilla según el tipo de recuperación. Para ello, 11 sujetos varones bien entrenados fueron distribuidos aleatoriamente a tres grupos experimentales: grupo...","author":[{"family":"Bastida Castillo","given":"Alejandro"},{"family":"Gómez-Carmona","given":"Carlos D."},{"family":"Pino Ortega","given":"José"}],"issued":{"date-parts":[["2016",12,13]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Bastida-Castillo, Gómez-Carmona, y Pino-Ortega, 2016). Los datos fueron almacenados en la memoria interna del dispositivo, siendo posteriormente descargados y analizados mediante el software S PROTM (RealTrack Systems, Almería, España).VariablesEn la presente investigación, a fin de que los resultados pudiesen compararse entre segmentos debido a la diferente distancia y tiempo empleado para completarse, las variables seleccionadas para el análisis de la carga física soportada fueron relativizadas al tiempo de ejecución, analizándose por minuto o calculando la media de exigencias de cada segmento. Carga externaPlayer Load por minuto (PL/min): Es la suma vectorial de las aceleraciones del dispositivo en sus 3 ejes (vertical, anteroposterior y lateral). Esta variable se ha utilizado para evaluar la carga neuromuscular ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"kndGNuqd","properties":{"formattedCitation":"(Gomez-Carmona, Bastida-Castillo, Gonz\\uc0\\u225{}lez-Custodio, Olcina, & Pino-Ortega, 2019; Reche-Soto, Cardona-Nieto, Diaz-Suarez, Gomez-Carmona, & Pino-Ortega, 2019)","plainCitation":"(Gomez-Carmona, Bastida-Castillo, González-Custodio, Olcina, & Pino-Ortega, 2019; Reche-Soto, Cardona-Nieto, Diaz-Suarez, Gomez-Carmona, & Pino-Ortega, 2019)","noteIndex":0},"citationItems":[{"id":3426,"uris":["http://zotero.org/groups/845255/items/QLAB4I3X"],"uri":["http://zotero.org/groups/845255/items/QLAB4I3X"],"itemData":{"id":3426,"type":"article-journal","title":"Using an inertial device (WIMU PRO™️) to quantify neuromuscular load in running: Reliability, convergent validity and the influence of type of surface and device location","container-title":"The Journal of Strength and Conditioning Research","volume":"Epub: Ahead of Print","DOI":"10.1519/JSC.0000000000003106","journalAbbreviation":"J Strength Cond Res","author":[{"family":"Gomez-Carmona","given":"Carlos D."},{"family":"Bastida-Castillo","given":"Alejandro"},{"family":"González-Custodio","given":"Adrián"},{"family":"Olcina","given":"Guillermo"},{"family":"Pino-Ortega","given":"José"}],"issued":{"date-parts":[["2019"]]}}},{"id":3981,"uris":["http://zotero.org/groups/844373/items/B6TRY6TL"],"uri":["http://zotero.org/groups/844373/items/B6TRY6TL"],"itemData":{"id":3981,"type":"article-journal","title":"AcelT y PlayerLoad™️: Dos variables para la cuantificación de la carga neuromuscular","container-title":"Revista Internacional de Medicina y Ciencias de la Actividad Física y del Deporte","volume":"Pendiente de publicación","author":[{"family":"Reche-Soto","given":"Pedro"},{"family":"Cardona-Nieto","given":"D"},{"family":"Diaz-Suarez","given":"Arturo"},{"family":"Gomez-Carmona","given":"Carlos"},{"family":"Pino-Ortega","given":"Jose"}],"issued":{"date-parts":[["2019"]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Gómez-Carmona, Bastida-Castillo, González-Custodio, Olcina, & Pino-Ortega, 2019; Reche-Soto, Cardona-Nieto, Diaz-Suarez, Gómez-Carmona, & Pino-Ortega, 2020). Se representa en unidades arbitrarias (a.u.) y se calcula a partir de la siguiente ecuación:PLn=(Xn-Xn-1)2+ (Yn-Yn-1)2+ (Zn-Zn-1)2100 PL acumulado =n=0mPLn x 0,01 Power metabolic por minuto (PM/min): Es el resultado de la multiplicación de la velocidad (V) por el coste energético de la actividad (CE) derivado de la inclinación y la aceleración ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"OiTHlzIj","properties":{"formattedCitation":"(Osgnach, Poser, Bernardini, Rinaldo, & Di Prampero, 2010; Reche-Soto et\\uc0\\u160{}al., 2018)","plainCitation":"(Osgnach, Poser, Bernardini, Rinaldo, & Di Prampero, 2010; Reche-Soto et al., 2018)","noteIndex":0},"citationItems":[{"id":"jd4YtdFl/EwFLCTuE","uris":["http://zotero.org/users/local/beObHR6h/items/VX459NDM"],"uri":["http://zotero.org/users/local/beObHR6h/items/VX459NDM"],"itemData":{"id":93,"type":"article-journal","title":"Energy Cost and Metabolic Power in Elite Soccer: A New Match Analysis Approach","container-title":"Medicine & Science in Sports & Exercise","page":"170-178","volume":"42","issue":"1","source":"CrossRef","DOI":"10.1249/MSS.0b013e3181ae5cfd","ISSN":"0195-9131","shortTitle":"Energy Cost and Metabolic Power in Elite Soccer","language":"en","author":[{"family":"Osgnach","given":"Cristian"},{"family":"Poser","given":"Stefano"},{"family":"Bernardini","given":"Riccardo"},{"family":"Rinaldo","given":"Roberto"},{"family":"Di Prampero","given":"Pietro Enrico"}],"issued":{"date-parts":[["2010",1]]}}},{"id":1036,"uris":["http://zotero.org/groups/844373/items/FR4TEXVZ"],"uri":["http://zotero.org/groups/844373/items/FR4TEXVZ"],"itemData":{"id":1036,"type":"article-journal","title":"Player Load and Metabolic Power Dynamics as Load Quantifiers in Soccer","container-title":"Journal of Human Kinetics","volume":"Epub: Ahead of Print","source":"Zotero","abstract":"There has recently been an increase in quantification and objective analysis of soccer performance due to improvements in technology using load indexes such as PlayerLoadTM and Metabolic Power. The objectives of this study were: (1) to describe the performance of PlayerLoadTM and Metabolic Power in competition according to the specific role, match-to-match variation, periods of play, game location and match status according to game periods, and (2) to analyze the relationship between both indexes. Twenty-one nationallevel soccer players were distributed in the following specific positional roles: external defenders (ED) (n = 4), central defenders (CD) (n = 4), midfielders (M) (n = 5), external midfielders (EM) (n = 4) and attackers (A) (n = 4). A total of 12 matches played by a Spanish Third Division team during the 2016/2017 season were analyzed. WIMU PROTM inertial devices (RealTrack System, Almeria, Spain) were used for recording the data. The main results were: (1) a performance reduction in both variables over the course of match time, (2) significant differences in both variables based on the specific position, (3) differences in physical demands during the season matches, (4) winning during a game period and the condition of being the visitor team provoked higher demands, and (5) a high correlation between both variables in soccer. In conclusion, different contextual variables influence the external load demands; both indexes are related so they could be used for external load quantification, and it is necessary to analyze physical demands of the competition for a specific and individualized load design in training sessions.","DOI":"http://www.doi.org/10.2478/hukin-2018-0072","language":"en","author":[{"family":"Reche-Soto","given":"Pedro"},{"family":"Cardona-Nieto","given":"Donaldo"},{"family":"Diaz-Suarez","given":"Arturo"},{"family":"Bastida-Castillo","given":"Alejandro"},{"family":"Gomez-Carmona","given":"Carlos"},{"family":"Garcia-Rubio","given":"Javier"},{"family":"Pino-Ortega","given":"Jose"}],"issued":{"date-parts":[["2018"]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Osgnach, Poser, Bernardini, Rinaldo, & Di Prampero, 2010; Reche-Soto et al., 2019). Se representa en W/kg y es calculada a través de la siguiente fórmula:PMet=CE ∙ VVelocidad (V): Relación que se establece entre el espacio o la distancia (d) que recorre un objeto y el tiempo (t) que invierte en ello. Se calcula a través de la siguiente fórmula:V= d ∙ t-1Entropía (ApEn): La entropía aproximada (ApEn) es una medida que depende de la probabilidad condicional de que dos secuencias que son similares para m muestras permanezcan similares, dentro de una tolerancia r, en la próxima muestra m+1. Si una secuencia de datos contiene una gran cantidad de patrones repetitivos (predecible o más regular) tendrá una ApEn pequeña, mientras que una con pocos (menos predecible o más irregular) tendrá una ApEn mayor ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"2jm1bqj3dn","properties":{"formattedCitation":"(Pincus, 2001)","plainCitation":"(Pincus, 2001)","noteIndex":0},"citationItems":[{"id":"jd4YtdFl/VO5iTNZD","uris":["http://zotero.org/groups/814338/items/8IPQTSFU"],"uri":["http://zotero.org/groups/814338/items/8IPQTSFU"],"itemData":{"id":1613,"type":"article-journal","title":"Assessing serial irregularity and its implications for health","container-title":"Annals of the New York Academy of Sciences","page":"245–267","volume":"954","issue":"1","source":"Google Scholar","author":[{"family":"Pincus","given":"Steven M."}],"issued":{"date-parts":[["2001"]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Pincus, 2001). Para una serie temporal {x(n)} de N muestras finitas, y definidos los parámetros r y m, ApEn (m, r, N) se puede calcular mediante la siguiente ecuación (aplicada sobre la señal del acelerómetro):Vertical stiffness o fuerzas de reacción vertical durante la carrera (KVERT): Es la relación existente entre la resultante de la fuerza máxima aplicada (Fmax) y el desplazamiento vertical del centro de masas (∆yc-1) ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"115bhskvcc","properties":{"formattedCitation":"{\\rtf (Jean-Beno\\uc0\\u238{}t Morin, Dalleau, Kyr\\uc0\\u246{}l\\uc0\\u228{}inen, Jeannin, & Belli, 2005)}","plainCitation":"(Jean-Benoît Morin, Dalleau, Kyröläinen, Jeannin, & Belli, 2005)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":"jd4YtdFl/yBd2jsqx","uris":["http://zotero.org/groups/1616292/items/Q2UJDB5E"],"uri":["http://zotero.org/groups/1616292/items/Q2UJDB5E"],"itemData":{"id":3222,"type":"article-journal","title":"A Simple Method for Measuring Stiffness during Running","container-title":"Journal of Applied Biomechanics","page":"167-180","volume":"21","issue":"2","source":"CrossRef","DOI":"10.1123/jab.21.2.167","ISSN":"1065-8483, 1543-2688","language":"en","author":[{"family":"Morin","given":"Jean-Benoît"},{"family":"Dalleau","given":"Georges"},{"family":"Kyröläinen","given":"Heikki"},{"family":"Jeannin","given":"Thibault"},{"family":"Belli","given":"Alain"}],"issued":{"date-parts":[["2005",5]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Morin, Dalleau, Kyröläinen, Jeannin, y Belli, 2005) y se calcula a partir de la siguiente fórmula:kvert= Fmax ∙ ∆yc-1Carga internaFrecuencia cardiaca (FCMEDIA): Es el número de latidos del corazón por unidad de tiempo. Se mide en pulsaciones por minuto y es una clara respuesta fisiológica al aumento de la actividad ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"a16j9qb4fnh","properties":{"formattedCitation":"(Bouzas, Ottoline, & Delgado, 2010)","plainCitation":"(Bouzas, Ottoline, & Delgado, 2010)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":"jd4YtdFl/fgZ3PDsh","uris":["http://zotero.org/users/local/o7j2npH8/items/DJP4AF8P"],"uri":["http://zotero.org/users/local/o7j2npH8/items/DJP4AF8P"],"itemData":{"id":119,"type":"article-journal","title":"Aplicaciones de la frecuencia cardiaca máxima en la evaluación y prescripción de ejercicio","container-title":"Apunts. Medicina de l'Esport","page":"251-258","volume":"45","issue":"168","source":"ScienceDirect","abstract":"El objetivo del estudio es presentar posibles aplicaciones de la frecuencia cardiaca máxima (FCM) en el entrenamiento y ambiente clínico así como identificar las ecuaciones que estiman la FCM. En el entrenamiento proporciona informaciones para la prescripción del ejercicio, el estado de sobreentrenamiento y el cálculo del gasto diario energético. En el ambiente clínico ayuda en la realización e interpretación de pruebas submaximales y maximales. En determinadas situaciones se utilizan ecuaciones matemáticas para el cálculo de la FCM. En la literatura médica especializada existen más de cincuenta ecuaciones disponibles, en las cuales solo se tiene en cuenta el factor edad o se incluyen otros factores tales como sexo, condición de salud o parámetros antropométricos. Por todo ello, para tener mayor exactitud a la hora de elegir una ecuación estimativa de la FCM es necesario conocer las existentes y optar por aquella que se adapta mejor a los objetivos de evaluación o prescripción de ejercicio.\nThe aim of this study was to show the possible applications of the heart rate maximum (HRmax) on training and clinical environment, as well as to identify the use of different equations to estimate the HRmax. The training provides information for the prescription of exercise, state of over-training and to calculate the daily energy expenditure. Moreover, when performed in the clinical environment they can help interpret sub-maximal tests as maximal ones. In some situations mathematical equations are used for calculating the HRmax. Thus, of more than fifty (50) equations were available in the specialised literature, some only have age as a factor, while others include, age, state of health and anthropometric parameters. However, to obtain more accuracy when choosing any equation to estimate the HRmax, one must have all the data and choose the one that best suits the objectives of evaluation or exercise prescription.","DOI":"10.1016/j.apunts.2010.04.003","ISSN":"1886-6581","journalAbbreviation":"Apunts. Medicina de l'Esport","author":[{"family":"Bouzas","given":"João C."},{"family":"Ottoline","given":"Nádia Maria"},{"family":"Delgado","given":"Manuel"}],"issued":{"date-parts":[["2010",10,1]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Bouzas, Ottoline, y Delgado, 2010).InstrumentosCaracterísticas antropométricasLa altura del sujeto fue medida con un tallímetro de pared (SECA, Hamburgo, Alemania). El peso corporal, masa muscular y masa grasa del atleta se obtuvo mediante una báscula de composición corporal compuesto por 8 electrodos de contacto modelo BC-601 (TANITA, Tokio, Japón).Carga externaLa adquisición de los datos se llevó a cabo empleando un dispositivo inercial denominado WIMU PROTM (RealTrack Systems, Almería, España). El dispositivo dispone diferentes sensores (4 acelerómetros, tres giroscopios, un magnetómetro, un chip GPS y otro UWB, entre otros). Para el registro de las variables velocidad y PM/min se utilizó el sensor de posicionamiento global por satélite (GPS) con una frecuencia de muestreo de 10 Hz, siendo su fiabilidad y validez evaluada previamente ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"X0zbALFy","properties":{"formattedCitation":"(Bastida Castillo, G\\uc0\\u243{}mez Carmona, De la Cruz S\\uc0\\u225{}nchez, & Pino Ortega, 2018)","plainCitation":"(Bastida Castillo, Gómez Carmona, De la Cruz Sánchez, & Pino Ortega, 2018)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":1279,"uris":["http://zotero.org/groups/844373/items/DJBSB3V2"],"uri":["http://zotero.org/groups/844373/items/DJBSB3V2"],"itemData":{"id":1279,"type":"article-journal","title":"Accuracy, intra- and inter-unit reliability, and comparison between GPS and UWB-based position-tracking systems used for time–motion analyses in soccer","container-title":"European Journal of Sport Science","page":"1-8","source":"CrossRef","DOI":"10.1080/17461391.2018.1427796","ISSN":"1746-1391, 1536-7290","language":"en","author":[{"family":"Bastida Castillo","given":"Alejandro"},{"family":"Gómez Carmona","given":"Carlos D."},{"family":"De la Cruz Sánchez","given":"Ernesto"},{"family":"Pino Ortega","given":"José"}],"issued":{"date-parts":[["2018",1,31]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Bastida-Castillo, Gómez-Carmona, De la Cruz Sánchez, y Pino-Ortega, 2018). Para el registro de las variables PL/min y KVERT se utilizaron los 4 acelerómetros que componen el dispositivo, con un fondo de escala de ±16g, ±16g, ±32g y ±400g, los cuales registraron a una frecuencia de muestreo de 100 Hz, siendo evaluada su fiabilidad en una investigación previa ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"Tufvnzjz","properties":{"formattedCitation":"(G\\uc0\\u243{}mez-Carmona, Bastida-Castillo, Garc\\uc0\\u237{}a-Rubio, Ib\\uc0\\u225{}\\uc0\\u241{}ez, & Pino-Ortega, 2018)","plainCitation":"(Gómez-Carmona, Bastida-Castillo, García-Rubio, Ibáñez, & Pino-Ortega, 2018)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":268,"uris":["http://zotero.org/groups/729592/items/4Z98VWC6"],"uri":["http://zotero.org/groups/729592/items/4Z98VWC6"],"itemData":{"id":268,"type":"article-journal","title":"Static and dynamic reliability of WIMU PROTM accelerometers according to anatomical placement","container-title":"Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology","volume":"Epub: Ahead of print","author":[{"family":"Gómez-Carmona","given":"Carlos D."},{"family":"Bastida-Castillo","given":"Alejandro"},{"family":"García-Rubio","given":"Javier"},{"family":"Ibáñez","given":"Sergio J."},{"family":"Pino-Ortega","given":"José"}],"issued":{"date-parts":[["2018"]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Gómez-Carmona, Bastida-Castillo, García-Rubio, Ibáñez, & Pino-Ortega, 2019).Carga internaSe registró mediante el empleo de una banda GARMINTM (Garmin Ltd., Olathe, Kansas, Estados Unidos) que se colocaba al sujeto justo por debajo de la apófisis xifoides, debajo de la línea intermamaria, la cual sincronizaba los datos al sistema WIMU PROTM a través de tecnología Ant+ con una frecuencia de muestreo de 4 Hz, siendo los datos almacenados en el dispositivo. Este protocolo ha sido evaluado previamente ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"AMVhwHHc","properties":{"formattedCitation":"(Molina-Carmona, Gomez-Carmona, Bastida Castillo, & Pino-Ortega, 2018)","plainCitation":"(Molina-Carmona, Gomez-Carmona, Bastida Castillo, & Pino-Ortega, 2018)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":1853,"uris":["http://zotero.org/groups/1726566/items/G6WWPIE7"],"uri":["http://zotero.org/groups/1726566/items/G6WWPIE7"],"itemData":{"id":1853,"type":"article-journal","title":"Validez del dispositivo inercial WIMU PRO™️ para el registro de la frecuencia cardíaca en un test de campo","container-title":"Sport-TK: Revista Euroamericana de Ciencias del Deporte","page":"81-86","volume":"7","language":"esp","author":[{"family":"Molina-Carmona","given":"Iván"},{"family":"Gomez-Carmona","given":"Carlos D."},{"family":"Bastida Castillo","given":"Alejandro"},{"family":"Pino-Ortega","given":"José"}],"issued":{"date-parts":[["2018"]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Molina-Carmona, Gomez-Carmona, Bastida-Castillo, y Pino-Ortega, 2018).Análisis estadísticoLos datos de las variables analizadas se muestran como promedios y desviaciones estándar (promedio ± DE) para describir todas las exigencias o requerimientos realizados durante la prueba. El análisis de la distribución de los datos se realizó mediante la prueba Shapiro-Wilk ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"2okljevlea","properties":{"formattedCitation":"(Field, 2013)","plainCitation":"(Field, 2013)","noteIndex":0},"citationItems":[{"id":"jd4YtdFl/1ONoZFDh","uris":["http://zotero.org/groups/814338/items/DMVUHF35"],"uri":["http://zotero.org/groups/814338/items/DMVUHF35"],"itemData":{"id":1595,"type":"book","title":"Discovering Statistics Using IBM SPSS Statistics","publisher":"SAGE","publisher-place":"Londres","number-of-pages":"954","edition":"4","source":"Google Books","event-place":"Londres","abstract":"Unrivalled in the way it makes the teaching of statistics compelling and accessible to even the most anxious of students, the only statistics textbook you and your students will ever need just got better! 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Para calcular la magnitud de las diferencias entre segmentos se utilizó el estadístico d de Cohen, siendo clasificado según ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"1vdScnil","properties":{"formattedCitation":"(Hopkins, Marshall, Batterham, & Hanin, 2009)","plainCitation":"(Hopkins, Marshall, Batterham, & Hanin, 2009)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":237,"uris":["http://zotero.org/groups/729592/items/ARUIJT7J"],"uri":["http://zotero.org/groups/729592/items/ARUIJT7J"],"itemData":{"id":237,"type":"article-journal","title":"Progressive Statistics for Studies in Sports Medicine and Exercise Science:","container-title":"Medicine & Science in Sports & Exercise","page":"3-13","volume":"41","issue":"1","source":"CrossRef","DOI":"10.1249/MSS.0b013e31818cb278","ISSN":"0195-9131","title-short":"Progressive Statistics for Studies in Sports Medicine and Exercise Science","language":"en","author":[{"family":"Hopkins","given":"William G."},{"family":"Marshall","given":"Stephen W."},{"family":"Batterham","given":"Alan M."},{"family":"Hanin","given":"Juri"}],"issued":{"date-parts":[["2009",1]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} Hopkins, Marshall, Batterham y Hanin (2009)como: efecto bajo (0-0.2), efecto pequeño (0.2-0.6), efecto moderado (0.6-1.2), efecto grande (1.2-2.0) y efecto muy grande (>2.0). Los gráficos fueron realizados mediante el software Graphpad Prism (Graphpad Software Inc., La Jolla CA, EEUU). Las pruebas estadísticas fueron realizadas mediante el software SPSS 24.0 (SPSS Inc., Chicago IL, EEUU). La significación estadística se estableció con el valor de p< 0.05. RESULTADOSEn la tabla 1 se muestra el análisis descriptivo de las variables analizadas en esta investigación en los diferentes segmentos la prueba en relación con la orografía del terreno. Se encuentran los mayores valores en las variables PL/min, PM/min, velocidad y KVERT en los segmentos sin desnivel, mientras que los mayores valores en FCMEDIA se hallaron en los segmentos con desnivel positivo.Tabla 1. Media y desviación estándar de las variables analizadas en función del segmento de la prueba.SegmentoPL/min (u.a.)PM/min (W/kg)FCMEDIA (ppm)Velocidad (km/h)ApEn(u.a.)KVERTMDEMDEMDEMDEMDEMDESD 14.451.1116.291.63182.725.6415.581.530.520.0729.312.84DP 13.370.7613.351.36191.111.3112.851.310.490.0526.011.54SD 24.200.6815.301.50185.213.6014.281.640.480.0428.911.97DP 22.780.6010.342.18189.331.709.821.990.460.0525.251.49DN 14.000.4413.381.22178.653.1012.471.170.490.0627.702.00DN 23.780.6414.061.69186.522.8313.471.720.510.0427.311.01Total3.760.7113.791.60185.593.0313.081.560.490.0527.411.81Nota. SD: Sin desnivel; DP: Desnivel positivo; DN: Desnivel negativo; PL/min: Player Load por minuto (unidad arbitraria); PM/min: Power Metabolic por minuto (watios/kilo); FCMEDIA: Frecuencia Cardiaca media (pulsaciones); ApEn: Entropía Aproximada (unidad arbitraria); KVERT: Índice de rigidez (unidad arbitraria); M: Media; DE: Desviación estándar.Posteriormente, en la figura 2, se muestra la representación gráfica y el análisis comparativo de las variables analizadas en función del segmento al que pertenecen según el tipo de inclinación del terreno. En las variables PL/min, PM/min, Velocidad y KVERT se evidenciaron los mayores valores (p < 0.05) en los segmentos sin desnivel y los menores valores en los segmentos con desnivel positivo con un tamaño del efecto de moderado a muy grande (PL/min: d = 1.82 - 1.15; PM/min: d = 3.09 - 1.36; Velocidad: d = 3.24 - 0.96; KVERT: d = 1.79 - 1.64). En cambio, en la variable FCMEDIA encontramos los mayores valores en los segmentos con desnivel positivo. Por último, en la variable ApEn se obtuvieron valores semejantes sin diferencias significativas (p > 0.24) en todos los segmentos analizados encontrando el valor más bajo en el segmento de desnivel positivo 2.En el análisis pormenorizado por segmentos en cuanto a las variables PL/min, KVERT y Velocidad se encontró mayores valores en los tramos sin desnivel (p < 0.05), posteriormente los tramos con desnivel negativo y finalmente los tramos con desnivel positivo que son los que reportan los menores valores en esta variable. Existen diferencias significativas en función del tipo de inclinación (p < 0.05), pero no entre los segmentos con el mismo tipo de desnivel (p = 0.23 - 0.68), excepto en la variable velocidad entre el segmento con desnivel positivo 1 y 2 con un tamaño del efecto grande (p < 0.05; d = 1.79).En la variable PM no se aprecian diferencias significativas entre los segmentos sin desnivel y los desniveles negativos. Únicamente el segmento con desnivel positivo 2 tuvo diferencias significativas con el resto de los segmentos (p < 0.01). Finalmente, en cuanto a la FCMEDIA encontramos el menor valor en el segmento con desnivel negativo 1 (178.65 ± 3.10 ppm) y los mayores valores en los segmentos con desnivel positivo (DP1 = 191.11 ± 1.31 ppm; DP2 = 189.33 ± 1.70 ppm), reportando diferencias con el resto de los segmentos (p < 0.05). No se encuentran diferencias entre los segmentos sin desnivel y el segmento con desnivel negativo 2.4761230-645731500Figura 2. Gráfico de cajas y bigotes y diferencias significativas entre las variables en función de los segmentos diferenciados por la orografía del terreno: (a) Player Load (PL), (b) Power Metabolic (PM), (c) Stiffness vertical (KVERT), (d) Entropía aproximada (ApEn), (e) Frecuencia cardíaca (FCMEDIA) y (f) Velocidad.SD1: Diferencias significativas respecto al segmento sin desnivel 1(p<0.05)SD2: Diferencias significativas respecto al segmento sin desnivel 2 (p<0.05)DP1: Diferencias significativas respecto al segmento desnivel positivo 1 (p<0.05)DP2: Diferencias significativas respecto al segmento desnivel positivo 2 (p<0.05)DN1: Diferencias significativas respecto al segmento desnivel negativo 1 (p<0.05)DN2: Diferencias significativas respecto al segmento desnivel negativo 2 (p<0.05)DISCUSIÓNLos objetivos de la presente investigación fueron describir la carga interna y externa durante una carrera de montaña y analizar la influencia del desnivel de la prueba en esta carga. A partir de los resultados obtenidos, se ha podido determinar que la carga a la que está sometida el sujeto varía dependiendo del tipo de desnivel que encuentre durante la carrera ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"a24anj3vr2v","properties":{"formattedCitation":"(Vernillo et\\uc0\\u160{}al., 2017)","plainCitation":"(Vernillo et al., 2017)","noteIndex":0},"citationItems":[{"id":"jd4YtdFl/ZdEZwpoM","uris":["http://zotero.org/users/local/beObHR6h/items/VZ34SE8A"],"uri":["http://zotero.org/users/local/beObHR6h/items/VZ34SE8A"],"itemData":{"id":75,"type":"article-journal","title":"Biomechanics and Physiology of Uphill and Downhill Running","container-title":"Sports Medicine","page":"615-629","volume":"47","issue":"4","source":"CrossRef","DOI":"10.1007/s40279-016-0605-y","ISSN":"0112-1642, 1179-2035","language":"en","author":[{"family":"Vernillo","given":"Gianluca"},{"family":"Giandolini","given":"Marlène"},{"family":"Edwards","given":"W. Brent"},{"family":"Morin","given":"Jean-Benoît"},{"family":"Samozino","given":"Pierre"},{"family":"Horvais","given":"Nicolas"},{"family":"Millet","given":"Guillaume Y."}],"issued":{"date-parts":[["2017",4]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Vernillo et al., 2017), al cual ha de adaptarse variando los factores mecánicos y fisiológicos.En relación con la variable PL/min, se encuentran mayores valores en los segmentos con desnivel negativo y sin desnivel con relación a los tramos de desnivel positivo, siendo estas diferencias significativas (p < 0.05). Los estudios que analizan este parámetro están relacionados con los deportes colectivos donde las situaciones cambiantes dificultan la posibilidad de cuantificar la carga ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"a26efkau7n","properties":{"formattedCitation":"(Sparks, Coetzee, & Gabbett, 2017)","plainCitation":"(Sparks, Coetzee, & Gabbett, 2017)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":"jd4YtdFl/YkPcJdjS","uris":["http://zotero.org/users/local/beObHR6h/items/ZESMUU2W"],"uri":["http://zotero.org/users/local/beObHR6h/items/ZESMUU2W"],"itemData":{"id":79,"type":"article-journal","title":"Internal and External Match Loads of University-Level Soccer Players: A Comparison Between Methods","container-title":"Journal of Strength and Conditioning Research","page":"1072-1077","volume":"31","issue":"4","source":"CrossRef","DOI":"10.1519/JSC.0000000000001560","ISSN":"1064-8011","shortTitle":"Internal and External Match Loads of University-Level Soccer Players","language":"en","author":[{"family":"Sparks","given":"Martinique"},{"family":"Coetzee","given":"Ben"},{"family":"Gabbett","given":"Tim J."}],"issued":{"date-parts":[["2017",4]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Sparks, Coetzee, y Gabbett, 2017). De los resultados de estos se observa que el valor de PL/min aumenta donde hay cambios significativos de velocidad, producto tanto de una aceleración como de una deceleración. Se ha visto también que las zonas donde las velocidades son más altas, el PL/min es mayor ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"zBCkRJ69","properties":{"formattedCitation":"(Barrett et\\uc0\\u160{}al., 2014; Buchheit, Gray, & Morin, 2015)","plainCitation":"(Barrett et al., 2014; Buchheit, Gray, & Morin, 2015)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":72,"uris":["http://zotero.org/groups/729592/items/W26I9MBR"],"uri":["http://zotero.org/groups/729592/items/W26I9MBR"],"itemData":{"id":72,"type":"article-journal","title":"PlayerLoad™: Reliability, Convergent Validity, and Influence of Unit Position during Treadmill Running","container-title":"International Journal of Sports Physiology and Performance","page":"945-952","volume":"9","issue":"6","source":"CrossRef","DOI":"10.1123/ijspp.2013-0418","ISSN":"1555-0265, 1555-0273","title-short":"PlayerLoad™","language":"en","author":[{"family":"Barrett","given":"Steve"},{"family":"Midgley","given":"Adrian"},{"family":"Lovell","given":"Ric"}],"issued":{"date-parts":[["2014",11]]}}},{"id":"jd4YtdFl/VjroqC3Y","uris":["http://zotero.org/users/local/beObHR6h/items/7D97BB3A"],"uri":["http://zotero.org/users/local/beObHR6h/items/7D97BB3A"],"itemData":{"id":77,"type":"article-journal","title":"Assessing stride variables and vertical stiffness with GPS-embedded accelerometers: preliminary insights for the monitoring of neuromuscular fatigue on the field","container-title":"Journal of sports science & medicine","page":"698","volume":"14","issue":"4","source":"Google Scholar","shortTitle":"Assessing stride variables and vertical stiffness with GPS-embedded accelerometers","author":[{"family":"Buchheit","given":"Martin"},{"family":"Gray","given":"Andrew"},{"family":"Morin","given":"Jean-Benoit"}],"issued":{"date-parts":[["2015"]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Barrett et al., 2014; Buchheit, Gray, y Morin, 2015). Por lo tanto, un mayor PL/min en los segmentos con desnivel negativo está asociado a los cambios de velocidades significativos que se dan por las aceleraciones/deceleraciones ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"abbb27fsse","properties":{"formattedCitation":"{\\rtf (Sparks et\\uc0\\u160{}al., 2017)}","plainCitation":"(Sparks et al., 2017)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":"jd4YtdFl/YkPcJdjS","uris":["http://zotero.org/users/local/beObHR6h/items/ZESMUU2W"],"uri":["http://zotero.org/users/local/beObHR6h/items/ZESMUU2W"],"itemData":{"id":79,"type":"article-journal","title":"Internal and External Match Loads of University-Level Soccer Players: A Comparison Between Methods","container-title":"Journal of Strength and Conditioning Research","page":"1072-1077","volume":"31","issue":"4","source":"CrossRef","DOI":"10.1519/JSC.0000000000001560","ISSN":"1064-8011","shortTitle":"Internal and External Match Loads of University-Level Soccer Players","language":"en","author":[{"family":"Sparks","given":"Martinique"},{"family":"Coetzee","given":"Ben"},{"family":"Gabbett","given":"Tim J."}],"issued":{"date-parts":[["2017",4]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Sparks, Coetzee y Gabbett, 2017) y a mayores impactos producidos por los desniveles negativos (Vernillo et al., 2017). En cambio, los altos valores en los segmentos sin desnivel están asociados a un incremento de la intensidad de los desplazamientos registrada mediante la velocidad ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"oQIjR7b2","properties":{"formattedCitation":"(Barrett et\\uc0\\u160{}al., 2014; Nedergaard et\\uc0\\u160{}al., 2017)","plainCitation":"(Barrett et al., 2014; Nedergaard et al., 2017)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":72,"uris":["http://zotero.org/groups/729592/items/W26I9MBR"],"uri":["http://zotero.org/groups/729592/items/W26I9MBR"],"itemData":{"id":72,"type":"article-journal","title":"PlayerLoad™: Reliability, Convergent Validity, and Influence of Unit Position during Treadmill Running","container-title":"International Journal of Sports Physiology and Performance","page":"945-952","volume":"9","issue":"6","source":"CrossRef","DOI":"10.1123/ijspp.2013-0418","ISSN":"1555-0265, 1555-0273","title-short":"PlayerLoad™","language":"en","author":[{"family":"Barrett","given":"Steve"},{"family":"Midgley","given":"Adrian"},{"family":"Lovell","given":"Ric"}],"issued":{"date-parts":[["2014",11]]}}},{"id":329,"uris":["http://zotero.org/groups/729592/items/3H3ZF95F"],"uri":["http://zotero.org/groups/729592/items/3H3ZF95F"],"itemData":{"id":329,"type":"article-journal","title":"The Relationship Between Whole-Body External Loading and Body-Worn Accelerometry During Team-Sport Movements","container-title":"International Journal of Sports Physiology and Performance","page":"18-26","volume":"12","issue":"1","source":"CrossRef","DOI":"10.1123/ijspp.2015-0712","ISSN":"1555-0265, 1555-0273","language":"en","author":[{"family":"Nedergaard","given":"Niels J."},{"family":"Robinson","given":"Mark A."},{"family":"Eusterwiemann","given":"Elena"},{"family":"Drust","given":"Barry"},{"family":"Lisboa","given":"Paulo J."},{"family":"Vanrenterghem","given":"Jos"}],"issued":{"date-parts":[["2017",1]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Barrett, Midgley y Lovell, 2014; Nedergaard et al., 2017). Por tanto, esta variable podría ser un indicador adecuado para el análisis de las exigencias debido a su alta sensibilidad en función de la pendiente y por lo tanto su capacidad para identificar cambios en la mecánica de carrera provocada, por ejemplo por la velocidad ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"on5U89tK","properties":{"formattedCitation":"(Barreira et\\uc0\\u160{}al., 2017; Barrett et\\uc0\\u160{}al., 2014; Nedergaard et\\uc0\\u160{}al., 2017)","plainCitation":"(Barreira et al., 2017; Barrett et al., 2014; Nedergaard et al., 2017)","noteIndex":0},"citationItems":[{"id":73,"uris":["http://zotero.org/groups/729592/items/2BN5WUID"],"uri":["http://zotero.org/groups/729592/items/2BN5WUID"],"itemData":{"id":73,"type":"article-journal","title":"Mechanical Player Load using trunk-mounted accelerometry in football: Is it a reliable, task- and player-specific observation?","container-title":"Journal of Sports Sciences","page":"1674-1681","volume":"35","issue":"17","source":"CrossRef","DOI":"10.1080/02640414.2016.1229015","ISSN":"0264-0414, 1466-447X","title-short":"Mechanical Player Load?","language":"en","author":[{"family":"Barreira","given":"Paulo"},{"family":"Robinson","given":"Mark A."},{"family":"Drust","given":"Barry"},{"family":"Nedergaard","given":"Niels"},{"family":"Raja Azidin","given":"Raja Mohammed Firhad"},{"family":"Vanrenterghem","given":"Jos"}],"issued":{"date-parts":[["2017",9,2]]}}},{"id":72,"uris":["http://zotero.org/groups/729592/items/W26I9MBR"],"uri":["http://zotero.org/groups/729592/items/W26I9MBR"],"itemData":{"id":72,"type":"article-journal","title":"PlayerLoad™: Reliability, Convergent Validity, and Influence of Unit Position during Treadmill Running","container-title":"International Journal of Sports Physiology and Performance","page":"945-952","volume":"9","issue":"6","source":"CrossRef","DOI":"10.1123/ijspp.2013-0418","ISSN":"1555-0265, 1555-0273","title-short":"PlayerLoad™","language":"en","author":[{"family":"Barrett","given":"Steve"},{"family":"Midgley","given":"Adrian"},{"family":"Lovell","given":"Ric"}],"issued":{"date-parts":[["2014",11]]}}},{"id":329,"uris":["http://zotero.org/groups/729592/items/3H3ZF95F"],"uri":["http://zotero.org/groups/729592/items/3H3ZF95F"],"itemData":{"id":329,"type":"article-journal","title":"The Relationship Between Whole-Body External Loading and Body-Worn Accelerometry During Team-Sport Movements","container-title":"International Journal of Sports Physiology and Performance","page":"18-26","volume":"12","issue":"1","source":"CrossRef","DOI":"10.1123/ijspp.2015-0712","ISSN":"1555-0265, 1555-0273","language":"en","author":[{"family":"Nedergaard","given":"Niels J."},{"family":"Robinson","given":"Mark A."},{"family":"Eusterwiemann","given":"Elena"},{"family":"Drust","given":"Barry"},{"family":"Lisboa","given":"Paulo J."},{"family":"Vanrenterghem","given":"Jos"}],"issued":{"date-parts":[["2017",1]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Barreira et al., 2017; Barrett et al., 2014; Nedergaard et al., 2017) y fatiga ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"vNRWaZ7T","properties":{"formattedCitation":"(Barrett et\\uc0\\u160{}al., 2016; Cormack et\\uc0\\u160{}al., 2013)","plainCitation":"(Barrett et al., 2016; Cormack et al., 2013)","noteIndex":0},"citationItems":[{"id":248,"uris":["http://zotero.org/groups/729592/items/F9T3AWCI"],"uri":["http://zotero.org/groups/729592/items/F9T3AWCI"],"itemData":{"id":248,"type":"article-journal","title":"Within-Match PlayerLoad™ Patterns during a Simulated Soccer Match: Potential Implications for Unit Positioning and Fatigue Management","container-title":"International Journal of Sports Physiology and Performance","page":"135-140","volume":"11","issue":"1","source":"CrossRef","DOI":"10.1123/ijspp.2014-0582","ISSN":"1555-0265, 1555-0273","title-short":"Within-Match PlayerLoad™ Patterns during a Simulated Soccer Match","language":"en","author":[{"family":"Barrett","given":"Steve"},{"family":"Midgley","given":"Adrian W."},{"family":"Towlson","given":"Christopher"},{"family":"Garrett","given":"Andrew"},{"family":"Portas","given":"Matt"},{"family":"Lovell","given":"Ric"}],"issued":{"date-parts":[["2016",1]]}}},{"id":"jd4YtdFl/CxQTqRNK","uris":["http://zotero.org/users/local/beObHR6h/items/XR238B3I"],"uri":["http://zotero.org/users/local/beObHR6h/items/XR238B3I"],"itemData":{"id":"FC0d22gE/jLbBC7k7","type":"article-journal","title":"Influence of neuromuscular fatigue on accelerometer load in elite Australian football players","container-title":"International journal of sports physiology and performance","page":"373–378","volume":"8","issue":"4","source":"Google Scholar","author":[{"family":"Cormack","given":"Stuart J."},{"family":"Mooney","given":"Mitchell G."},{"family":"Morgan","given":"Will"},{"family":"McGuigan","given":"Michael R."}],"issued":{"date-parts":[["2013"]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Barrett et al., 2016; Cormack et al., 2013), entre otros.En el caso del PM, los resultados muestran que los valores más altos se reportaron en las zonas de mayor velocidad que correspondían con las zonas sin desnivel ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"Qyt27aba","properties":{"formattedCitation":"(Osgnach et\\uc0\\u160{}al., 2010)","plainCitation":"(Osgnach et al., 2010)","noteIndex":0},"citationItems":[{"id":"jd4YtdFl/EwFLCTuE","uris":["http://zotero.org/users/local/beObHR6h/items/VX459NDM"],"uri":["http://zotero.org/users/local/beObHR6h/items/VX459NDM"],"itemData":{"id":"B1cBE4Ol/YGsNaUJp","type":"article-journal","title":"Energy Cost and Metabolic Power in Elite Soccer: A New Match Analysis Approach","container-title":"Medicine & Science in Sports & Exercise","page":"170-178","volume":"42","issue":"1","source":"CrossRef","DOI":"10.1249/MSS.0b013e3181ae5cfd","ISSN":"0195-9131","shortTitle":"Energy Cost and Metabolic Power in Elite Soccer","language":"en","author":[{"family":"Osgnach","given":"Cristian"},{"family":"Poser","given":"Stefano"},{"family":"Bernardini","given":"Riccardo"},{"family":"Rinaldo","given":"Roberto"},{"family":"Di Prampero","given":"Pietro Enrico"}],"issued":{"date-parts":[["2010",1]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Osgnach et al., 2010). El consumo más bajo se encontró en los dos segmentos de desnivel positivo donde los valores de velocidad alcanzada fueron más bajos. Estos resultados se encuentran en contraste con la bibliografía, ya que la mayor parte de los estudios encontrados reconocen un mayor gasto energético en los tramos de subida ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"jnHPA66Z","properties":{"formattedCitation":"{\\rtf (Vernillo et\\uc0\\u160{}al., 2015, 2017)}","plainCitation":"(Vernillo et al., 2015, 2017)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":"jd4YtdFl/ldPyW63g","uris":["http://zotero.org/users/local/beObHR6h/items/PI85VUNT"],"uri":["http://zotero.org/users/local/beObHR6h/items/PI85VUNT"],"itemData":{"id":"lVmg8Ubp/2LW0Ua6h","type":"article-journal","title":"Energy cost and kinematics of level, uphill and downhill running: fatigue-induced changes after a mountain ultramarathon","container-title":"Journal of Sports Sciences","page":"1998-2005","volume":"33","issue":"19","source":"CrossRef","DOI":"10.1080/02640414.2015.1022870","ISSN":"0264-0414, 1466-447X","shortTitle":"Energy cost and kinematics of level, uphill and downhill running","language":"en","author":[{"family":"Vernillo","given":"Gianluca"},{"family":"Savoldelli","given":"Aldo"},{"family":"Zignoli","given":"Andrea"},{"family":"Skafidas","given":"Spyros"},{"family":"Fornasiero","given":"Alessandro"},{"family":"La Torre","given":"Antonio"},{"family":"Bortolan","given":"Lorenzo"},{"family":"Pellegrini","given":"Barbara"},{"family":"Schena","given":"Federico"}],"issued":{"date-parts":[["2015",11,26]]}}},{"id":"jd4YtdFl/ZdEZwpoM","uris":["http://zotero.org/users/local/beObHR6h/items/VZ34SE8A"],"uri":["http://zotero.org/users/local/beObHR6h/items/VZ34SE8A"],"itemData":{"id":"lVmg8Ubp/HSPDfDfA","type":"article-journal","title":"Biomechanics and Physiology of Uphill and Downhill Running","container-title":"Sports Medicine","page":"615-629","volume":"47","issue":"4","source":"CrossRef","DOI":"10.1007/s40279-016-0605-y","ISSN":"0112-1642, 1179-2035","language":"en","author":[{"family":"Vernillo","given":"Gianluca"},{"family":"Giandolini","given":"Marlène"},{"family":"Edwards","given":"W. Brent"},{"family":"Morin","given":"Jean-Benoît"},{"family":"Samozino","given":"Pierre"},{"family":"Horvais","given":"Nicolas"},{"family":"Millet","given":"Guillaume Y."}],"issued":{"date-parts":[["2017",4]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Vernillo et al., 2015; 2017), donde se requieren una mayor demanda de aplicación de fuerza ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"1pjojljo8o","properties":{"formattedCitation":"(Gottschall & Kram, 2005)","plainCitation":"(Gottschall & Kram, 2005)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":"jd4YtdFl/pI6J6ZwV","uris":["http://zotero.org/groups/1616292/items/VES5WKJM"],"uri":["http://zotero.org/groups/1616292/items/VES5WKJM"],"itemData":{"id":3308,"type":"article-journal","title":"Ground reaction forces during downhill and uphill running","container-title":"Journal of Biomechanics","page":"445-452","volume":"38","issue":"3","source":"CrossRef","DOI":"10.1016/j.jbiomech.2004.04.023","ISSN":"00219290","language":"en","author":[{"family":"Gottschall","given":"Jinger S."},{"family":"Kram","given":"Rodger"}],"issued":{"date-parts":[["2005",3]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Gottschall y Kram, 2005). Se requiere de más información para ver su capacidad de detectar los cambios en el consumo energético debido al desnivel, ya que dicho cálculo está optimizado para estimación en deportes colectivos donde la superficie de trabajo es plana.En cuanto a la FCMEDIA, los resultados mostraron una gran variabilidad, dándose los datos más altos en las zonas de desnivel positivo (DP1 = 191.1 ± 1.31 ppm; DP2 = 189.33 ± 1.70 ppm). Todas las diferencias fueron significativas (p < 0.05; d = 0.52 - 2.05) exceptuando las que se desprendían de la comparación entre el tramo sin desnivel 2 y el tramo con desnivel negativo 2 (p = 0.37). Esto contrasta con lo recogido por ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"a1eoem661nm","properties":{"formattedCitation":"{\\rtf (Born, St\\uc0\\u246{}ggl, Swar\\uc0\\u233{}n, & Bj\\uc0\\u246{}rklund, 2017)}","plainCitation":"(Born, Stöggl, Swarén, & Björklund, 2017)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":"jd4YtdFl/Wwn77b6D","uris":["http://zotero.org/users/local/beObHR6h/items/6K23DIKN"],"uri":["http://zotero.org/users/local/beObHR6h/items/6K23DIKN"],"itemData":{"id":87,"type":"article-journal","title":"Near-Infrared Spectroscopy: More Accurate Than Heart Rate for Monitoring Intensity in Running in Hilly Terrain","container-title":"International Journal of Sports Physiology and Performance","page":"440-447","volume":"12","issue":"4","source":"CrossRef","DOI":"10.1123/ijspp.2016-0101","ISSN":"1555-0265, 1555-0273","shortTitle":"Near-Infrared Spectroscopy","language":"en","author":[{"family":"Born","given":"Dennis-Peter"},{"family":"Stöggl","given":"Thomas"},{"family":"Swarén","given":"Mikael"},{"family":"Björklund","given":"Glenn"}],"issued":{"date-parts":[["2017",4]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} Born, Stöggl, Swarén, y Björklund, (2017) donde no encontraron diferencias en la FCMEDIA en función del tipo de orografía, si encontrando estas en la saturación de oxígeno muscular (SmO2). Por otro lado, los resultados de la FC se encuentran en consonancia con ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"a24gqea13s2","properties":{"formattedCitation":"{\\rtf (Chatterjee et\\uc0\\u160{}al., 2015)}","plainCitation":"(Chatterjee et al., 2015)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":"jd4YtdFl/pTOhmpcX","uris":["http://zotero.org/users/local/beObHR6h/items/GG5KI2PQ"],"uri":["http://zotero.org/users/local/beObHR6h/items/GG5KI2PQ"],"itemData":{"id":85,"type":"article-journal","title":"Cardio-Respiratory and Metabolic Changes during Continuous Uphill-Downhill Load Carriage Task","source":"Google Scholar","URL":"http://inet.vidyasagar.ac.in:8080/jspui/handle/123456789/193","author":[{"family":"Chatterjee","given":"Tirthankar"},{"family":"Paul","given":"Sohini"},{"family":"Pramanik","given":"Anilendu"},{"family":"Chowdhury","given":"Bodhisattwa"},{"family":"Pal","given":"Madhu Sudan"},{"family":"Majumdar","given":"Dhurjati"}],"issued":{"date-parts":[["2015"]]},"accessed":{"date-parts":[["2017",7,3]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} Chatterjee et al. (2015) donde se muestra que los cambios de pendiente afectaron directamente al VO2 y al gasto cardiaco siendo más altos en las zonas con un desnivel positivo. Por lo cual, la FC es un buen indicador de la dificultad física durante la prueba, detectando con precisión la dificultad de los segmentos con inclinación positiva, pero no diferenciando entre los segmentos sin inclinación y con inclinación negativa.Las velocidades alcanzadas durante la carrera también variaron dependiendo del tipo de orografía del terreno, siendo mayores en los tramos donde no había desnivel. Las diferencias de velocidad entre los tramos sin desnivel y los de subida se deben, como se ha visto en distintos estudios ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"a1vcg50age9","properties":{"formattedCitation":"(Born et\\uc0\\u160{}al., 2017; Chatterjee et\\uc0\\u160{}al., 2015)","plainCitation":"(Born et al., 2017; Chatterjee et al., 2015)","noteIndex":0},"citationItems":[{"id":"jd4YtdFl/Wwn77b6D","uris":["http://zotero.org/users/local/beObHR6h/items/6K23DIKN"],"uri":["http://zotero.org/users/local/beObHR6h/items/6K23DIKN"],"itemData":{"id":87,"type":"article-journal","title":"Near-Infrared Spectroscopy: More Accurate Than Heart Rate for Monitoring Intensity in Running in Hilly Terrain","container-title":"International Journal of Sports Physiology and Performance","page":"440-447","volume":"12","issue":"4","source":"CrossRef","DOI":"10.1123/ijspp.2016-0101","ISSN":"1555-0265, 1555-0273","shortTitle":"Near-Infrared Spectroscopy","language":"en","author":[{"family":"Born","given":"Dennis-Peter"},{"family":"Stöggl","given":"Thomas"},{"family":"Swarén","given":"Mikael"},{"family":"Björklund","given":"Glenn"}],"issued":{"date-parts":[["2017",4]]}}},{"id":"jd4YtdFl/pTOhmpcX","uris":["http://zotero.org/users/local/beObHR6h/items/GG5KI2PQ"],"uri":["http://zotero.org/users/local/beObHR6h/items/GG5KI2PQ"],"itemData":{"id":85,"type":"article-journal","title":"Cardio-Respiratory and Metabolic Changes during Continuous Uphill-Downhill Load Carriage Task","source":"Google Scholar","URL":"http://inet.vidyasagar.ac.in:8080/jspui/handle/123456789/193","author":[{"family":"Chatterjee","given":"Tirthankar"},{"family":"Paul","given":"Sohini"},{"family":"Pramanik","given":"Anilendu"},{"family":"Chowdhury","given":"Bodhisattwa"},{"family":"Pal","given":"Madhu Sudan"},{"family":"Majumdar","given":"Dhurjati"}],"issued":{"date-parts":[["2015"]]},"accessed":{"date-parts":[["2017",7,3]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} (Born et al., 2017; Chatterjee et al., 2015) a una mayor demanda energética y un mayor consumo de oxígeno para mantener la intensidad. Por otro lado, la reducción de la velocidad en las zonas de desnivel negativo respecto a los segmentos sin desnivel se ha visto relacionada con el nivel técnico del corredor y la inclinación de la pendiente ADDIN ZOTERO_TEMP (Kay, 2014). De los resultados obtenidos para la ApEn, esta variable analiza la complejidad de la señal del dato bruto del acelerómetro, encontrado variaciones dependiendo del tipo de segmento, aunque no siendo estas significativas. Finalmente, en la variable stiffness muscular (KVERT) se encuentra que en los segmentos de desnivel positivo los valores fueron más bajos que en el resto de segmentos, siendo todas las diferencias significativas. Esto concuerda con el trabajo de ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"a2505lfudji","properties":{"formattedCitation":"{\\rtf (Giovanelli et\\uc0\\u160{}al., 2016)}","plainCitation":"(Giovanelli et al., 2016)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":"jd4YtdFl/xAV09uxp","uris":["http://zotero.org/users/local/beObHR6h/items/JBR2EF63"],"uri":["http://zotero.org/users/local/beObHR6h/items/JBR2EF63"],"itemData":{"id":91,"type":"article-journal","title":"Effects of an Uphill Marathon on Running Mechanics and Lower-Limb Muscle Fatigue","container-title":"International Journal of Sports Physiology and Performance","page":"522-529","volume":"11","issue":"4","source":"CrossRef","DOI":"10.1123/ijspp.2014-0602","ISSN":"1555-0265, 1555-0273","language":"en","author":[{"family":"Giovanelli","given":"Nicola"},{"family":"Taboga","given":"Paolo"},{"family":"Rejc","given":"Enrico"},{"family":"Simunic","given":"Bostjan"},{"family":"Antonutto","given":"Guglielmo"},{"family":"Lazzer","given":"Stefano"}],"issued":{"date-parts":[["2016",5]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} Giovanelli et al. (2016), donde se demostró que la fatiga en subida disminuye la capacidad para aplicar fuerza máxima, lo que afecta de forma directa al KVERT. Además, también se encontraron diferencias significativas entre los segmentos sin desnivel con los segmentos con desnivel negativo los cuales pudieron verse afectados por la fatiga acumulada durante el resto de la prueba ya que el estudio de ADDIN ZOTERO_ITEM CSL_CITATION {"citationID":"aeetm0rdc","properties":{"formattedCitation":"{\\rtf (Vernillo et\\uc0\\u160{}al., 2015)}","plainCitation":"(Vernillo et al., 2015)","dontUpdate":true,"noteIndex":0},"citationItems":[{"id":"jd4YtdFl/ldPyW63g","uris":["http://zotero.org/users/local/beObHR6h/items/PI85VUNT"],"uri":["http://zotero.org/users/local/beObHR6h/items/PI85VUNT"],"itemData":{"id":89,"type":"article-journal","title":"Energy cost and kinematics of level, uphill and downhill running: fatigue-induced changes after a mountain ultramarathon","container-title":"Journal of Sports Sciences","page":"1998-2005","volume":"33","issue":"19","source":"CrossRef","DOI":"10.1080/02640414.2015.1022870","ISSN":"0264-0414, 1466-447X","shortTitle":"Energy cost and kinematics of level, uphill and downhill running","language":"en","author":[{"family":"Vernillo","given":"Gianluca"},{"family":"Savoldelli","given":"Aldo"},{"family":"Zignoli","given":"Andrea"},{"family":"Skafidas","given":"Spyros"},{"family":"Fornasiero","given":"Alessandro"},{"family":"La Torre","given":"Antonio"},{"family":"Bortolan","given":"Lorenzo"},{"family":"Pellegrini","given":"Barbara"},{"family":"Schena","given":"Federico"}],"issued":{"date-parts":[["2015",11,26]]}}}],"schema":"https://github.com/citation-style-language/schema/raw/master/csl-citation.json"} Vernillo et al. (2015) demostró que el coste energético post carrera aumentaba en la bajada caracterizado por un menor tiempo de vuelo y un mayor número de pasos que demuestran una menor capacidad de aplicación de fuerza.CONCLUSIONESLa carga externa e interna difiere significativamente durante la carrera de montaña entre los diferentes segmentos que compone la prueba en función del desnivel.La pendiente positiva provoca una mayor carga interna registrada mediante FCMEDIA, mientras que los segmentos sin desnivel provoca una mayor carga externa registrada mediante PL/min, PM/min y KVERT. La mayor velocidad se encontró en los tramos sin desnivel. La variable velocidad de desplazamiento y las variables de carga externa registradas (PM/min, PL/min y KVERT) mostraron una dinámica similar en los segmentos analizados.Las variables PL/min y KVERT se encontraron como las variables útiles para el análisis de las exigencias de las carreras de montaña debido a su alta sensibilidad para discriminar los diferentes tipos de pendiente (positiva, negativa y sin pendiente).APLICACIONES PRÁCTICAS Y PROPUESTAS DE INVESTIGACIÓNLa utilización de los sistemas inerciales, así como las variables medidas representativas de los cambios de orografía del terreno, pueden dar una visión más acertada de las exigencias en las carreras de montaña. Y así, a partir de esta información, diseñar entrenamientos específicos en base a la carga real en competición para evitar lesiones y sobre-entrenamiento. La falta de estudios en torno a esta materia y la dificultad de la cuantificación del entrenamiento de esta modalidad por la variabilidad del terreno y las dispares demandas mecánicas y fisiológicas que se dan, hace necesaria una mayor investigación sobre la temática del estudio. Futuras investigaciones deberían seguir esta línea de análisis modificando la secuencia de desniveles, así como el grado de pendiente de estos para tratar de determinar cómo afectan en el rendimiento. Además, parece necesario el análisis con un mayor número de participantes y de competiciones para comparar la carga del corredor tanto intra-sujeto en diferentes competiciones como inter-sujetos dentro de una misma competición.Es necesario ampliar la evidencia científica de la influencia de la fatiga, deshidratación, temperatura ambiental, e impacto neuromuscular, entre otras condiciones presentes en este tipo de pruebas de fondo y ultra fondo en la variabilidad de la carga externa e interna.REFERENCIA BIBLIOGRÁFICA ADDIN ZOTERO_BIBL {"uncited":[],"omitted":[],"custom":[[["http://zotero.org/users/3024263/items/47X22MH5"],"Bastida Castillo, A., G\\uc0\\u243{}mez-Carmona, C. D., y Pino Ortega, J. (2016). Efectos del Tipo de Recuperaci\\uc0\\u243{}n Sobre la Oxigenaci\\uc0\\u243{}n Muscular Durante el Ejercicio de Sentadilla. {\\i{}Kronos}, {\\i{}15}(2), 1-13."],[["http://zotero.org/groups/729592/items/F9T3AWCI"],"Barrett, S., Midgley, A. W., Towlson, C., Garrett, A., Portas, M., y Lovell, R. (2016). Within-Match PlayerLoad\\super TM\\nosupersub{} Patterns during a Simulated Soccer Match: Potential Implications for Unit Positioning and Fatigue Management. {\\i{}International Journal of Sports Physiology and Performance}, {\\i{}11}(1), 135-140. https://doi.org/10.1123/ijspp.2014-0582"],[["http://zotero.org/groups/729592/items/W26I9MBR"],"Barrett, S., Midgley, A., y Lovell, R. (2014). PlayerLoad\\super TM\\nosupersub{}: Reliability, Convergent Validity, and Influence of Unit Position during Treadmill Running. {\\i{}International Journal of Sports Physiology and Performance}, {\\i{}9}(6), 945-952. https://doi.org/10.1123/ijspp.2013-0418"],[["http://zotero.org/groups/729592/items/NQIP98PB"],"Boyd, L. J., Ball, K., y Aughey, R. J. (2013). Quantifying external load in Australian football matches and training using accelerometers. {\\i{}Int J Sports Physiol Perform}, {\\i{}8}(1), 44\\uc0\\u8211{}51."],[["http://zotero.org/groups/729592/items/3H3ZF95F"],"Nedergaard, N. J., Robinson, M. A., Eusterwiemann, E., Drust, B., Lisboa, P. J., y Vanrenterghem, J. (2017). The Relationship Between Whole-Body External Loading and Body-Worn Accelerometry During Team-Sport Movements. {\\i{}International Journal of Sports Physiology and Performance}, {\\i{}12}(1), 18-26. https://doi.org/10.1123/ijspp.2015-0712"],[["http://zotero.org/groups/729592/items/2BN5WUID"],"Barreira, P., Robinson, M. A., Drust, B., Nedergaard, N., Raja Azidin, R. M. F., y Vanrenterghem, J. (2017). Mechanical Player Load using trunk-mounted accelerometry in football: Is it a reliable, task- and player-specific observation? {\\i{}Journal of Sports Sciences}, {\\i{}35}(17), 1674-1681. https://doi.org/10.1080/02640414.2016.1229015"],[["http://zotero.org/groups/729592/items/ARUIJT7J"],"Hopkins, W. G., Marshall, S. W., Batterham, A. M., y Hanin, J. (2009). Progressive Statistics for Studies in Sports Medicine and Exercise Science: {\\i{}Medicine & Science in Sports & Exercise}, {\\i{}41}(1), 3-13. https://doi.org/10.1249/MSS.0b013e31818cb278"],[["http://zotero.org/groups/844373/items/DJBSB3V2"],"Bastida-Castillo, A., G\\uc0\\u243{}mez-Carmona, C. D., De la Cruz S\\uc0\\u225{}nchez, E., y Pino-Ortega, J. (2018). Accuracy, intra- and inter-unit reliability, and comparison between GPS and UWB-based position-tracking systems used for time\\uc0\\u8211{}motion analyses in soccer. {\\i{}European Journal of Sport Science}, {\\i{}18}(4), 450-457. https://doi.org/10.1080/17461391.2018.1427796"],[["http://zotero.org/groups/1726566/items/G6WWPIE7"],"Molina-Carmona, I., Gomez-Carmona, C. D., Bastida Castillo, A., y Pino-Ortega, J. (2018). Validez del dispositivo inercial WIMU PRO\\super TM\\nosupersub{}\\uc0\\u65039{} para el registro de la frecuencia card\\uc0\\u237{}aca en un test de campo. {\\i{}Sport-TK: Revista Euroamericana de Ciencias del Deporte}, {\\i{}7}, 81-86."],[["http://zotero.org/groups/729592/items/4Z98VWC6"],"G\\uc0\\u243{}mez-Carmona, C. D., Bastida-Castillo, A., Garc\\uc0\\u237{}a-Rubio, J., Ib\\uc0\\u225{}\\uc0\\u241{}ez, S. J., y Pino-Ortega, J. (2019). Static and dynamic reliability of WIMU PROTM accelerometers according to anatomical placement. {\\i{}Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology}, {\\i{}233}(2), 238-248."],[["http://zotero.org/groups/844373/items/FR4TEXVZ"],"Reche-Soto, P., Cardona-Nieto, D., Diaz-Suarez, A., Bastida-Castillo, A., Gomez-Carmona, C., Garcia-Rubio, J., y Pino-Ortega, J. (2018). Player Load and Metabolic Power Dynamics as Load Quantifiers in Soccer. {\\i{}Journal of Human Kinetics}, {\\i{}Epub: Ahead of Print}. http://www.doi.org/10.2478/hukin-2018-0072"],[["http://zotero.org/groups/845255/items/QLAB4I3X"],"G\\uc0\\u243{}mez-Carmona, C. D., Bastida-Castillo, A., Gonz\\uc0\\u225{}lez-Custodio, A., Olcina, G., y Pino-Ortega, J. (2019). Using an inertial device (WIMU PRO\\super TM\\nosupersub{}\\uc0\\u65039{}) to quantify neuromuscular load in running: Reliability, convergent validity and the influence of type of surface and device location. {\\i{}The Journal of Strength and Conditioning Research}, {\\i{}Pendiente de Publicaci\\uc0\\u243{}n.} https://doi.org/10.1519/JSC.0000000000003106"],[["http://zotero.org/groups/844373/items/B6TRY6TL"],"Reche-Soto, P., Cardona-Nieto, D., Diaz-Suarez, A., Gomez-Carmona, C., y Pino-Ortega, J. (2019). AcelT y PlayerLoad\\super TM\\nosupersub{}\\uc0\\u65039{}: Dos variables para la cuantificaci\\uc0\\u243{}n de la carga neuromuscular. {\\i{}Revista Internacional de Medicina y Ciencias de la Actividad F\\uc0\\u237{}sica y del Deporte}, {\\i{}Pendiente de publicaci\\uc0\\u243{}n}."],[["http://zotero.org/groups/1616292/items/2YV2Y5LH"],"Kerherv\\uc0\\u233{}, H. A., Millet, G. Y., y Solomon, C. (2015). The Dynamics of Speed Selection and Psycho-Physiological Load during a Mountain Ultramarathon. {\\i{}PLoS ONE}, {\\i{}10}(12), e0145482. https://doi.org/10.1371/journal.pone.0145482"],[["http://zotero.org/groups/1616292/items/JR4ZKGCC"],"Banister, E. W. (1991). Modeling elite athletic performance. En H.J. Green, J.D. McDougar y H. Wenger (Eds.) {\\i{}Physiological Testing of Elite Athletes} (pp. 403-424). Champaign, Illinois: Human Kinetics."],[["http://zotero.org/groups/1616292/items/W3HFT498"],"Buceta, J. M., L\\uc0\\u243{}pez de la Llave, A., P\\uc0\\u233{}rez-Llantada, M.C., Vallejo, M., y del Pino, M.D. (2007). Intervenci\\uc0\\u243{}n psicol\\uc0\\u243{}gica con corredores de marat\\uc0\\u243{}n: Caracter\\uc0\\u237{}sticas y valoraci\\uc0\\u243{}n del programa aplicado en el marat\\uc0\\u243{}n de Madrid. {\\i{}Revista de Psicolog\\uc0\\u237{}a del Deporte}, {\\i{}11}(1), 83-109."],[["http://zotero.org/users/local/beObHR6h/items/6K23DIKN"],"Born, D.-P., St\\uc0\\u246{}ggl, T., Swar\\uc0\\u233{}n, M., y Bj\\uc0\\u246{}rklund, G. (2017). Near-Infrared Spectroscopy: More Accurate Than Heart Rate for Monitoring Intensity in Running in Hilly Terrain. {\\i{}International Journal of Sports Physiology and Performance}, {\\i{}12}(4), 440-447. https://doi.org/10.1123/ijspp.2016-0101"],[["http://zotero.org/users/local/beObHR6h/items/JP27GEEG"],"Borresen, J., y Lambert, M. I. (2009). The quantification of training load, the training response and the effect on performance. {\\i{}Sports Medicine}, {\\i{}39}(9), 779\\uc0\\u8211{}795."],[["http://zotero.org/users/local/o7j2npH8/items/DJP4AF8P"],"Bouzas, J. C., Ottoline, N. M., y Delgado, M. (2010). Aplicaciones de la frecuencia cardiaca m\\uc0\\u225{}xima en la evaluaci\\uc0\\u243{}n y prescripci\\uc0\\u243{}n de ejercicio. {\\i{}Apunts. Medicina de l\\uc0\\u8217{}Esport}, {\\i{}45}(168), 251-258. https://doi.org/10.1016/j.apunts.2010.04.003"],[["http://zotero.org/users/local/beObHR6h/items/7D97BB3A"],"Buchheit, M., Gray, A., y Morin, J.B. (2015). Assessing stride variables and vertical stiffness with GPS-embedded accelerometers: Preliminary insights for the monitoring of neuromuscular fatigue on the field. {\\i{}Journal of sports science & medicine}, {\\i{}14}(4), 698-701."],[["http://zotero.org/users/local/beObHR6h/items/GG5KI2PQ"],"Chatterjee, T., Paul, S., Pramanik, A., Chowdhury, B., Pal, M. S., y Majumdar, D. (2015). Cardio-Respiratory and Metabolic Changes during Continuous Uphill-Downhill Load Carriage Task. {\\i{}Ergonomics for Rural Development, }3-10. Recuperado de: http://inet.vidyasagar.ac.in:8080/jspui/handle/123456789/193"],[["http://zotero.org/users/local/beObHR6h/items/XR238B3I"],"Cormack, S. J., Mooney, M. G., Morgan, W., y McGuigan, M. R. (2013). Influence of neuromuscular fatigue on accelerometer load in elite Australian football players. {\\i{}International journal of sports physiology and performance}, {\\i{}8}(4), 373\\uc0\\u8211{}378."],[["http://zotero.org/groups/1616292/items/35NIRPZQ"],"Eich, T. S., y Metcalfe, J. (2009). Effects of the stress of marathon running on implicit and explicit memory. {\\i{}Psychonomic Bulletin & Review}, {\\i{}16}(3), 475-479. https://doi.org/10.3758/PBR.16.3.475"],[["http://zotero.org/users/local/beObHR6h/items/JBR2EF63"],"Giovanelli, N., Taboga, P., Rejc, E., Simunic, B., Antonutto, G., y Lazzer, S. (2016). Effects of an Uphill Marathon on Running Mechanics and Lower-Limb Muscle Fatigue. {\\i{}International Journal of Sports Physiology and Performance}, {\\i{}11}(4), 522-529. https://doi.org/10.1123/ijspp.2014-0602"],[["http://zotero.org/groups/1616292/items/VES5WKJM"],"Gottschall, J. S., y Kram, R. (2005). Ground reaction forces during downhill and uphill running. {\\i{}Journal of Biomechanics}, {\\i{}38}(3), 445-452. https://doi.org/10.1016/j.jbiomech.2004.04.023"],[["http://zotero.org/groups/1616292/items/KV3E2BP3"],"Hughson, R. L., Weisiger, K. H., y Swanson, G. D. (1987). Blood lactate concentration increases as a continuous function in progressive exercise. {\\i{}Journal of Applied Physiology}, {\\i{}62}(5), 1975-1981."],[["http://zotero.org/users/local/beObHR6h/items/GR6MMXG8"],"Jobson, S. A., Passfield, L., Atkinson, G., Barton, G., y Scarf, P. (2009). The analysis and utilization of cycling training data. {\\i{}Sports medicine}, {\\i{}39}(10), 833\\uc0\\u8211{}844."],[["http://zotero.org/groups/1616292/items/U2M4KV89"],"Kyr\\uc0\\u246{}l\\uc0\\u228{}inen, H., Pullinen, T., Candau, R., Avela, J., Huttunen, P., y Komi, P. V. (2000). Effects of marathon running on running economy and kinematics. {\\i{}European journal of applied physiology}, {\\i{}82}(4), 297\\uc0\\u8211{}304."],[["http://zotero.org/groups/1616292/items/QJB7H94B"],"Millet, G., Martin, V., Lattier, G., y Ballay, Y. (2003). Mechanisms contributing to knee extensor strength loss after prolonged running exercise. {\\i{}Journal of Applied Physiology}, {\\i{}94}(1), 193-198. https://doi.org/10.1152/japplphysiol.00600.2002"],[["http://zotero.org/groups/1616292/items/FVERFRF7"],"Millet, Guillaume Y., Morin, J.-B., Degache, F., Edouard, P., Feasson, L., Verney, J., y Oullion, R. (2009). Running from Paris to Beijing: Biomechanical and physiological consequences. {\\i{}European Journal of Applied Physiology}, {\\i{}107}(6), 731-738. https://doi.org/10.1007/s00421-009-1194-3"],[["http://zotero.org/groups/1616292/items/P62V6CS3"],"Morin, J. B., Tomazin, K., Edouard, P., y Millet, G. Y. (2011). Changes in running mechanics and spring\\uc0\\u8211{}mass behavior induced by a mountain ultra-marathon race. {\\i{}Journal of Biomechanics}, {\\i{}44}(6), 1104-1107. https://doi.org/10.1016/j.jbiomech.2011.01.028"],[["http://zotero.org/groups/1616292/items/Q2UJDB5E"],"Morin, Jean-Beno\\uc0\\u238{}t, Dalleau, G., Kyr\\uc0\\u246{}l\\uc0\\u228{}inen, H., Jeannin, T., y Belli, A. (2005). A Simple Method for Measuring Stiffness during Running. {\\i{}Journal of Applied Biomechanics}, {\\i{}21}(2), 167-180. https://doi.org/10.1123/jab.21.2.167"],[["http://zotero.org/groups/1616292/items/JMDDZ3IG"],"Morin, Jean-Beno\\uc0\\u238{}T, Samozino, P., y Millet, G. Y. (2011). Changes in Running Kinematics, Kinetics, and Spring-Mass Behavior over a 24-h Run: {\\i{}Medicine & Science in Sports & Exercise}, {\\i{}43}(5), 829-836. https://doi.org/10.1249/MSS.0b013e3181fec518"],[["http://zotero.org/groups/1616292/items/8ZRFNFJE"],"Nicol, C., Komi, P. V., y Marconnet, P. (2007). Effects of marathon fatigue on running kinematics and economy. {\\i{}Scandinavian Journal of Medicine & Science in Sports}, {\\i{}1}(4), 195-204. https://doi.org/10.1111/j.1600-0838.1991.tb00296.x"],[["http://zotero.org/users/local/beObHR6h/items/VX459NDM"],"Osgnach, C., Poser, S., Bernardini, R., Rinaldo, R., y Di Prampero, P. E. (2010). Energy Cost and Metabolic Power in Elite Soccer: A New Match Analysis Approach. {\\i{}Medicine & Science in Sports & Exercise}, {\\i{}42}(1), 170-178. https://doi.org/10.1249/MSS.0b013e3181ae5cfd"],[["http://zotero.org/groups/1616292/items/K477REUT"],"Ruiz-Juan, F., y Zarauz, A. (2014). An\\uc0\\u225{}lisis de la motivaci\\uc0\\u243{}n en corredores de marat\\uc0\\u243{}n espa\\uc0\\u241{}oles. {\\i{}Revista Latinoamericana de Psicologia}, {\\i{}46}(1), 1\\uc0\\u8211{}11."],[["http://zotero.org/users/local/beObHR6h/items/ZESMUU2W"],"Sparks, M., Coetzee, B., y Gabbett, T. J. (2017). Internal and External Match Loads of University-Level Soccer Players: A Comparison Between Methods. {\\i{}Journal of Strength and Conditioning Research}, {\\i{}31}(4), 1072-1077. https://doi.org/10.1519/JSC.0000000000001560"],[["http://zotero.org/users/local/beObHR6h/items/XB4D7QUU"],"Taylor, K., Chapman, D., Cronin, J., Newton, M. J., y Gill, N. (2012). Fatigue monitoring in high performance sport: A survey of current trends. {\\i{}J Aust Strength Cond}, {\\i{}20}(1), 12\\uc0\\u8211{}23."],[["http://zotero.org/users/local/beObHR6h/items/U4IZDJXI"],"Twist, C., y Highton, J. (2013). Monitoring fatigue and recovery in rugby league players. {\\i{}International Journal of sports physiology and performance}, {\\i{}8}(5), 467\\uc0\\u8211{}474."],[["http://zotero.org/groups/1616292/items/9EE4WAK9"],"Urdampilleta, A., L\\uc0\\u243{}pez-Grueso, R., Mart\\uc0\\u237{}nez-Sanz, J. M., y Mielgo-Ayuso, J. (2014). Par\\uc0\\u225{}metros bioqu\\uc0\\u237{}micos b\\uc0\\u225{}sicos, hematol\\uc0\\u243{}gicos y hormonales para el control de la salud y el estado nutricional en los deportistas. {\\i{}Revista Espa\\uc0\\u241{}ola de Nutrici\\uc0\\u243{}n Humana y Diet\\uc0\\u233{}tica}, {\\i{}18}(3), 155\\uc0\\u8211{}171."],[["http://zotero.org/groups/1616292/items/8WIAB4XF"],"Uth, N., Sorensen, H., Overgaard, K., y Pedersen, P. K. (2004). Estimation of VO2max from the ratio between HRmax and HRrest? The Heart Rate Ratio Method. {\\i{}European Journal of Applied Physiology}, {\\i{}91}(1), 111-115. https://doi.org/10.1007/s00421-003-0988-y"],[["http://zotero.org/users/local/beObHR6h/items/VZ34SE8A"],"Vernillo, G., Giandolini, M., Edwards, W. B., Morin, J.-B., Samozino, P., Horvais, N., y Millet, G. Y. (2017). Biomechanics and Physiology of Uphill and Downhill Running. {\\i{}Sports Medicine}, {\\i{}47}(4), 615-629. https://doi.org/10.1007/s40279-016-0605-y"]]} CSL_BIBLIOGRAPHY Banister, E. W. (1991). Modeling elite athletic performance. En H.J. Green, J.D. McDougar y H. Wenger (Eds.) Physiological Testing of Elite Athletes (pp. 403-424). Champaign, Illinois: Human Kinetics.Barreira, P., Robinson, M. A., Drust, B., Nedergaard, N., Raja Azidin, R. M. F., y Vanrenterghem, J. (2017). Mechanical Player Load using trunk-mounted accelerometry in football: Is it a reliable, task- and player-specific observation? Journal of Sports Sciences, 35(17), 1674-1681. https://doi.org/10.1080/02640414.2016.1229015Barrett, S., Midgley, A., y Lovell, R. (2014). PlayerLoadTM: Reliability, Convergent Validity, and Influence of Unit Position during Treadmill Running. International Journal of Sports Physiology and Performance, 9(6), 945-952. https://doi.org/10.1123/ijspp.2013-0418Barrett, S., Midgley, A. W., Towlson, C., Garrett, A., Portas, M., y Lovell, R. (2016). Within-Match PlayerLoadTM Patterns during a Simulated Soccer Match: Potential Implications for Unit Positioning and Fatigue Management. International Journal of Sports Physiology and Performance, 11(1), 135-140. https://doi.org/10.1123/ijspp.2014-0582Bastida-Castillo, A., Gómez-Carmona, C. D., De la Cruz Sánchez, E., y Pino-Ortega, J. (2018). Accuracy, intra- and inter-unit reliability, and comparison between GPS and UWB-based position-tracking systems used for time–motion analyses in soccer. European Journal of Sport Science, 18(4), 450-457. https://doi.org/10.1080/17461391.2018.1427796Bastida-Castillo, A., Gómez-Carmona, C. D., y Pino-Ortega, J. (2016). Efectos del Tipo de Recuperación Sobre la Oxigenación Muscular Durante el Ejercicio de Sentadilla. Kronos, 15(2), 1-13.Born, D.-P., Stöggl, T., Swarén, M., y Björklund, G. (2017). Near-Infrared Spectroscopy: More Accurate Than Heart Rate for Monitoring Intensity in Running in Hilly Terrain. International Journal of Sports Physiology and Performance, 12(4), 440-447. https://doi.org/10.1123/ijspp.2016-0101Borresen, J., y Lambert, M. I. (2009). The quantification of training load, the training response and the effect on performance. Sports Medicine, 39(9), 779–795. https://doi.org/10.2165/11317780-000000000-00000Bouzas, J. C., Ottoline, N. M., y Delgado, M. (2010). Aplicaciones de la frecuencia cardiaca máxima en la evaluación y prescripción de ejercicio. Apunts. Medicina de l’Esport, 45(168), 251-258. https://doi.org/10.1016/j.apunts.2010.04.003Boyd, L. J., Ball, K., y Aughey, R. J. (2013). Quantifying external load in Australian football matches and training using accelerometers. Int J Sports Physiol Perform, 8(1), 44–51. https://doi.org/10.1123/ijspp.8.1.44Buceta, J. M., López de la Llave, A., Pérez-Llantada, M.C., Vallejo, M., y del Pino, M.D. (2007). Intervención psicológica con corredores de maratón: Características y valoración del programa aplicado en el maratón de Madrid. Revista de Psicología del Deporte, 11(1), 83-109.Buchheit, M., Gray, A., y Morin, J.B. (2015). Assessing stride variables and vertical stiffness with GPS-embedded accelerometers: Preliminary insights for the monitoring of neuromuscular fatigue on the field. Journal of sports science & medicine, 14(4), 698-701.Chatterjee, T., Paul, S., Pramanik, A., Chowdhury, B., Pal, M. S., y Majumdar, D. (2015). Cardio-Respiratory and Metabolic Changes during Continuous Uphill-Downhill Load Carriage Task. Ergonomics for Rural Development, 3-10. Recuperado de: http://inet.vidyasagar.ac.in:8080/jspui/handle/123456789/193Consejo Superior de Deportes. (2016). Encuesta sobre los hábitos deportivos en España (2015). Madrid: Consejo Superior de Deportes y Centro de Investigaciones Sociológicas.Cormack, S. J., Mooney, M. G., Morgan, W., y McGuigan, M. R. (2013). Influence of neuromuscular fatigue on accelerometer load in elite Australian football players. International journal of sports physiology and performance, 8(4), 373–378. https://doi.org/10.1123/ijspp.8.4.373Eich, T. S., y Metcalfe, J. (2009). Effects of the stress of marathon running on implicit and explicit memory. Psychonomic Bulletin & Review, 16(3), 475-479. https://doi.org/10.3758/PBR.16.3.475Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics (4.a ed.). Londres: SAGE.Gabbett, T. (2013). Quantifying the Physical Demands of Collision Sports: Does Microsensor Technology Measure What It Claims to Measure? Journal of Strength and Conditioning Research, 27(8), 2319-2322. https://doi.org/10.1519/JSC.0b013e318277fd21Giovanelli, N., Taboga, P., Rejc, E., Simunic, B., Antonutto, G., y Lazzer, S. (2016). Effects of an Uphill Marathon on Running Mechanics and Lower-Limb Muscle Fatigue. International Journal of Sports Physiology and Performance, 11(4), 522-529. https://doi.org/10.1123/ijspp.2014-0602Gómez-Carmona, C. D., Bastida-Castillo, A., García-Rubio, J., Ibáñez, S. J., y Pino-Ortega, J. (2019). Static and dynamic reliability of WIMU PROTM accelerometers according to anatomical placement. Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology, 233(2), 238-248. https://doi.org/10.1177/1754337118816922Gómez-Carmona, C. D., Bastida-Castillo, A., González-Custodio, A., Olcina, G., y Pino-Ortega, J. (2019). Using an inertial device (WIMU PROTM️) to quantify neuromuscular load in running: Reliability, convergent validity and the influence of type of surface and device location. The Journal of Strength and Conditioning Research, 34(2), 365-373. https://doi.org/10.1519/JSC.0000000000003106Gottschall, J. S., y Kram, R. (2005). Ground reaction forces during downhill and uphill running. Journal of Biomechanics, 38(3), 445-452. https://doi.org/10.1016/j.jbiomech.2004.04.023Gutiérrez-Vargas, R., Martín-Rodríguez, S., Sánchez-Ureña, B., Rodríguez-Montero, A., Salas-Cabrera, J., Gutiérrez-Vargas, J. C., … Rojas-Valverde, D. (2020). Biochemical and Muscle Mechanical Postmarathon Changes in Hot and Humid Conditions: Journal of Strength and Conditioning Research, 34(3), 847-856. https://doi.org/10.1519/JSC.0000000000002746Gutiérrez-Vargas, R., Ugalde-Ramírez, J. A., Rojas-Valverde, D., Salas-Cabrera, J., Rodríguez-Montero, A., & Gutiérrez-Vargas, J. C. (2017). La termografía infrarroja como herramienta efectiva para detectar áreas músculares dañadas después de correr una maratón. Revista de la Facultad de Medicina, 65(4), 601-607. https://doi.org/10.15446/revfacmed.v65n4.60638Halson, S. L. (2014). Monitoring Training Load to Understand Fatigue in Athletes. Sports Medicine, 44(S2), 139-147. https://doi.org/10.1007/s40279-014-0253-zHopkins, W. G., Marshall, S. W., Batterham, A. M., y Hanin, J. (2009). Progressive Statistics for Studies in Sports Medicine and Exercise Science: Medicine & Science in Sports & Exercise, 41(1), 3-13. https://doi.org/10.1249/MSS.0b013e31818cb278Hughson, R. L., Weisiger, K. H., y Swanson, G. D. (1987). Blood lactate concentration increases as a continuous function in progressive exercise. Journal of Applied Physiology, 62(5), 1975-1981. https://doi.org/10.1152/jappl.1987.62.5.1975Jobson, S. A., Passfield, L., Atkinson, G., Barton, G., y Scarf, P. (2009). The analysis and utilization of cycling training data. Sports medicine, 39(10), 833–844. https://doi.org/10.2165/11317840-000000000-00000Kerhervé, H. A., Millet, G. Y., y Solomon, C. (2015). The Dynamics of Speed Selection and Psycho-Physiological Load during a Mountain Ultramarathon. PLoS ONE, 10(12), e0145482. https://doi.org/10.1371/journal.pone.0145482Kyröläinen, H., Pullinen, T., Candau, R., Avela, J., Huttunen, P., y Komi, P. V. (2000). Effects of marathon running on running economy and kinematics. European Journal of Applied Physiology, 82(4), 297–304. https://doi.org/10.1007/s004210000219Martin, V., Kerherve, H., Messonnier, L. A., Banfi, J. C., Geyssant, A., Bonnefoy, R., … Millet, G. Y. (2010). Central and peripheral contributions to neuromuscular fatigue induced by a 24-h treadmill run. Journal of Applied Physiology, 108(5), 1224-1233. https://doi.org/10.1152/japplphysiol.01202.2009Millet, G. (2011). Can Neuromuscular Fatigue Explain Running Strategies and Performance in Ultra-Marathons?: The Flush Model. Sports Medicine, 41(6), 489-506. https://doi.org/10.2165/11588760-000000000-00000Millet, G., Martin, V., Lattier, G., y Ballay, Y. (2003). Mechanisms contributing to knee extensor strength loss after prolonged running exercise. Journal of Applied Physiology, 94(1), 193-198. https://doi.org/10.1152/japplphysiol.00600.2002Millet, G. Y., Banfi, J. C., Kerherve, H., Morin, J. B., Vincent, L., Estrade, C., … Feasson, L. (2011). Physiological and biological factors associated with a 24 h treadmill ultra-marathon performance: Factors associated with ultra-marathon performance. Scandinavian Journal of Medicine & Science in Sports, 21(1), 54-61. https://doi.org/10.1111/j.1600-0838.2009.01001.xMillet, Guillaume, Tomazin, K., Verges, S., Vincent, C., Bonnefoy, R., Boisson, R.-C., … Martin, V. (2011). Neuromuscular Consequences of an Extreme Mountain Ultra-Marathon. PLoS ONE, 6(2), e17059. https://doi.org/10.1371/journal.pone.0017059Millet, Guillaume Y., Morin, J.-B., Degache, F., Edouard, P., Feasson, L., Verney, J., y Oullion, R. (2009). Running from Paris to Beijing: Biomechanical and physiological consequences. European Journal of Applied Physiology, 107(6), 731-738. https://doi.org/10.1007/s00421-009-1194-3Molina-Carmona, I., Gomez-Carmona, C. D., Bastida Castillo, A., y Pino-Ortega, J. (2018). Validez del dispositivo inercial WIMU PROTM️ para el registro de la frecuencia cardíaca en un test de campo. Sport-TK: Revista Euroamericana de Ciencias del Deporte, 7, 81-86. https://doi.org/10.6018/321921Morin, J. B., Tomazin, K., Edouard, P., y Millet, G. Y. (2011). Changes in running mechanics and spring–mass behavior induced by a mountain ultra-marathon race. Journal of Biomechanics, 44(6), 1104-1107. https://doi.org/10.1016/j.jbiomech.2011.01.028Morin, J. B., Dalleau, G., Kyröläinen, H., Jeannin, T., y Belli, A. (2005). A Simple Method for Measuring Stiffness during Running. Journal of Applied Biomechanics, 21(2), 167-180. https://doi.org/10.1123/jab.21.2.167Morin, J. B., Samozino, P., y Millet, G. Y. (2011). Changes in Running Kinematics, Kinetics, and Spring-Mass Behavior over a 24-h Run: Medicine & Science in Sports & Exercise, 43(5), 829-836. https://doi.org/10.1249/MSS.0b013e3181fec518Nedergaard, N. J., Robinson, M. A., Eusterwiemann, E., Drust, B., Lisboa, P. J., y Vanrenterghem, J. (2017). The Relationship Between Whole-Body External Loading and Body-Worn Accelerometry During Team-Sport Movements. International Journal of Sports Physiology and Performance, 12(1), 18-26. https://doi.org/10.1123/ijspp.2015-0712Nicol, C., Komi, P. V., y Marconnet, P. (2007). Effects of marathon fatigue on running kinematics and economy. Scandinavian Journal of Medicine & Science in Sports, 1(4), 195-204. https://doi.org/10.1111/j.1600-0838.1991.tb00296.xOsgnach, C., Poser, S., Bernardini, R., Rinaldo, R., y Di Prampero, P. E. (2010). Energy Cost and Metabolic Power in Elite Soccer: A New Match Analysis Approach. Medicine & Science in Sports & Exercise, 42(1), 170-178. https://doi.org/10.1249/MSS.0b013e3181ae5cfdPichot, V., Roche, F., Gaspoz, J.-M., Enjolras, F., Antoniadis, A., Minini, P., … Barthelemy, J. C. (2000). Relation between heart rate variability and training load in middle-distance runners. Medicine and Science in Sports and Exercise, 32(10), 1729–1736. https://doi.org/10.1097/00005768-200010000-00011Pincus, S. M. (2001). Assessing serial irregularity and its implications for health. Annals of the New York Academy of Sciences, 954(1), 245–267. https://doi.org/10.1111/j.1749-6632.2001.tb02755.xReche-Soto, P., Cardona-Nieto, D., Diaz-Suarez, A., Bastida-Castillo, A., Gomez-Carmona, C., Garcia-Rubio, J., y Pino-Ortega, J. (2019). Player Load and Metabolic Power Dynamics as Load Quantifiers in Soccer. Journal of Human Kinetics, 69(1), 259-269. http://www.doi.org/10.2478/hukin-2018-0072Reche-Soto, P., Cardona-Nieto, D., Diaz-Suarez, A., Gomez-Carmona, C., y Pino-Ortega, J. (2020). AcelT y PlayerLoadTM️: Dos variables para la cuantificación de la carga neuromuscular. Revista Internacional de Medicina y Ciencias de la Actividad Física y del Deporte, 20(77), 167-183. https://doi.org/10.15366/rimcafd2020.77.011Rojas-Valverde, D. (2019). Brief historical review of distance and ultradistance runnig in Costa Rica and the world. Viref:revista de Educación Física, 8(1), 1-19.Ruiz-Juan, F., y Zarauz, A. (2014). Análisis de la motivación en corredores de maratón españoles. Revista Latinoamericana de Psicologia, 46(1), 1–11. https://doi.org/10.1016/S0120-0534(14)70001-9Sparks, M., Coetzee, B., y Gabbett, T. J. (2017). Internal and External Match Loads of University-Level Soccer Players: A Comparison Between Methods. Journal of Strength and Conditioning Research, 31(4), 1072-1077. https://doi.org/10.1519/JSC.0000000000001560Taylor, K., Chapman, D., Cronin, J., Newton, M. J., y Gill, N. (2012). Fatigue monitoring in high performance sport: A survey of current trends. Journal of Australian Strength & Conditioning, 20(1), 12–23.Twist, C., y Highton, J. (2013). Monitoring fatigue and recovery in rugby league players. International Journal of sports physiology and performance, 8(5), 467–474. https://doi.org/10.1123/ijspp.8.5.467Urdampilleta, A., López-Grueso, R., Martínez-Sanz, J. M., y Mielgo-Ayuso, J. (2014). Parámetros bioquímicos básicos, hematológicos y hormonales para el control de la salud y el estado nutricional en los deportistas. Revista Española de Nutrición Humana y Dietética, 18(3), 155–171. https://doi.org/10.14306/renhyd.18.3.24Uth, N., Sorensen, H., Overgaard, K., y Pedersen, P. K. (2004). Estimation of VO2max from the ratio between HRmax and HRrest? The Heart Rate Ratio Method. European Journal of Applied Physiology, 91(1), 111-115. https://doi.org/10.1007/s00421-003-0988-yVernillo, G., Giandolini, M., Edwards, W. B., Morin, J.-B., Samozino, P., Horvais, N., y Millet, G. Y. (2017). Biomechanics and Physiology of Uphill and Downhill Running. Sports Medicine, 47(4), 615-629. https://doi.org/10.1007/s40279-016-0605-yVernillo, G., Savoldelli, A., Zignoli, A., Skafidas, S., Fornasiero, A., La Torre, A., … Schena, F. (2015). Energy cost and kinematics of level, uphill and downhill running: Fatigue-induced changes after a mountain ultramarathon. Journal of Sports Sciences, 33(19), 1998-2005. https://doi.org/10.1080/02640414.2015.1022870Número de citas totales / Total references: 53 (100%)Número de citas propias de la revista / Journal's own references: 1 (1,88%)Rev.int.med.cienc.act.fís.deporte - vol. 20 - número 80 - ISSN: 1577-0354Rev.int.med.cienc.act.fís.deporte - vol. 20 - número 80 - ISSN: 1577-0354PAGE \* MERGEFORMAT641iVBORw0KGgoAAAANSUhEUgAAAfsAAABCCAIAAADfW+iMAAAAAXNSR0IArs4c6QAAGORJREFUeF7t
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