Monitoring training status with HR measures: do all roads lead to Rome?

Monitoring an athlete's physiological status in response to various types and volumes of (aerobic-oriented) training can provide useful information for optimizing training programs. Measures of resting, exercise and recovery heart rate (HR) are receiving increasing interest for monitoring fatig...

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Main Author: Martin eBuchheit
Format: Article
Language:English
Published: Frontiers Media S.A. 2014-02-01
Series:Frontiers in Physiology
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fphys.2014.00073/full
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spelling doaj-a4dbabb1d64046ceae79ec428237bd322020-11-25T00:06:43ZengFrontiers Media S.A.Frontiers in Physiology1664-042X2014-02-01510.3389/fphys.2014.0007371297Monitoring training status with HR measures: do all roads lead to Rome?Martin eBuchheit0MyorobieMonitoring an athlete's physiological status in response to various types and volumes of (aerobic-oriented) training can provide useful information for optimizing training programs. Measures of resting, exercise and recovery heart rate (HR) are receiving increasing interest for monitoring fatigue, fitness and endurance performance responses, which has direct implications for adjusting training load 1) daily during specific training blocks and 2) throughout the competitive season. These measures are still not widely implemented to monitor athletes’ responses to training load, probably because of apparent contradictory findings in the literature. In this review I contend that most of the contradictory findings are related to methodological inconsistencies and/or misinterpretation of the data rather than to limitations of heart rate measures to accurately inform on training status. I also provide evidence that measures derived from 5-min (almost daily) recordings of resting (indices capturing beat-to-beat changes in HR, reflecting parasympathetic activity) and submaximal exercise (30- to 60-s average) HR are likely the most useful monitoring tools. For appropriate interpretation at the individual level, changes in a given measure should be interpreted by taking into account the error of measurement and the smallest important change of the measure, as well as the training context (training phase, load and intensity distribution). The decision to use a given measure should be based upon the level of information that is required by the athlete, the marker’s sensitivity to changes in training status and the practical constrains required for the measurements. However, measures of HR cannot inform on all aspects of wellness, fatigue and performance, so their use in combination with daily training logs, psychometric questionnaires and non-invasive, cost-effective performance tests such as a countermovement jump may offer a complete solution to monitor training statushttp://journal.frontiersin.org/Journal/10.3389/fphys.2014.00073/fullFatigueHeart rate variabilityheart rate recoveryWellnessteam sportstraining response
collection DOAJ
language English
format Article
sources DOAJ
author Martin eBuchheit
spellingShingle Martin eBuchheit
Monitoring training status with HR measures: do all roads lead to Rome?
Frontiers in Physiology
Fatigue
Heart rate variability
heart rate recovery
Wellness
team sports
training response
author_facet Martin eBuchheit
author_sort Martin eBuchheit
title Monitoring training status with HR measures: do all roads lead to Rome?
title_short Monitoring training status with HR measures: do all roads lead to Rome?
title_full Monitoring training status with HR measures: do all roads lead to Rome?
title_fullStr Monitoring training status with HR measures: do all roads lead to Rome?
title_full_unstemmed Monitoring training status with HR measures: do all roads lead to Rome?
title_sort monitoring training status with hr measures: do all roads lead to rome?
publisher Frontiers Media S.A.
series Frontiers in Physiology
issn 1664-042X
publishDate 2014-02-01
description Monitoring an athlete's physiological status in response to various types and volumes of (aerobic-oriented) training can provide useful information for optimizing training programs. Measures of resting, exercise and recovery heart rate (HR) are receiving increasing interest for monitoring fatigue, fitness and endurance performance responses, which has direct implications for adjusting training load 1) daily during specific training blocks and 2) throughout the competitive season. These measures are still not widely implemented to monitor athletes’ responses to training load, probably because of apparent contradictory findings in the literature. In this review I contend that most of the contradictory findings are related to methodological inconsistencies and/or misinterpretation of the data rather than to limitations of heart rate measures to accurately inform on training status. I also provide evidence that measures derived from 5-min (almost daily) recordings of resting (indices capturing beat-to-beat changes in HR, reflecting parasympathetic activity) and submaximal exercise (30- to 60-s average) HR are likely the most useful monitoring tools. For appropriate interpretation at the individual level, changes in a given measure should be interpreted by taking into account the error of measurement and the smallest important change of the measure, as well as the training context (training phase, load and intensity distribution). The decision to use a given measure should be based upon the level of information that is required by the athlete, the marker’s sensitivity to changes in training status and the practical constrains required for the measurements. However, measures of HR cannot inform on all aspects of wellness, fatigue and performance, so their use in combination with daily training logs, psychometric questionnaires and non-invasive, cost-effective performance tests such as a countermovement jump may offer a complete solution to monitor training status
topic Fatigue
Heart rate variability
heart rate recovery
Wellness
team sports
training response
url http://journal.frontiersin.org/Journal/10.3389/fphys.2014.00073/full
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