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

Abstract

Measures of resting, exercise, and recovery heart rate 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. However, 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 heart rate, reflecting cardiac parasympathetic activity) and submaximal exercise (30- to 60-s average) heart rate 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 heart rate 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 in athletes participating in aerobic-oriented sports.

Autonomic cardiac regulation and morpho-physiological responses to eight week training preparation in junior soccer players

“…In this regards has been assumed that factor such as age, gender, ethnicity, baseline fitness status, nutrition, sleep, prior training, and genetics may explain the individual responses in VO 2 max to endurance training (Bouchard & Rankinen, 2001;Buchheit, 2014;Vollaard et al, 2009). We found a positive correlation between ΔVO 2 max and the mean morning level of vagally modulated HRV components in supine and upright position, respectively, measured throughout the training preparation.…”

“…For example Buchheit (2014) recommended the HRV measurements at least 3-4 times per week in individually exercised endurance athletes. According to same author, for team sports may be more suitable monitor the heart rate recovery rather then HRV level, because more frequent application HRV measurement could be related with higher technical and logistical complications in the daily training practice.…”

“…3, 2014, 155-163 doi: 10.5507/ag.2014 have argued that "trainability" is associated with the resting level of autonomic nervous system (ANS) activity, particularly vagal activity (Botek, McKune, Krejčí, Stejskal, & Gába, 2014;Boutcher et al, 2013;Hautala, Kiviniemi, & Tulppo, 2009;Hautala et al, 2003;Kiviniemi, Hautala, Kinnunen, & Tulppo, 2007;Vesterinen et al, 2013). The use of non-invasive tools, such as resting heart rate (HR) and heart rate variability (HRV), for the assessment of training status has become very popular among coaches, and athletes, respectively (Buchheit, 2014).…”

“…Both, high frequency (HF) oscillations in RR intervals (Akselrod et al, 1981;Pichot et al, 2000), and a root of mean square successive differences (rMSSD) (Buchheit, 2014) have been suggested to reflect the cardiac vagal outflow, while reciprocal changes between vagal and sympathetic activity are evaluated via analysis of low frequency power LF (Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology, 1996) and LF/HF (Ori, Monir, Weiss, Sayhouni, & Singer, 1992), respectively. A supine position is widely used for ANS activity assessment in athletes (Aubert, Seps, & Beckers, 2003;Buchheit, 2014;Hedelin, Bjerle, & Henriksson-Larsén, 2001;Pichot et al, 2000) despite the finding that a plateau in HF power in individuals with a low resting HR may occur (Goldberger, Challapalli, Tung, Parker, & Kadish, 2001;Kiviniemi et al, 2007;Plews, Laursen, Stanley, Kilding, & Buchheit, 2013). Therefore, to measure changes in the vagal activity in trained athletes, it has been recommended that they are measured in an upright position (Kiviniemi et al, 2007).…”

“…3, 2014, 155-163 doi: 10.5507/ag.2014 have argued that "trainability" is associated with the resting level of autonomic nervous system (ANS) activity, particularly vagal activity (Botek, McKune, Krejčí, Stejskal, & Gába, 2014;Boutcher et al, 2013;Hautala, Kiviniemi, & Tulppo, 2009;Hautala et al, 2003;Kiviniemi, Hautala, Kinnunen, & Tulppo, 2007;Vesterinen et al, 2013). The use of non-invasive tools, such as resting heart rate (HR) and heart rate variability (HRV), for the assessment of training status has become very popular among coaches, and athletes, respectively (Buchheit, 2014).Spectral analysis (SA) of RR intervals to determine HRV is commonly accepted as a non-invasive method for ANS activity assessment (Akselrod et al, 1981). Both, high frequency (HF) oscillations in RR intervals (Akselrod et al, 1981;Pichot et al, 2000), and a root of mean square successive differences (rMSSD) (Buchheit, 2014) have been suggested to reflect the cardiac vagal outflow, while reciprocal changes between vagal and sympathetic activity are evaluated via analysis of low frequency power LF (Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology, 1996) and LF/HF (Ori, Monir, Weiss, Sayhouni, & Singer, 1992), respectively.…”