Clint R Bellenger1,2, Rebecca L Thomson3, Eileen Y Robertson4, Kade Davison3, Maximillian J Nelson3, Laura Karavirta5, Jonathan D Buckley3. 1. Alliance for Research in Exercise, Nutrition and Activity (ARENA), Sansom Institute for Health Research, University of South Australia, 2471, Adelaide, SA, 5001, Australia. clint.bellenger@mymail.unisa.edu.au. 2. South Australian Sports Institute, Adelaide, Australia. clint.bellenger@mymail.unisa.edu.au. 3. Alliance for Research in Exercise, Nutrition and Activity (ARENA), Sansom Institute for Health Research, University of South Australia, 2471, Adelaide, SA, 5001, Australia. 4. South Australian Sports Institute, Adelaide, Australia. 5. Polar Electro Oy, Kempele, Finland.
Abstract
PURPOSE: Correlations between fatigue-induced changes in performance and maximal rate of HR increase (rHRI) may be affected by differing assessment workloads. This study evaluated the effect of assessing rHRI at different workloads on performance tracking, and compared this with HR variability (HRV) and HR recovery (HRR). METHODS: Performance [5-min cycling time trial (5TT)], rHRI (at multiple workloads), HRV and HRR were assessed in 12 male cyclists following 1 week of light training (LT), 2 weeks of heavy training (HT) and a 10-day taper (T). RESULTS: 5TT very likely decreased after HT (effect size ± 90% confidence interval = -0.75 ± 0.41), and almost certainly increased after T (1.15 ± 0.48). rHRI at 200 W likely increased at HT (0.70 ± 0.60), and then likely decreased at T (-0.50 ± 0.70). rHRI at 120 and 160 W was unchanged. Pre-exercise HR during rHRI assessments at 120 W and 160 W likely decreased after HT (≤-0.39 ± 0.14), and correlations between these changes and rHRI were large to very large (r = -0.67 ± 0.31 and r = -0.78 ± 0.23). When controlling for pre-exercise HR, rHRI at 120 W very likely slowed after HT (-0.72 ± 0.44), and was moderately correlated with 5TT (r = 0.35 ± 0.32). RMSSD likely increased at HT (0.75 ± 0.49) and likely decreased at T (-0.49 ± 0.49). HRR following 5TT likely increased at HT (0.84 ± 0.31) and then likely decreased at T (-0.81 ± 0.35). CONCLUSIONS: When controlling for pre-exercise HR, rHRI assessment at 120 W most sensitively tracked performance. Increased RMSSD following HT indicated heightened parasympathetic modulation in fatigued athletes. HRR was only sensitive to changes in training status when assessed after maximal exercise, which may limit its practical applicability.
PURPOSE: Correlations between fatigue-induced changes in performance and maximal rate of HR increase (rHRI) may be affected by differing assessment workloads. This study evaluated the effect of assessing rHRI at different workloads on performance tracking, and compared this with HR variability (HRV) and HR recovery (HRR). METHODS: Performance [5-min cycling time trial (5TT)], rHRI (at multiple workloads), HRV and HRR were assessed in 12 male cyclists following 1 week of light training (LT), 2 weeks of heavy training (HT) and a 10-day taper (T). RESULTS: 5TT very likely decreased after HT (effect size ± 90% confidence interval = -0.75 ± 0.41), and almost certainly increased after T (1.15 ± 0.48). rHRI at 200 W likely increased at HT (0.70 ± 0.60), and then likely decreased at T (-0.50 ± 0.70). rHRI at 120 and 160 W was unchanged. Pre-exercise HR during rHRI assessments at 120 W and 160 W likely decreased after HT (≤-0.39 ± 0.14), and correlations between these changes and rHRI were large to very large (r = -0.67 ± 0.31 and r = -0.78 ± 0.23). When controlling for pre-exercise HR, rHRI at 120 W very likely slowed after HT (-0.72 ± 0.44), and was moderately correlated with 5TT (r = 0.35 ± 0.32). RMSSD likely increased at HT (0.75 ± 0.49) and likely decreased at T (-0.49 ± 0.49). HRR following 5TT likely increased at HT (0.84 ± 0.31) and then likely decreased at T (-0.81 ± 0.35). CONCLUSIONS: When controlling for pre-exercise HR, rHRI assessment at 120 W most sensitively tracked performance. Increased RMSSD following HT indicated heightened parasympathetic modulation in fatigued athletes. HRR was only sensitive to changes in training status when assessed after maximal exercise, which may limit its practical applicability.
Authors: Clint R Bellenger; Rebecca L Thomson; Peter R C Howe; Laura Karavirta; Jonathan D Buckley Journal: J Sci Med Sport Date: 2015-07-10 Impact factor: 4.319
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Authors: Clint R Bellenger; Rebecca L Thomson; Eileen Y Robertson; Kade Davison; Maximillian J Nelson; Laura Karavirta; Jonathan D Buckley Journal: Sci Rep Date: 2020-09-03 Impact factor: 4.379
Authors: Clint R Bellenger; Rebecca L Thomson; Kade Davison; Eileen Y Robertson; Jonathan D Buckley Journal: Front Physiol Date: 2021-01-08 Impact factor: 4.566
Authors: Maximillian J Nelson; Jonathan D Buckley; Rebecca L Thomson; Clint R Bellenger; Kade Davison Journal: Front Physiol Date: 2021-12-14 Impact factor: 4.566
Authors: Lea C Rundfeldt; Martina A Maggioni; Robert H Coker; Hanns-Christian Gunga; Alain Riveros-Rivera; Adriane Schalt; Mathias Steinach Journal: Front Physiol Date: 2018-02-12 Impact factor: 4.566
Authors: Noah M A d'Unienville; Alison M Hill; Alison M Coates; Catherine Yandell; Maximillian J Nelson; Jonathan D Buckley Journal: BMJ Open Sport Exerc Med Date: 2019-08-07