Literature DB >> 33519504

A New Detection Method Defining the Aerobic Threshold for Endurance Exercise and Training Prescription Based on Fractal Correlation Properties of Heart Rate Variability.

Bruce Rogers1, David Giles2, Nick Draper3, Olaf Hoos4, Thomas Gronwald5.   

Abstract

The short-term scaling exponent alpha1 of detrended fluctuation analysis (DFA a1), a nonlinear index of heart rate variability (HRV) based on fractal correlation properties, has been shown to steadily change with increasing exercise intensity. To date, no study has specifically examined using the behavior of this index as a method for defining a low intensity exercise zone. The aim of this report is to compare both oxygen intake (VO2) and heart rate (HR) reached at the first ventilatory threshold (VT1), a well-established delimiter of low intensity exercise, to those derived from a predefined DFA a1 transitional value. Gas exchange and HRV data were obtained from 15 participants during an incremental treadmill run. Comparison of both VO2 and HR reached at VT1 defined by gas exchange (VT1 GAS) was made to those parameters derived from analysis of DFA a1 reaching a value of 0.75 (HRVT). Based on Bland Altman analysis, linear regression, intraclass correlation (ICC) and t testing, there was strong agreement between VT1 GAS and HRVT as measured by both HR and VO2. Mean VT1 GAS was reached at 39.8 ml/kg/min with a HR of 152 bpm compared to mean HRVT which was reached at 40.1 ml/kg/min with a HR of 154 bpm. Strong linear relationships were seen between test modalities, with Pearson's r values of 0.99 (p < 0.001) and.97 (p < 0.001) for VO2 and HR comparisons, respectively. Intraclass correlation between VT1 GAS and HRVT was 0.99 for VO2 and 0.96 for HR. In addition, comparison of VT1 GAS and HRVT showed no differences by t testing, also supporting the method validity. In conclusion, it appears that reaching a DFA a1 value of 0.75 on an incremental treadmill test is closely associated with crossing the first ventilatory threshold. As training intensity below the first ventilatory threshold is felt to have great importance for endurance sport, utilization of DFA a1 activity may provide guidance for a valid low training zone.
Copyright © 2021 Rogers, Giles, Draper, Hoos and Gronwald.

Entities:  

Keywords:  aerobic threshold; detrended fluctuation analysis; endurance exercise; endurance training; intensity distribution; intensity zones; polarized training; ventilatory threshold

Year:  2021        PMID: 33519504      PMCID: PMC7845545          DOI: 10.3389/fphys.2020.596567

Source DB:  PubMed          Journal:  Front Physiol        ISSN: 1664-042X            Impact factor:   4.566


  13 in total

1.  Validation of a non-linear index of heart rate variability to determine aerobic and anaerobic thresholds during incremental cycling exercise in women.

Authors:  Marcelle Schaffarczyk; Bruce Rogers; Rüdiger Reer; Thomas Gronwald
Journal:  Eur J Appl Physiol       Date:  2022-10-21       Impact factor: 3.346

2.  An Index of Non-Linear HRV as a Proxy of the Aerobic Threshold Based on Blood Lactate Concentration in Elite Triathletes.

Authors:  Bruce Rogers; Sander Berk; Thomas Gronwald
Journal:  Sports (Basel)       Date:  2022-02-18

Review 3.  Fractal Correlation Properties of Heart Rate Variability as a Biomarker for Intensity Distribution and Training Prescription in Endurance Exercise: An Update.

Authors:  Bruce Rogers; Thomas Gronwald
Journal:  Front Physiol       Date:  2022-05-09       Impact factor: 4.755

4.  Correlation Properties of Heart Rate Variability during a Marathon Race in Recreational Runners: Potential Biomarker of Complex Regulation during Endurance Exercise.

Authors:  Thomas Gronwald; Bruce Rogers; Laura Hottenrott; Olaf Hoos; Kuno Hottenrott
Journal:  J Sports Sci Med       Date:  2021-10-01       Impact factor: 2.988

5.  Influence of Artefact Correction and Recording Device Type on the Practical Application of a Non-Linear Heart Rate Variability Biomarker for Aerobic Threshold Determination.

Authors:  Bruce Rogers; David Giles; Nick Draper; Laurent Mourot; Thomas Gronwald
Journal:  Sensors (Basel)       Date:  2021-01-26       Impact factor: 3.576

6.  Profiling the Aerobic Window of Horses in Response to Training by Means of a Modified Lactate Minimum Speed Test: Flatten the Curve.

Authors:  Lorie De Maré; Berit Boshuizen; Carmen Vidal Moreno de Vega; Constance de Meeûs; Lukas Plancke; Yannick Gansemans; Filip Van Nieuwerburgh; Dieter Deforce; Jean Eduardo de Oliveira; Guilherme Hosotani; Maarten Oosterlinck; Catherine Delesalle
Journal:  Front Physiol       Date:  2022-03-22       Impact factor: 4.566

7.  Reliability of Symbolic Analysis of Heart Rate Variability and Its Changes During Sympathetic Stimulation in Elite Modern Pentathlon Athletes: A Pilot Study.

Authors:  Jakub S Gąsior; Maciej Rosoł; Marcel Młyńczak; Andrew A Flatt; Bartosz Hoffmann; Rafał Baranowski; Bożena Werner
Journal:  Front Physiol       Date:  2022-02-28       Impact factor: 4.566

Review 8.  Smart Electrically Assisted Bicycles as Health Monitoring Systems: A Review.

Authors:  Eli Gabriel Avina-Bravo; Johan Cassirame; Christophe Escriba; Pascal Acco; Jean-Yves Fourniols; Georges Soto-Romero
Journal:  Sensors (Basel)       Date:  2022-01-08       Impact factor: 3.576

9.  The Movesense Medical Sensor Chest Belt Device as Single Channel ECG for RR Interval Detection and HRV Analysis during Resting State and Incremental Exercise: A Cross-Sectional Validation Study.

Authors:  Bruce Rogers; Marcelle Schaffarczyk; Martina Clauß; Laurent Mourot; Thomas Gronwald
Journal:  Sensors (Basel)       Date:  2022-03-05       Impact factor: 3.576

10.  Fractal correlation properties of heart rate variability as a biomarker of endurance exercise fatigue in ultramarathon runners.

Authors:  Bruce Rogers; Laurent Mourot; Gregory Doucende; Thomas Gronwald
Journal:  Physiol Rep       Date:  2021-07
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