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van Rassel CR, Ajayi OO, Sales KM, Clermont CA, Rummel M, MacInnis MJ. Quantifying exercise intensity with fractal correlation properties of heart rate variability: a study on incremental and constant-speed running. Eur J Appl Physiol 2024:10.1007/s00421-024-05592-2. [PMID: 39235602 DOI: 10.1007/s00421-024-05592-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Accepted: 08/18/2024] [Indexed: 09/06/2024]
Abstract
The short-term scaling exponent of detrended fluctuation analysis (DFAα1) applied to interbeat intervals may provide a method to identify ventilatory thresholds and indicate systemic perturbation during prolonged exercise. The purposes of this study were to (i) identify the gas exchange threshold (GET) and respiratory compensation point (RCP) using DFAα1 values of 0.75 and 0.5 from incremental exercise, (ii) compare DFAα1 thresholds with DFAα1 measures during constant-speed running near the maximal lactate steady state (MLSS), and (iii) assess the repeatability of DFAα1 between MLSS trials. Twelve runners performed an incremental running test and constant-speed running 5% below, at, and 5% above the MLSS, plus a repeat trial at MLSS. During 30-min running trials near MLSS, DFAα1 responses were variable (i.e., 0.27-1.24) and affected by intensity (p = 0.031) and duration (p = 0.003). No difference in DFAα1 was detected between MLSS trials (p = 0.597). In the early phase (~ 8 min), DFAα1 measures at MLSS (0.71 [0.13]) remained higher than the DFAα1 identified at RCP from the incremental test (0.57 [0.13]; p = 0.024). In addition, following ~ 18 min of constant speed running at MLSS, DFAα1 measures (0.64 [0.14]) remained higher than 0.5 (p = 0.011)-the value thought to demarcate the boundaries between heavy and severe exercise intensities. Accordingly, using fixed DFAα1 values associated with the RCP from incremental exercise to guide constant-speed exercise training may produce a greater than expected exercise intensity, however; the dependency of DFAα1 on intensity and duration suggest its potential utility to quantify systemic perturbations imposed by continuous exercise.
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Affiliation(s)
- C R van Rassel
- Faculty of Kinesiology, University of Calgary, Calgary, AB, T2N 1N4, Canada
| | - O O Ajayi
- Faculty of Kinesiology, University of Calgary, Calgary, AB, T2N 1N4, Canada
| | - K M Sales
- Faculty of Kinesiology, University of Calgary, Calgary, AB, T2N 1N4, Canada
| | - C A Clermont
- Faculty of Kinesiology, University of Calgary, Calgary, AB, T2N 1N4, Canada
- Canadian Sport Institute Alberta, Calgary, AB, T3B 6B7, Canada
| | - M Rummel
- AI Endurance Inc, Hamilton, ON, L8P 0A1, Canada
| | - M J MacInnis
- Faculty of Kinesiology, University of Calgary, Calgary, AB, T2N 1N4, Canada.
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Andriolo S, Rummel M, Gronwald T. Relationship of Cycling Power and Non-Linear Heart Rate Variability from Everyday Workout Data: Potential for Intensity Zone Estimation and Monitoring. SENSORS (BASEL, SWITZERLAND) 2024; 24:4468. [PMID: 39065866 PMCID: PMC11280911 DOI: 10.3390/s24144468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2024] [Revised: 07/05/2024] [Accepted: 07/06/2024] [Indexed: 07/28/2024]
Abstract
The short-term scaling exponent alpha1 of detrended fluctuation analysis (DFA-a1) of heart rate variability (HRV) has been shown to be a sensitive marker for assessing global organismic demands. The wide dynamic range within the exercise intensity spectrum and the relationship to established physiologic threshold boundaries potentially allow in-field use and also open opportunities to provide real-time feedback. The present study expands the idea of using everyday workout data from the AI Endurance app to obtain the relationship between cycling power and DFA-a1. Collected data were imported between September 2021 and August 2023 with an initial pool of 3123 workouts across 21 male users. The aim of this analysis was to further apply a new method of implementing workout group data considering representative values of DFA-a1 segmentation compared to single workout data and including all data points to enhance the validity of the internal-to-external load relationship. The present data demonstrate a universal relationship between cycling power and DFA-a1 from everyday workout data that potentially allows accessible and regular tracking of intensity zone demarcation information. The analysis highlights the superior efficacy of the representative-based approach of included data in most cases. Validation data of the performance level and the up-to-date relationship are still pending.
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Affiliation(s)
| | | | - Thomas Gronwald
- Institute of Interdisciplinary Exercise Science and Sports Medicine, MSH Medical School Hamburg, 20457 Hamburg, Germany
- G-Lab, Faculty of Applied Sport Sciences and Personality, BSP Business and Law School, 12247 Berlin, Germany
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Van Hooren B, Bongers BC, Rogers B, Gronwald T. The Between-Day Reliability of Correlation Properties of Heart Rate Variability During Running. Appl Psychophysiol Biofeedback 2023; 48:453-460. [PMID: 37516677 PMCID: PMC10582140 DOI: 10.1007/s10484-023-09599-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/12/2023] [Indexed: 07/31/2023]
Abstract
The short-term scaling exponent of detrended fluctuation analysis (DFA-a1) of heart rate variability may be a helpful tool to assess autonomic balance as a prelude to daily, individualized training. For this concept to be useful, between-session reliability should be acceptable. The aim of this study was to explore the reliability of DFA-a1 during a low-intensity exercise session in both a non-fatigued and a fatigued condition in healthy males and females. Ten participants completed two sessions with each containing an exhaustive treadmill ramp protocol. Before and after the fatiguing ramp, a standardized submaximal low-intensity exercise bout was performed during which DFA-a1, heart rate, and oxygen consumption (VO2) were measured. We compared between-session reliability of all metrics prior to the ramps (i.e., non-fatigued status) and after the first ramp (i.e., fatigued status). Intraclass correlation coefficients (ICC) with 95% confidence intervals (CI), the standard error of measurement, and the smallest worthwhile change (SWC) were determined. The ICC and SWC pre fatiguing ramp were 0.85 (95% CI 0.39-0.96) and 5.5% for DFA-a1, 0.85 (0.38-0.96) and 2.2% for heart rate, and 0.84 (0.31-0.96) and 3.1% for VO2. Post fatiguing ramp, the ICC and SWC were 0.55 (0.00-0.89) and 7.9% for DFA-a1, 0.91 (0.62-0.98) and 1.6% for heart rate, and 0.80 (0.17-0.95) and 3.0% for VO2. DFA-a1 shows generally acceptable to good between-session reliability with a SWC of 0.06 and 0.07 (5.5-7.9%) during non-fatigued and fatigued conditions. This suggests that this metric may be useful to inform on training readiness.
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Affiliation(s)
- Bas Van Hooren
- Department of Nutrition and Movement Sciences, School of Nutrition and Translational Research in Metabolism (NUTRIM), Faculty of Health, Medicine and Life Sciences, Maastricht University, Universiteitssingel 50, 6229 ER, Maastricht, The Netherlands.
| | - Bart C Bongers
- Department of Nutrition and Movement Sciences, School of Nutrition and Translational Research in Metabolism (NUTRIM), Faculty of Health, Medicine and Life Sciences, Maastricht University, Universiteitssingel 50, 6229 ER, Maastricht, The Netherlands
- Department of Surgery, School of Nutrition and Translational Research in Metabolism (NUTRIM), Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Bruce Rogers
- College of Medicine, University of Central Florida, Orlando, FL, USA
| | - Thomas Gronwald
- Institute of Interdisciplinary Exercise Science and Sports Medicine, MSH Medical School Hamburg, Hamburg, Germany
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Van Hooren B, Mennen B, Gronwald T, Bongers BC, Rogers B. Correlation properties of heart rate variability to assess the first ventilatory threshold and fatigue in runners. J Sports Sci 2023:1-10. [PMID: 37916488 DOI: 10.1080/02640414.2023.2277034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 10/22/2023] [Indexed: 11/03/2023]
Abstract
PURPOSE The short-term scaling exponent alpha1 of detrended fluctuation analysis (DFA-a1) of heart rate variability (HRV) has shown potential to delineate the first ventilatory threshold (VT1). The aims of this study were to investigate the accuracy of this method for VT1 determination in runners using a consumer grade chest belt and to explore the effects of acute fatigue. METHODS We compared oxygen uptake (V̇O2) and heart rate (HR) at gas exchange VT1 to V̇O2 and HR at a DFA-a1 value of 0.75. Gas exchange and HRV data were obtained from 14 individuals during a treadmill run involving two incremental ramps. Agreement was assessed using Bland-Altman analysis and linear regression. RESULTS Bland-Altman analysis between gas exchange and HRV V̇O2 and HR at VT1 during the first ramp showed a mean (95% limits of agreement) bias of -0.5 (-6.8 to 5.8) ml∙kg-1∙min-1, and -0.9 (-12.2 to 10.5) beats∙min-1, with R2 of 0.83 and 0.56, respectively. During the second ramp, the differences were -7.3 (-18.1 to 3.5) ml∙kg-1∙min-1 and -12.3 (-30.4 to 5.9) beats∙min-1, with R2 of 0.62 and 0.43, respectively. CONCLUSION A chest-belt derived DFA-a1 of 0.75 is closely related to gas exchange VT1, with the variability in accuracy at an individual level being similar to gas exchange methods. This suggests this to be a useful method for exercise intensity demarcation. The altered relationship during the second ramp indicates that DFA-a1 is only able to accurately demarcate exercise intensity thresholds in a non-fatigued state, but also opens opportunities for fatigue-based training prescription.
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Affiliation(s)
- Bas Van Hooren
- Department of Nutrition and Movement Sciences, School of Nutrition and Translational Research in Metabolism (NUTRIM), Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands
| | - Bram Mennen
- Department of Nutrition and Movement Sciences, School of Nutrition and Translational Research in Metabolism (NUTRIM), Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands
| | - Thomas Gronwald
- MSH Medical School Hamburg, Institute of Interdisciplinary Exercise Science and Sports Medicine, Hamburg, Germany
| | - Bart C Bongers
- Department of Nutrition and Movement Sciences, School of Nutrition and Translational Research in Metabolism (NUTRIM), Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands
- Department of Surgery, School of Nutrition and Translational Research in Metabolism (NUTRIM), Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands
| | - Bruce Rogers
- College of Medicine, University of Central Florida, Orlando, Florida, USA
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Torres RE, Heileson JL, Richardson KA, Chapman-Lopez TJ, Funderburk LK, Forsse JS. The Effectiveness of Utilizing HRV Indices as a Predictor of ACFT Performance Outcomes. Mil Med 2023; 188:e2096-e2101. [PMID: 36705446 DOI: 10.1093/milmed/usad009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 11/07/2022] [Accepted: 01/09/2023] [Indexed: 01/28/2023] Open
Abstract
BACKGROUND The Army Combat Fitness Test (ACFT) is a performance assessment used by the U.S. Army to assess a cadet's strength, endurance, and agility with a series of six events to ensure that cadets are combat ready. Heart rate variability (HRV) is an instrument that measures cardiac autonomic modulation and has been incorporated to predict the performance of athletes in daily training and competition since acute bouts of exercise alter HRV variables. PURPOSE To assess the applicability of using HRV to predict ACFT score performance outcomes in cadets. METHODS Fifty army cadets (n = 36 male; n = 14 female; age = 20.60 ± 3.61 years; height = 173.34 ± 10.39 cm; body mass = 76.33 ± 14.68 kg; body fat percentage = 17.58 ± 5.26%) completed the ACFT and reported for HRV assessment. HRV assessment had the participant lay supine for 5 minutes, and traditional time and frequency domain variables were assessed. A Pearson's correlation and multiple linear regressions were run. RESULTS HRV time and frequency domains were not significantly correlated in linear regression models except the stress index (SI) and the 2-mile run (2MR). The standing power throw and sprint drag carry were significantly correlated with traditional HRV variables. CONCLUSIONS HRV was not a predictor of ACFT performance for individual events or overall ACFT. The SI presented predictive properties only for 2MR, with no other significant correlations between HRV variables with standing power throw and sprint drag carry. The SI ability to predict 2MR performance outcome via HRV is a promising tool to assess army cadet performance and recovery.
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Affiliation(s)
- Ricardo E Torres
- Integrated Laboratory of Exercise, Nutrition, and Renal Vascular Research, Department of Health, Human Performance, and Recreation, Baylor University, Waco, TX 76798-7313, USA
| | - Jeffrey L Heileson
- Integrated Laboratory of Exercise, Nutrition, and Renal Vascular Research, Department of Health, Human Performance, and Recreation, Baylor University, Waco, TX 76798-7313, USA
- Walter Reed Army Medical Center, Bethesda, MD 20814, USA
| | - Kathleen A Richardson
- Integrated Laboratory of Exercise, Nutrition, and Renal Vascular Research, Department of Health, Human Performance, and Recreation, Baylor University, Waco, TX 76798-7313, USA
| | - Tomas J Chapman-Lopez
- Integrated Laboratory of Exercise, Nutrition, and Renal Vascular Research, Department of Health, Human Performance, and Recreation, Baylor University, Waco, TX 76798-7313, USA
| | - LesLee K Funderburk
- Integrated Laboratory of Exercise, Nutrition, and Renal Vascular Research, Department of Health, Human Performance, and Recreation, Baylor University, Waco, TX 76798-7313, USA
- Human Sciences and Design, Baylor University, Waco, TX 76798, USA
| | - Jeffrey S Forsse
- Integrated Laboratory of Exercise, Nutrition, and Renal Vascular Research, Department of Health, Human Performance, and Recreation, Baylor University, Waco, TX 76798-7313, USA
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Prigent G, Apte S, Paraschiv-Ionescu A, Besson C, Gremeaux V, Aminian K. Concurrent Evolution of Biomechanical and Physiological Parameters With Running-Induced Acute Fatigue. Front Physiol 2022; 13:814172. [PMID: 35222081 PMCID: PMC8874325 DOI: 10.3389/fphys.2022.814172] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Accepted: 01/10/2022] [Indexed: 12/28/2022] Open
Abstract
Understanding the influence of running-induced acute fatigue on the homeostasis of the body is essential to mitigate the adverse effects and optimize positive adaptations to training. Fatigue is a multifactorial phenomenon, which influences biomechanical, physiological, and psychological facets. This work aimed to assess the evolution of these three facets with acute fatigue during a half-marathon. 13 recreational runners were equipped with one inertial measurement unit (IMU) on each foot, one combined global navigation satellite system-IMU-electrocardiogram sensor on the chest, and an Android smartphone equipped with an audio recording application. Spatio-temporal parameters for the running gait, along with the heart rate, its variability and complexity were computed using validated algorithms. Perceived fatigability was assessed using the rating-of-fatigue (ROF) scale at every 10 min of the race. The data was split into eight equal segments, corresponding to at least one ROF value per segment, and only level running parts were retained for analysis. During the race, contact time, duty factor, and trunk anteroposterior acceleration increased, and the foot strike angle and vertical stiffness decreased significantly. Heart rate showed a progressive increase, while the metrics for heart rate variability and complexity decreased during the race. The biomechanical parameters showed a significant alteration even with a small change in perceived fatigue, whereas the heart rate dynamics altered at higher changes. When divided into two groups, the slower runners presented a higher change in heart rate dynamics throughout the race than the faster runners; they both showed similar trends for the gait parameters. When tested for linear and non-linear correlations, heart rate had the highest association with biomechanical parameters, while the trunk anteroposterior acceleration had the lowest association with heart rate dynamics. These results indicate the ability of faster runners to better judge their physiological limits and hint toward a higher sensitivity of perceived fatigue to neuromuscular changes in the running gait. This study highlights measurable influences of acute fatigue, which can be studied only through concurrent measurement of biomechanical, physiological, and psychological facets of running in real-world conditions.
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Affiliation(s)
- Gäelle Prigent
- Laboratory of Movement Analysis and Measurement, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Salil Apte
- Laboratory of Movement Analysis and Measurement, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Anisoara Paraschiv-Ionescu
- Laboratory of Movement Analysis and Measurement, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Cyril Besson
- Sport Medicine Unit, Division of Physical Medicine and Rehabilitation, Swiss Olympic Medical Center, Lausanne University Hospital, Lausanne, Switzerland
- Institute of Sport Sciences, University of Lausanne, Lausanne, Switzerland
| | - Vincent Gremeaux
- Sport Medicine Unit, Division of Physical Medicine and Rehabilitation, Swiss Olympic Medical Center, Lausanne University Hospital, Lausanne, Switzerland
- Institute of Sport Sciences, University of Lausanne, Lausanne, Switzerland
| | - Kamiar Aminian
- Laboratory of Movement Analysis and Measurement, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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