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Investigating HRV's contribution to identify exercise pattern and intensity in healthy subjects
Clara L Sanchez1, François B Favier1, Arthur Fabre1
1EuroMov Digital Health in Motion, Université de Montpellier, IMT Mines Ales, Montpellier, France.
Background:
The ability to discern exercise modalities, defined here as intensity and pattern, holds significant importance in various contexts, particularly in conditions where treatment management is heavily influenced by daily physical activity. The objectives of this study were thus to evaluate the predictive capabilities of heart rate variability (HRV) components for identifying exercise modalities, and to examine whether HRV during exercise exhibits distinctive characteristics depending on the intensity and continuous or intermittent nature of the activity.
Methods:
We conducted HRV analysis across different exercises varying in intensity and pattern [two constant-load sessions at 40% (C40) and 60% (C60) of maximal aerobic power, and one intermittent session (INT)], using cycle ergometers with 26 volunteer subjects. HRV was analyzed using time-domain, frequency-domain, and nonlinear measures from data recorded with a Polar H10 Heart Rate Sensor chest strap and processed with Kubios HRV software. Gas exchanges and lactate levels were also measured. HRV data from the final 4 minutes of each exercise session were analyzed using penalized multinomial logistic regression to predict specific exercise modalities performed. Additionally, repeated measures ANOVA were conducted followed by post-hoc tests when appropriate, to assess differences across conditions.
Results:
Multinomial logistic regression model demonstrated robust predictive performance, achieving sensitivities and specificities ranging from 88 to 98%. Time-domain (meanRR, SDNN) and nonlinear (DFA-ɑ1) emerged as the retained predictors. ANOVA tests revealed distinct impacts of exercise modality on HRV components: time-domain measures, LF and HF spectral powers, and the nonlinear index DFA-ɑ1 were significantly reduced in C60 compared with C40, while time-domain variability indices, LF and HF spectral powers, and DFA-ɑ1 remained higher during INT exercise than in both other conditions.
Conclusion:
HRV emerges as a promising tool for distinguishing between exercise modalities with various intensity and/or continuous or intermittent pattern.
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