Methodological framework for heart rate variability analysis during exercise: application to running and cycling stress testing
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Standard methodologies of heart rate variability analysis and physiological interpretation as a marker of autonomic nervous system condition have been largely published at rest, but not so much during exercise. A methodological framework for heart rate variability (HRV) analysis during exercise is proposed, which deals with the non-stationary nature of HRV during exercise, includes respiratory information, and identifies and corrects spectral components related to cardiolocomotor coupling (CC). This is applied to 23 male subjects who underwent different tests: maximal and submaximal, running and cycling; where the ECG, respiratory frequency and oxygen consumption were simultaneously recorded. High-frequency (HF) power results largely modified from estimations with the standard fixed band to those obtained with the proposed methodology. For medium and high levels of exercise and recovery, HF power results in a 20 to 40% increase. When cycling, HF power increases around 40% with respect to running, while CC power is around 20% stronger in running.
KeywordsCardiolocomotor coupling Stride cadence Pedalling cadence Non-stationary analysis
This work is supported by the CIBER in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN) through Instituto de Salud Carlos III, by MINECO and FEDER under project TIN2014-53567-R, by Grupo Consolidado BSICoS ref:T96 from DGA and European Social Fund (EU). The computation was performed by the ICTS NANBIOSIS, more specifically by the High Performance Computing Unit of the CIBER-BBN at the University of Zaragoza.
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