Standard spectral HRV analysis should not be applied during exercise due to confounding factors, while alternative methods like coarse graining spectral analysis show promise but require validation.
Autonomic control during exercise
Heart rate variability (HRV) measures (CGSA and non-linear analyses) vs Standard spectral HRV analysis
Heart rate variability (HRV) is a non-invasive indicator of cardiac autonomic modulation at rest. During rhythmic exercise, global HRV decreases as a function of exercise intensity. Measures reflecting sympathovagal interactions at rest do not behave as expected during exercise. This makes interpretation of HRV measures difficult, especially at higher exercise intensities. This problem is further confounded by the occurrence of non-neural oscillations in the high-frequency band due to increased respiratory effort. Alternative data treatments, such as coarse graining spectral analysis (CGSA), have demonstrated expected changes in autonomic function during exercise with some success. The separation of harmonic from fractal and/or chaotic components of HRV and study of the latter during exercise have provided further insight into cardioregulatory control. However, more research is needed. Some cross-sectional differences between HRV in athletes and controls during exercise are evident and data suggest longitudinal changes may be possible. Standard spectral HRV analysis should not be applied to exercise conditions. The use of CGSA and non-linear analyses show much promise in this area. Until further validation of these measures is carried out and clarification of the physiological meaning of such measures occurs, HRV data regarding altered autonomic control during exercise should be treated with caution.
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Sandercock et al. (Thu,) conducted a review in Autonomic control during exercise. Heart rate variability (HRV) measures (CGSA and non-linear analyses) vs. Standard spectral HRV analysis was evaluated. Standard spectral HRV analysis should not be applied during exercise due to confounding factors, while alternative methods like coarse graining spectral analysis show promise but require validation.
synapsesocial.com/papers/6a154f4a5347fbb1739f9155 — DOI: https://doi.org/10.1111/j.1600-0838.2006.00556.x
Gavin Sandercock
Preventive Cardiology
David A. Brodie
Buckinghamshire New University
Scandinavian Journal of Medicine and Science in Sports
London Metropolitan University
Buckinghamshire New University
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