title: The use of heart rate variability measures to assess autonomic control during exercise.
abstract: 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.
authors.affiliation: School of Health and Human Sciences, London Metropolitan University, London, UK. g.sandercock@londonmet.ac.uk
authors.forename: G R H
authors.initials: GR
authors.lastname: Sandercock
authors.forename: D A
authors.initials: DA
authors.lastname: Brodie
mesh_terms: D017776:Autonomic Pathways / Q000502:physiology*; D003430:Cross-Sectional Studies; D015444:Exercise / Q000502:physiology*; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D008137:Longitudinal Studies; D010806:Physical Education and Training; D013057:Spectrum Analysis / Q000379:methods