Wavelet Transforms in Sport: Application to Biological Time Series

Abstract

In sports, biological signals are often used to control and design the sports activity. One of the most common used signals is heart rate (HR). Heart rate variability (HRV) refers to natural fluctuations in the interval between normal heartbeats that occurs while individuals rest or exercise. HRV results from the dynamic interplay between the multiple physiologic mechanisms that regulate HR, and it mainly reflects an expression of the interplay between the sympathetic and parasympathetic nervous systems (Task Force, 1996). Two main oscillatory processes interact with the heart as feedback and forward mechanisms, via autonomic pathways: the modulation of the heart rate by breathing, known as respiratory sinus arrhythmia (RSA), and the short-term blood pressure control, known as baroreflex. These main rhythms usually appear in the high and low frequency ranges of HRV, respectively; however, the dynamic interactions in the cardiovascular system may change this typical spectrum. However, the intrinsic properties of the complex autonomic regulation of cardiovascular function are difficult to measure since, even at rest, emotions and mental loading may affect it.