Exploring the Hidden Complexity: Entropy Analysis in Pulse Oximetry of Female Athletes

Abstract

This study examines the relationship between physiological complexity, as measured by Approximate Entropy (ApEn) and Sample Entropy (SampEn), and fitness levels in female athletes. Our focus is on their association with maximal oxygen consumption ((Formula presented.)). Our findings reveal a complex relationship between entropy metrics and fitness levels, indicating that higher fitness typically, though not invariably, correlates with greater entropy in physiological time series data; however, this is not consistent for all individuals. For Heart Rate (HR), entropy measures suggest stable patterns across fitness categories, while pulse oximetry ((Formula presented.)) data shows greater variability. For instance, the medium fitness group displayed an ApEn(HR) = (Formula presented.) with a coefficient of variation (CV) of 22.17 and ApEn((Formula presented.)) = (Formula presented.) with a CV of 46.08%, compared to the excellent fitness group with ApEn(HR) = (Formula presented.) with a CV of 15.19% and ApEn((Formula presented.)) = (Formula presented.) with a CV of 49.46%, suggesting broader physiological responses among more fit individuals. The larger standard deviations and CVs for (Formula presented.) entropy may indicate the body’s proficient oxygen utilization at higher levels of physical demand. Our findings advocate for combining entropy metrics with wearable sensor technology for improved biomedical analysis and personalized healthcare.