RT Journal Article
T1 Exploring the hidden complexity: entropy analysis in pulse oximetry of female athletes
A1 Cabanas, Ana M
A1 Fuentes-Guajardo, Macarena
A1 Sáez, Nicolás
A1 Catalán, Davidson
A1 Collao-Caiconte, Patricio O.
A1 Martín Escudero, María Del Pilar
AB 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 (𝑉𝑂2,𝑚𝑎𝑥). 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 (𝑆𝑝𝑂2) data shows greater variability. For instance, the medium fitness group displayed an ApEn(HR) = 0.57±0.13 with a coefficient of variation (CV) of 22.17 and ApEn(𝑆𝑝𝑂2) = 0.96±0.49 with a CV of 46.08%, compared to the excellent fitness group with ApEn(HR) = 0.60±0.09 with a CV of 15.19% and ApEn(𝑆𝑝𝑂2) =0.85±0.42 with a CV of 49.46%, suggesting broader physiological responses among more fit individuals. The larger standard deviations and CVs for 𝑆𝑝𝑂2 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.
PB MDPI
SN 2079-6374
YR 2024
FD 2024
LK https://hdl.handle.net/20.500.14352/105957
UL https://hdl.handle.net/20.500.14352/105957
LA eng
NO Biosensors 2024, 14(1), 52; https://doi.org/10.3390/bios14010052
NO ANID
NO MINEDUC
DS Docta Complutense
RD 21 abr 2025