Predictability of breathing parameters during cardiopulmonary exercise testing using entropy measurements.

ABSTRACT: Erratic breathing at rest and during exercise has been described in patients with dysfunctional breathing (DB). Sample entropy (SampEn) and approximate entropy (ApEn) were developed to assess the predictability of parameters in time series data. However, SampEn and ApEn were developed for data without trends. Their potential role in interpreting datasets during cardiopulmonary exercise testing (CPET) remains uncertain. We used simulations based on real-life exercise data to evaluate the effects of trends, varying numbers of analyzed respiratory cycles, and different coefficients used to calculate the tolerance interval on ApEn and SampEn measurements. We tested the LOESS_0.75 method to correct the trend in the calculation of SampEn and ApEn. Trends led to a significant underestim

SUBMITTER: Genecand L 

PROVIDER: S-EPMC12477547 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature