Application of time-delay multiscale symbolic phase compensated transfer entropy in analyzing cyclic alternating pattern (CAP) in sleep-related pathological data

Abstract

This paper proposes a new method to quantify the strength and direction of the information flow, that is, Time-delay multiscale symbolic phase compensated transfer entropy (denoted as SPcTE(τ,s)). We integrate time delay factors and time scale factors into the study of transfer entropy and use compensated transfer entropy to estimate transfer entropy to effectively eliminate the influence of instantaneous effects. Variational modal decomposition and wavelet analysis are used to preprocess experimental data to reduce noise. Artificial data experiments show that our method can capture the direction and size of the information flow between two time-delayed time series, locate the time point of the information transmission, and highlight the interaction between the two series on different time scales. In the study of the SPcTE(τ,s) of the Cyclic Alternating Pattern (CAP) in the clinical cases of adult sleep-disordered breathing (SDB), sleep disorders such as REM behavior disorder (RBD), bruxism (BRUX), insomnia (ins) and other states, it is found that they have different performance on different time delay factors and time scales. This method provides a more comprehensive research framework and provides important information in the potentially dynamic process.