Information domain analysis using compensated transfer entropy revealed significant age and gender-related changes in heart rate, blood pressure, and respiration coupling in healthy subjects.
An information domain approach using compensated transfer entropy can quantify significant age- and gender-based changes in cardiovascular, cardiorespiratory, and vasculorespiratory coupling in healthy subjects.
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This study presents a framework to quantify the coupling changes in cardiovascular, cardiorespiratory, and vasculorespiratory complexity using information domain approaches based on compensated transfer entropy (cTE). The dataset used for this research consists of the group of healthy young and old subjects. The proposed technique delivers significant coupling changes in healthy dataset based on age and gender in contribution of heart rate (HR), blood pressure (BP), and respiration (RESP). For validation of statistically significant values, the paired t-test is used. This study provides additional value to the prognostic and diagnostic approach in biomedical science.
Singh et al. (Thu,) reported a other. Information domain analysis using compensated transfer entropy revealed significant age and gender-related changes in heart rate, blood pressure, and respiration coupling in healthy subjects.