Human pulses reveal health conditions by a piezoelectret sensor via the approximate entropy analysis

Abstract

A piezoelectret pulse sensor combined with the approximate entropy (ApEn) analysis is utilized to detect human pulses to reveal health conditions. Inspired by the traditional Chinese medicine (TCM) with a foundation of more than 2500 years, human pulses are helpful in the diagnostics of illness as the body's vital energy circulates through blood vessels with branches connected to organs. A flexible cellular polypropylene (PP) piezoelectret film with a wooden cylinder substrate is used to emulate the pulse taking process in TCM to record the pulse characteristics. A group of 26 volunteers have been successfully diagnosed by the wearable sensing system and the approximate entropy analysis has been implemented to analyze the data. Results show a threshold approximate entropy value of 0.1 as the separation point between the volunteers of normal and abnormal health conditions.