A New Type of Bionics Based Piezoelectric Heartbeat Sensor Used in Pulse-Taking for Health Warning

2018 IEEE SENSORS Pub Date : 2018-10-01 DOI:10.1109/ICSENS.2018.8589641

Meining Ji, Xiaofeng Meng, J. Nie, Yaqin Wang, Liwei Lin

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引用次数: 4

Abstract

This work demonstrates a novel bionics-based heartbeat sensor combined with approximate entropy (ApEn) algorithm for health warning. The design of the proposed sensor was inspired by pulse-taking therapy in traditional Chinese medicine (TCM). A flexible piezoelectric film was adhered to a wooden cylinder to simulate the structure of the finger to achieve pulse-taking. The simulation of piezoelectric film under different force area and bending degree was realized by ANSYS. The results showed that the sensor structure proposed in this paper can not only simulate the characteristics of the finger to achieve the TCM pulse-taking, but also improve the sensitivity of piezoelectric film. The sensor was used to measure the pulse signal of human under different states of motion and different health conditions. Then the sample data were analyzed using the ApEn. The results showed that the ApEn value is 0.1 can be used as a threshold for judging and predicting human health status. The experiment proved that this method can avoid the requirement of the same force in the traditional pulse-taking. It not only can obtain the low distortion pulse signal, but also can obtain the heart rate accurately. Using this method can quickly achieve rapid detection and early warning of human health.

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一种用于健康预警脉搏测量的新型仿生压电心跳传感器

这项工作展示了一种新的基于仿生学的结合近似熵(ApEn)算法的健康预警心跳传感器。所提出的传感器的设计灵感来自于传统中医(TCM)的取脉疗法。将柔性压电薄膜粘附在木柱上，模拟手指的结构，实现取脉。利用ANSYS软件实现了压电薄膜在不同受力面积和弯曲程度下的仿真。实验结果表明，本文提出的传感器结构不仅可以模拟手指的特征，实现中医取脉，而且可以提高压电薄膜的灵敏度。该传感器用于测量人体在不同运动状态和不同健康状况下的脉搏信号。然后用ApEn对样本数据进行分析。结果表明，ApEn值为0.1可作为判断和预测人体健康状况的阈值。实验证明，该方法可以避免传统的取脉过程中对相同力的要求。它不仅可以获得低失真的脉搏信号，而且可以准确地获得心率。利用该方法可以快速实现对人体健康状况的快速检测和预警。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2018 IEEE SENSORS

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