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

机译:一种新型的基于仿生学的压电心跳传感器,用于脉搏健康警告

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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.
机译:这项工作演示了一种新颖的基于仿生学的心跳传感器,并结合了用于健康预警的近似熵(ApEn)算法。拟议中的传感器的设计灵感来自中药的脉搏治疗。将柔性压电膜粘贴到木制圆柱体上,以模拟手指的结构以获取脉冲。利用ANSYS对不同受力面积和弯曲程度的压电薄膜进行了仿真。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来实现中医脉搏,而且可以提高压电薄膜的灵敏度。该传感器用于在不同的运动状态和不同的健康状况下测量人体的脉冲信号。然后使用ApEn分析样品数据。结果表明,ApEn值为0.1可以作为判断和预测人类健康状况的阈值。实验证明,该方法可以避免传统脉搏采集中相同力的要求。它不仅可以获得低失真的脉冲信号,而且可以准确地获得心率。使用此方法可以快速实现对人类健康的快速检测和预警。

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