波形
均方误差
心率监护仪
脉搏(音乐)
信号(编程语言)
最小均方滤波器
均方根
压电传感器
脉搏率
计算机科学
压电
心率
材料科学
声学
人工智能
工程类
算法
数学
物理
统计
电气工程
自适应滤波器
电信
探测器
雷达
医学
血压
放射科
程序设计语言
作者
Shijian Luo,Ting Fang,Chong Dong,Jiaming Han
摘要
To achieve non-invasive, non-contact, and real-time heart rate monitoring, proposed a pulse signal acquisition system using PVDF (Polyvinylidene Fluoride) piezoelectric film. In order to address the issue of errors in heart rate extraction caused by differences in the morphology of pulse signals across individuals or in different states, the K-means clustering algorithm was innovatively used to locate the peak of pulse waveforms in different states and constructed a heart rate data set. Real-time heart rate monitoring by training a large number of pulse signal samples with the proposed CNN-LSTM network model. Experimental results demonstrated that the performance metrics of this model, including the MAE (Mean Absolute Error), RMSE (Root Mean Square Error), and R2 (Coefficient of Determination), are 0.2517, 0.3395, and 0.9863, respectively. the maximum error between the proposed system and the standard instrument within three minutes was only 1.55 beats/minute, indicating that the system exhibits high accuracy and reliability, and holds great potential for applications in heart rate detection.
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