基于MSP430单片机的心电智能监测系统

Yan Zhang, Yi Tian, Zhaobin Wang, Yide Ma, Yurun Ma
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引用次数: 6

摘要

本文提出了一种基于MSP430单片机的易于使用、便携、低功耗、实时、自动报警的心电图智能诊断系统。在V1导联处采集实时心电信号,在前端电路进行瞬时放大滤波,然后将模拟心电信号转换为数字信号,用Cohen Daubechies - Feauveau 9/7小波进行滤波。心电波形显示在LCD上,实时计算的心率显示在分段LCD上,每4秒刷新一次。一旦检测到心电图异常,蜂鸣器报警和带有患者位置信息的报警信息将立即发送给医生或亲属。实现了一种基于积分投影函数的实时r波检测算法,该算法特别针对采集心电图时最常见的噪声源和干扰源以及基线漂移进行了自适应设计。该系统可以识别室性早搏(PVC),这对被监测的受试者非常重要。实验结果表明,该系统的r波检测准确率为98.8%,PVC检测识别准确率为92.1%。
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An ECG intelligent monitoring system with MSP430 microcontroller
This work presents a novel easy-to-use, portable, low-power, real-time, and autoalarm electrocardiogram (ECG) intelligent diagnosis system on MSP430 microcontroller. The real-time ECG signal is acquired at V1 lead and instantaneously amplified and filtered on front end circuit, and then, the signal is converted from analog ECG signal to digital value and filtered with Cohen Daubechies Feauveau 9/7 wavelet. Also, the ECG waveform is displayed on LCD and the real-time calculated heart rate is displayed on segment LCD, refreshed every 4 seconds. The buzzer alarms and the alarm message with the position information of the patient are sent to the doctors or relatives immediately, once an abnormal ECG is detected. A real-time R-wave detection algorithm based on integral projection function has been implemented, which is specially designed to be adaptive against the most common sources of noise and interference present and baseline wandering when acquiring the ECG. The system can identify premature ventricular contractions(PVC), which are very important for the subjects who are being monitored. Experimental results show the R-wave detection accuracy of the proposed system is 98.8% and the PVC detection and identification of the proposed system is 92.1%.
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