Yan Zhang, Yi Tian, Zhaobin Wang, Yide Ma, Yurun Ma
{"title":"基于MSP430单片机的心电智能监测系统","authors":"Yan Zhang, Yi Tian, Zhaobin Wang, Yide Ma, Yurun Ma","doi":"10.1109/WOSSPA.2013.6602364","DOIUrl":null,"url":null,"abstract":"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%.","PeriodicalId":417940,"journal":{"name":"2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"An ECG intelligent monitoring system with MSP430 microcontroller\",\"authors\":\"Yan Zhang, Yi Tian, Zhaobin Wang, Yide Ma, Yurun Ma\",\"doi\":\"10.1109/WOSSPA.2013.6602364\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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%.\",\"PeriodicalId\":417940,\"journal\":{\"name\":\"2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-05-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WOSSPA.2013.6602364\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WOSSPA.2013.6602364","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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%.