{"title":"基于dsp的心脏病识别低功耗低噪声心电采集系统","authors":"Bo-Yu Shiu, Shuohan Wang, Y. Chu, T. Tsai","doi":"10.1109/BioCAS.2013.6679630","DOIUrl":null,"url":null,"abstract":"In this paper, we implemented a low-power low-noise ECG acquisition system for heart disease identifications. The ECG signal is acquired with an analog front-end circuit, and the offset and baseline drift is eliminated at the same time. We also implemented a digital signal processing (DSP) unit to effectively remove EMG interferences. Interception of ST segment is proposed to achieve the identification of heart diseases. The ECG front-end chip has been designed and fabricated by using a TSMC 90nm CMOS technology, the total power consumption was measured at 40.3μW. DSP algorithms are carried out in the FPGA. Experimental results show that the sensitivity and specificity of ST segment classification after EMG elimination is 96.6% and 93.1%, respectively.","PeriodicalId":344317,"journal":{"name":"2013 IEEE Biomedical Circuits and Systems Conference (BioCAS)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"Low-power low-noise ECG acquisition system with dsp for heart disease identification\",\"authors\":\"Bo-Yu Shiu, Shuohan Wang, Y. Chu, T. Tsai\",\"doi\":\"10.1109/BioCAS.2013.6679630\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we implemented a low-power low-noise ECG acquisition system for heart disease identifications. The ECG signal is acquired with an analog front-end circuit, and the offset and baseline drift is eliminated at the same time. We also implemented a digital signal processing (DSP) unit to effectively remove EMG interferences. Interception of ST segment is proposed to achieve the identification of heart diseases. The ECG front-end chip has been designed and fabricated by using a TSMC 90nm CMOS technology, the total power consumption was measured at 40.3μW. DSP algorithms are carried out in the FPGA. Experimental results show that the sensitivity and specificity of ST segment classification after EMG elimination is 96.6% and 93.1%, respectively.\",\"PeriodicalId\":344317,\"journal\":{\"name\":\"2013 IEEE Biomedical Circuits and Systems Conference (BioCAS)\",\"volume\":\"74 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE Biomedical Circuits and Systems Conference (BioCAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BioCAS.2013.6679630\",\"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 IEEE Biomedical Circuits and Systems Conference (BioCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BioCAS.2013.6679630","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Low-power low-noise ECG acquisition system with dsp for heart disease identification
In this paper, we implemented a low-power low-noise ECG acquisition system for heart disease identifications. The ECG signal is acquired with an analog front-end circuit, and the offset and baseline drift is eliminated at the same time. We also implemented a digital signal processing (DSP) unit to effectively remove EMG interferences. Interception of ST segment is proposed to achieve the identification of heart diseases. The ECG front-end chip has been designed and fabricated by using a TSMC 90nm CMOS technology, the total power consumption was measured at 40.3μW. DSP algorithms are carried out in the FPGA. Experimental results show that the sensitivity and specificity of ST segment classification after EMG elimination is 96.6% and 93.1%, respectively.