Product Development and Clinical Application of Arrhythmia Monitoring System
博士 === 國立中正大學 === 電機工程研究所 === 104 === An arrhythmia monitoring system is proposed and it is used for the clinical trial. There are three parts in this proposed system. In the first part, a high-resolution and low-power analog front-end circuit is proposed to implement the biosignal sensing circuits....
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ndltd-TW-104CCU004420312019-05-15T22:43:39Z http://ndltd.ncl.edu.tw/handle/snsvy6 Product Development and Clinical Application of Arrhythmia Monitoring System 心律不整檢測系統之產品開發與臨床應用 Liang, Ming-Chun 梁明鈞 博士 國立中正大學 電機工程研究所 104 An arrhythmia monitoring system is proposed and it is used for the clinical trial. There are three parts in this proposed system. In the first part, a high-resolution and low-power analog front-end circuit is proposed to implement the biosignal sensing circuits. It is realized with a chopper-based pre-amplifier and a high-pass sigma delta modulator. The features of the circuits are the low complexity, high resolution, and low power consumption. In the second part, a digital signal processor (DSP) with decimation filter and Universal Asynchronous Receiver/Transmitter (UART) package generator is proposed. The last part realizes a software interface based on Android for ECG (Electrocardiogram) signal recording, displaying, and classification. The wavelet-based classification method is proposed to classify the rhythm. The chip used in the system is fabricated in TSMC 0.18μm standard CMOS process and the operation voltage is 1.2V. The classification algorithm is verified with data from MIT/BIH Arrhythmia Database and the accuracy of beat detection is 99.4% and arrhythmia classification is 95.83%. The clinical trial is on-going and there are 8 patients enrolled from March 2016. The ECG signal of them can be acquired and classified. Lee, Shuenn-Yuh Chu, Yuan-Sun 李順裕 朱元三 2016 學位論文 ; thesis 151 en_US |
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博士 === 國立中正大學 === 電機工程研究所 === 104 === An arrhythmia monitoring system is proposed and it is used for the clinical trial. There are three parts in this proposed system. In the first part, a high-resolution and low-power analog front-end circuit is proposed to implement the biosignal sensing circuits. It is realized with a chopper-based pre-amplifier and a high-pass sigma delta modulator. The features of the circuits are the low complexity, high resolution, and low power consumption. In the second part, a digital signal processor (DSP) with decimation filter and Universal Asynchronous Receiver/Transmitter (UART) package generator is proposed. The last part realizes a software interface based on Android for ECG (Electrocardiogram) signal recording, displaying, and classification. The wavelet-based classification method is proposed to classify the rhythm. The chip used in the system is fabricated in TSMC 0.18μm standard CMOS process and the operation voltage is 1.2V. The classification algorithm is verified with data from MIT/BIH Arrhythmia Database and the accuracy of beat detection is 99.4% and arrhythmia classification is 95.83%. The clinical trial is on-going and there are 8 patients enrolled from March 2016. The ECG signal of them can be acquired and classified.
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author2 |
Lee, Shuenn-Yuh |
author_facet |
Lee, Shuenn-Yuh Liang, Ming-Chun 梁明鈞 |
author |
Liang, Ming-Chun 梁明鈞 |
spellingShingle |
Liang, Ming-Chun 梁明鈞 Product Development and Clinical Application of Arrhythmia Monitoring System |
author_sort |
Liang, Ming-Chun |
title |
Product Development and Clinical Application of Arrhythmia Monitoring System |
title_short |
Product Development and Clinical Application of Arrhythmia Monitoring System |
title_full |
Product Development and Clinical Application of Arrhythmia Monitoring System |
title_fullStr |
Product Development and Clinical Application of Arrhythmia Monitoring System |
title_full_unstemmed |
Product Development and Clinical Application of Arrhythmia Monitoring System |
title_sort |
product development and clinical application of arrhythmia monitoring system |
publishDate |
2016 |
url |
http://ndltd.ncl.edu.tw/handle/snsvy6 |
work_keys_str_mv |
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