ECG Detection And Correction Based On BP Signal Under Strong Noise Interference

碩士 === 國立雲林科技大學 === 資訊工程系 === 105 === In recent years, cardiovascular disease is the major causes of death. Cardiovascu-lar disease is mainly observed through electrocardiogram. ECG is susceptible to inter-ference from external factors, leading to added noise of ECG signal. In this study, ECG featur...

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Main Authors: KO WANG, CHIA-LIN, 柯王佳燐
Other Authors: WANG,WEN-FONG
Format: Others
Language:zh-TW
Published: 2017
Online Access:http://ndltd.ncl.edu.tw/handle/r46r5w
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spelling ndltd-TW-105YUNT03920062019-05-15T23:17:15Z http://ndltd.ncl.edu.tw/handle/r46r5w ECG Detection And Correction Based On BP Signal Under Strong Noise Interference 在強雜訊干擾條件下基於血壓訊號輔助心電圖R波標記與修正 KO WANG, CHIA-LIN 柯王佳燐 碩士 國立雲林科技大學 資訊工程系 105 In recent years, cardiovascular disease is the major causes of death. Cardiovascu-lar disease is mainly observed through electrocardiogram. ECG is susceptible to inter-ference from external factors, leading to added noise of ECG signal. In this study, ECG feature extraction combined with blood pressure. In this study, the original signal uses median filtering to remove low-frequency noise, and then use Wavelet modulus maxima detection characteristics. The pulse transit time(PTT) is used to train the classifier used to identify the characteristics of the ECG. In conclusion, the ECG signals add the noise for verifying the accuracy of our al-gorithm. The accuracy of our algorithm reached 95.76% under the strong noise signals. WANG,WEN-FONG 王文楓 2017 學位論文 ; thesis 32 zh-TW
collection NDLTD
language zh-TW
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sources NDLTD
description 碩士 === 國立雲林科技大學 === 資訊工程系 === 105 === In recent years, cardiovascular disease is the major causes of death. Cardiovascu-lar disease is mainly observed through electrocardiogram. ECG is susceptible to inter-ference from external factors, leading to added noise of ECG signal. In this study, ECG feature extraction combined with blood pressure. In this study, the original signal uses median filtering to remove low-frequency noise, and then use Wavelet modulus maxima detection characteristics. The pulse transit time(PTT) is used to train the classifier used to identify the characteristics of the ECG. In conclusion, the ECG signals add the noise for verifying the accuracy of our al-gorithm. The accuracy of our algorithm reached 95.76% under the strong noise signals.
author2 WANG,WEN-FONG
author_facet WANG,WEN-FONG
KO WANG, CHIA-LIN
柯王佳燐
author KO WANG, CHIA-LIN
柯王佳燐
spellingShingle KO WANG, CHIA-LIN
柯王佳燐
ECG Detection And Correction Based On BP Signal Under Strong Noise Interference
author_sort KO WANG, CHIA-LIN
title ECG Detection And Correction Based On BP Signal Under Strong Noise Interference
title_short ECG Detection And Correction Based On BP Signal Under Strong Noise Interference
title_full ECG Detection And Correction Based On BP Signal Under Strong Noise Interference
title_fullStr ECG Detection And Correction Based On BP Signal Under Strong Noise Interference
title_full_unstemmed ECG Detection And Correction Based On BP Signal Under Strong Noise Interference
title_sort ecg detection and correction based on bp signal under strong noise interference
publishDate 2017
url http://ndltd.ncl.edu.tw/handle/r46r5w
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