A Study of Detecting The Arteriovenous Graft Stenosis for Hemodialysis Based on Signal Processing Technique

碩士 === 國立臺灣科技大學 === 電機工程系 === 97 === In this thesis, we analyzed the acoustic signal from the hemodialysis patient’s arteriovenous graft, and developed an algorithm for stenosis detection. Based on our analysis, we found that their blood flow generates a baseband signal which is between 1 to 1.67Hz...

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Main Authors: Liang-wei Chiao, 焦良偉
Other Authors: Chih-Ming Chen
Format: Others
Language:zh-TW
Published: 2009
Online Access:http://ndltd.ncl.edu.tw/handle/37478382609275808427
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spelling ndltd-TW-097NTUS54420652016-05-02T04:11:39Z http://ndltd.ncl.edu.tw/handle/37478382609275808427 A Study of Detecting The Arteriovenous Graft Stenosis for Hemodialysis Based on Signal Processing Technique 以信號處理技術偵測血液透析患者廔管通路狹窄之研究 Liang-wei Chiao 焦良偉 碩士 國立臺灣科技大學 電機工程系 97 In this thesis, we analyzed the acoustic signal from the hemodialysis patient’s arteriovenous graft, and developed an algorithm for stenosis detection. Based on our analysis, we found that their blood flow generates a baseband signal which is between 1 to 1.67Hz over a carrier whose frequency range is highly correlated to the stenosis level in the arteriovenous graft. The carrier signal is much weaker(less than -100dB) than the baseband signal, as a result it is very difficult to observe the carrier directly and come up with a reliable detection result. By analyzing the signal in the time-frequency domain, we design an align-and-average scheme to suppress possible noises, and based on our analysis and observation, an array of cascaded bandpass filters are applied for detection purpose. Using our new technique, the results have been proved to within 5% of miss fire rate. The false alarm rate is about 23%, unfortunately. This leaves room for future improvement, however. Chih-Ming Chen Yen-nien Wang 陳志明 王延年 2009 學位論文 ; thesis 81 zh-TW
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description 碩士 === 國立臺灣科技大學 === 電機工程系 === 97 === In this thesis, we analyzed the acoustic signal from the hemodialysis patient’s arteriovenous graft, and developed an algorithm for stenosis detection. Based on our analysis, we found that their blood flow generates a baseband signal which is between 1 to 1.67Hz over a carrier whose frequency range is highly correlated to the stenosis level in the arteriovenous graft. The carrier signal is much weaker(less than -100dB) than the baseband signal, as a result it is very difficult to observe the carrier directly and come up with a reliable detection result. By analyzing the signal in the time-frequency domain, we design an align-and-average scheme to suppress possible noises, and based on our analysis and observation, an array of cascaded bandpass filters are applied for detection purpose. Using our new technique, the results have been proved to within 5% of miss fire rate. The false alarm rate is about 23%, unfortunately. This leaves room for future improvement, however.
author2 Chih-Ming Chen
author_facet Chih-Ming Chen
Liang-wei Chiao
焦良偉
author Liang-wei Chiao
焦良偉
spellingShingle Liang-wei Chiao
焦良偉
A Study of Detecting The Arteriovenous Graft Stenosis for Hemodialysis Based on Signal Processing Technique
author_sort Liang-wei Chiao
title A Study of Detecting The Arteriovenous Graft Stenosis for Hemodialysis Based on Signal Processing Technique
title_short A Study of Detecting The Arteriovenous Graft Stenosis for Hemodialysis Based on Signal Processing Technique
title_full A Study of Detecting The Arteriovenous Graft Stenosis for Hemodialysis Based on Signal Processing Technique
title_fullStr A Study of Detecting The Arteriovenous Graft Stenosis for Hemodialysis Based on Signal Processing Technique
title_full_unstemmed A Study of Detecting The Arteriovenous Graft Stenosis for Hemodialysis Based on Signal Processing Technique
title_sort study of detecting the arteriovenous graft stenosis for hemodialysis based on signal processing technique
publishDate 2009
url http://ndltd.ncl.edu.tw/handle/37478382609275808427
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