https://scholars.lib.ntu.edu.tw/handle/123456789/387348
標題: | Physiology-based diagnosis algorithm for arteriovenous fistula stenosis detection | 作者: | Yeih, Dong-Feng Wang, Yuh-Shyang Huang, Yi-Chun MING-FONG CHEN SHEY-SHI LU |
公開日期: | 2-十一月-2014 | 出版社: | Institute of Electrical and Electronics Engineers Inc. | 卷: | 2014 | 起(迄)頁: | 4619-4622 | 來源出版物: | Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference | 摘要: | In this paper, a diagnosis algorithm for arteriovenous fistula (AVF) stenosis is developed based on auscultatory features, signal processing, and machine learning. The AVF sound signals are recorded by electronic stethoscopes at pre-defined positions before and after percutaneous transluminal angioplasty (PTA) treatment. Several new signal features of stenosis are identified and quantified, and the physiological explanations for these features are provided. Utilizing support vector machine method, an average of 90% two-fold cross-validation hit-rate can be obtained, with angiography as the gold standard. This offers a non-invasive easy-to-use diagnostic method for medical staff or even patients themselves for early detection of AVF stenosis. © 2014 IEEE. |
URI: | http://www.scopus.com/inward/record.url?eid=2-s2.0-84944445814&partnerID=MN8TOARS http://scholars.lib.ntu.edu.tw/handle/123456789/387348 |
ISBN: | 978-142447929-0 | DOI: | 10.1109/EMBC.2014.6944653 |
顯示於: | 電機工程學系 |
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