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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 邵燿華 | |
| dc.contributor.author | Wen-Yen Huang | en |
| dc.contributor.author | 黃文彥 | zh_TW |
| dc.date.accessioned | 2021-06-08T06:58:01Z | - |
| dc.date.copyright | 2009-07-16 | |
| dc.date.issued | 2009 | |
| dc.date.submitted | 2009-07-13 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/25984 | - |
| dc.description.abstract | Abstract
Aims Morphological classification of the single heartbeat is the most important part of the computer aided Arrhythmia Analysis. The operations of these systems applied can be divided into four steps:1. The removal of noise and artifacts ; 2. Fiducial points detection; 3. Morphological classification;4. The rhythm analysis and medical interpretation . In this paper, our aim was to classify the heartbeat into various groups. Method and results we use the method based on the Empirical Mode Decomposition algorithm and Dynamic Time Warping algorithm for extraction of features that can be used to classify various abnormal heartbeats. Further, we reduce the dimensionality of data in the form of n features of a vector with p variables used to principal component analysis .The performance of our algorithms has been evaluated by MIT-BIH Arrhythmia Database. According to the experimental result, the accuracy of all beats is approximately equal to or greater than 85% with the overall accuracy being 90%. This indicates the effectiveness of this method for classification. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-08T06:58:01Z (GMT). No. of bitstreams: 1 ntu-98-R95543039-1.pdf: 3702392 bytes, checksum: 98ce0b9b3b59f586c2fee07970e606a6 (MD5) Previous issue date: 2009 | en |
| dc.description.tableofcontents | 目錄
中文摘要 .......................................I Abstract .......................................II 圖目錄..........................................III 第一章 序論......................................1 1-1 前言與研究動機...............................1 1-2 心電圖原理...................................2 1-3 MIT-BIH 心律不整資料庫.......................9 1-4 文獻回顧.....................................15 1-5 研究架構.....................................18 第二章 研究原理..................................19 2-1 經驗模態分解.................................19 2-2 動態時間扭曲演算法...........................24 2-3 主成分分析法.................................28 2-4 密度群聚.....................................31 第三章 實驗流程與結果............................38 3-1 特徵萃取.....................................39 3-2 主成分分析過程...............................41 3-3 以密度進行分群並驗證.........................43 3-4 分類結果的統計與分析.........................46 第四章 結果討論..................................51 參考文獻.........................................53 | |
| dc.language.iso | zh-TW | |
| dc.title | 心電圖型態分類:應用本質模態特徵 | zh_TW |
| dc.title | ECG Morphalogy Classification:Using Features of
Intrinsic Mode Function | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 97-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 王崇禮,周迺寬,包舜華 | |
| dc.subject.keyword | ECG,本質模態函數(IMF),主成分分析(PCA),密度集群分析(DBSCAN), | zh_TW |
| dc.subject.keyword | ECG,IMF,PCA,DBSCAN, | en |
| dc.relation.page | 56 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2009-07-13 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 應用力學研究所 | zh_TW |
| 顯示於系所單位： | 應用力學研究所 | |
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