教師資料查詢 | 類別: 會議論文 | 教師: 陳以錚 YI-CHENG CHEN (瀏覽個人網頁)

標題:Myocardial Infarction Classification by Morphological Feature Extraction from Big 12-Lead ECG Data
學年102
學期2
發表日期2014/05/13
作品名稱Myocardial Infarction Classification by Morphological Feature Extraction from Big 12-Lead ECG Data
作品名稱(其他語言)
著者Weng, Julia Tzu-Ya; Lin, Jyun-Jie; Chen, Yi-Cheng; Chang, Pei-Chann
作品所屬單位淡江大學資訊工程學系
出版者Springner
會議名稱The 1st International Workshop on Pattern Mining and Application of Big Data (BigPMA 2014) (in conjunction with PAKDD 2014)
會議地點Tainan, Taiwan
摘要Rapid and accurate diagnosis of patients with acute myocardial infarction is vital. The ST segment in Electrocardiography (ECG) represents the change of electric potential during the period from the end of ventricular depolarization to the beginning of repolarization and plays an important role in the detection of myocardial infarction. However, ECG monitoring generates big volumes of data and the underlying complexity must be extracted by a combination of methods. This study combines the advantages of polynomial approximation and principal component analysis. The proposed approach is stable for the 12-lead ECG data collected from the PTB database and achieves an accuracy of 98.07%.
關鍵字12-lead ECG;Myocardial infarction;Principal component;Polynomial approximation analysis;Support vector machine
語言英文(美國)
收錄於EI
會議性質國際
校內研討會地點
研討會時間20140513~20140516
通訊作者Julia Tzu-Ya Weng
國別中華民國
公開徵稿Y
出版型式電子版
出處Lecture Notes in Artificial Intelligence 8643, pp.689-699
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