A novel fuzzy c-means method for classifying heartbeat cases from ECG signals

NCU Institutional Repository > 資訊電機學院 > 電機工程學系 > 期刊論文 > Item 987654321/51902

jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://ir.lib.ncu.edu.tw/handle/987654321/51902

题名:	A novel fuzzy c-means method for classifying heartbeat cases from ECG signals
作者:	Yeh,YC;Wang,WJ;Chiou,CW
贡献者:	電機工程學系
关键词:	NEURAL-NETWORK;CLASSIFICATION;DIAGNOSIS
日期:	2010
上传时间:	2012-03-28 10:09:59 (UTC+8)
出版者:	國立中央大學
摘要:	This study proposes a simple and reliable method termed the fuzzy c-means method for classifying the heartbeat cases from electrocardiogram (ECG) signals. The proposed method has the advantages of good detection results, no complex mathematic computations, low memory space and low time complexity. The FCMM can accurately classify and distinguish the difference between normal heartbeats and abnormal heartbeats. Classifying the heartbeat cases from ECG signals consists of four main procedures: (i) Procedure-DOM for detecting QRS waveform using the Difference Operation Method; (ii) qualitative features stage (Procedure-ROM) for qualitative feature selection using the Range-Overlaps Method on ECG signals; (iii) Procedure-CCC is used to compute the cluster center for each class; and (iv) Procedure-HCD is used to determine the heartbeat case for the patient. The experiments show that the sensitivities were 98.28%, 90.35%, 86.97%, 92.19%, and 94.86% for NORM. LBBB, RBBB, VPC and APC, respectively. The total classification accuracy was approximately 93.57%. (C) 2010 Elsevier Ltd. All rights reserved.
關聯:	MEASUREMENT
显示于类别:	[電機工程學系] 期刊論文

文件中的档案:

档案	描述	大小	格式	浏览次数
index.html		0Kb	HTML	346	检视/开启

在NCUIR中所有的数据项都受到原著作权保护.

社群 sharing