Improving an automatic arrhythmias recogniser based in ECG signals

被引：0

作者：

Corsino, Jorge ^{[1
]}

Travieso, Carlos M. ^{[1
]}

Alonso, Jesus B. ^{[1
]}

Ferrer, Miguel A. ^{[1
]}

机构：

[1] Univ Las Palmas Gran Canaria, Technol Ctrr Innovat Commun CeTIC, Las Palmas Gran Canaria 35017, Spain

来源：

BIOSIGNALS 2008: PROCEEDINGS OF THE FIRST INTERNATIONAL CONFERENCE ON BIO-INSPIRED SYSTEMS AND SIGNAL PROCESSING, VOL II | 2008年

关键词：

automatic recognition of arrhythmias; electrocardiography; neural network; principal component analysis; wavelet transform;

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

In the present work, we have developed and improved a tool for the automatic arrhythmias detection, based on neural network with the "more-voted" algorithm. Arrhythmia Database MIT has been used in the work in order to detect eight different states, seven are pathologies and one is normal. The unions of different blocks and its optimization have found an improvement of success rates. In particular, we have used wavelet transform in order to characterize the patron wave of electrocardiogram (ECG), and principal components analysis in order to improve the discrimination of the coefficients. Finally, a neural network with more-voted method has been applied.

引用

页码：453 / 457

页数：5

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