Automatic Arrhythmia Beat Detection: Algorithm, System, and Implementation

被引:2
|
作者
Jatmiko, Wisnu [1 ]
Setiawan, I. Md Agus [1 ]
Akbar, Muhammad Ali [1 ]
Suryana, Muhammad Eka [1 ]
Wardhana, Yulistiyan [1 ]
Rachmadi, Muhammad Febrian [2 ]
机构
[1] Univ Indonesia, Fac Comp Sci, Depok 16424, Indonesia
[2] Univ Edinburgh, Sch Informat, Edinburgh EH8 9LE, Midlothian, Scotland
来源
MAKARA JOURNAL OF TECHNOLOGY | 2016年 / 20卷 / 02期
关键词
arrhythmia; learning vector quantization; FN-GLVQ; FPGA;
D O I
10.7454/mst.v20i2.3060
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Cardiac disease is one of the major causes of death in the world. Early diagnose of the symptoms depends on abnormality on heart beat pattern, known as Arrhythmia. A novel fuzzy neuro generalized learning vector quantization for automatic Arrhythmia heart beat classification is proposed. The algorithm is an extension from the GLVQ algorithm that employs a fuzzy logic concept as the discriminant function in order to develop a robust algorithm and improve the classification performance. The algorithm is tested against MIT-BIH arrhythmia database to measure the performance. Based on the experiment result, FN-GLVQ is able to increase the accuracy of GLVQ by a soft margin. As we intend to build a device with automated Arrhythmia detection, FN-GLVQ is then implemented into Field Gate Programmable Array to prototype the system into a real device.
引用
收藏
页码:82 / 92
页数:11
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