Detection of Bundle Branch Block Using Bat Algorithm and Levenberg Marquardt Neural Network

被引：3
|
作者：
Kora, Padmavathi [1 ]
Krishna, K. Sri Rama [2 ]
机构：
[1] GRIET, Hyderabad, Andhra Pradesh, India
[2] VRSEC, Vijayawada, India
来源：
PROCEEDINGS OF FIRST INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGY FOR INTELLIGENT SYSTEMS: VOL 1 | 2016年 / 50卷
关键词：
Bundle block; Bat algorithm; LMNN classifier; MIT-BIH Arrhythmia database;
D O I：
10.1007/978-3-319-30933-0_55
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Abnormal Cardiac beat identification is a key process in the detection of heart ailments. This work proposes a technique for the detection of Bundle Branch Block (BBB) using Bat Algorithm (BA) technique in combination with Levenberg Marquardt Neural Network (LMNN) classifier. BBB is developed when there is a block along the electrical impulses travel to make heart to beat. The Bat algorithm can be effectively used to find changes in the ECG by identifying best features (optimized features). For the detection of normal and Bundle block beats, these Bat feature values are given as the input for the LMNN classifier.
引用
收藏
页码：553 / 561
页数：9
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