Detection of Bundle Branch Block using Adaptive Bacterial Foraging Optimization and Neural Network

The medical practitioners analyze the electrical activity of the human heart so as to predict various ailments by studying the data collected from the Electrocardiogram (ECG). A Bundle Branch Block (BBB) is a type of heart disease which occurs when there is an obstruction along the pathway of an ele...

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Bibliographic Details
Published in:Egyptian informatics journal 2017-03, Vol.18 (1), p.67-74
Main Authors: Kora, Padmavthi, Kalva, Sri Rama Krishna
Format: Article
Language:English
Subjects:
ABFO
Bundle Branch Block
ECG
LMNN
MIT–BIH Arrhythmia database
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Summary:The medical practitioners analyze the electrical activity of the human heart so as to predict various ailments by studying the data collected from the Electrocardiogram (ECG). A Bundle Branch Block (BBB) is a type of heart disease which occurs when there is an obstruction along the pathway of an electrical impulse. This abnormality makes the heart beat irregular as there is an obstruction in the branches of heart, this results in pulses to travel slower than the usual. Our current study involved is to diagnose this heart problem using Adaptive Bacterial Foraging Optimization (ABFO) Algorithm. The Data collected from MIT/BIH arrhythmia BBB database applied to an ABFO Algorithm for obtaining best(important) feature from each ECG beat. These features later fed to Levenberg Marquardt Neural Network (LMNN) based classifier. The results show the proposed classification using ABFO is better than some recent algorithms reported in the literature.
ISSN:1110-8665
2090-4754
DOI:10.1016/j.eij.2016.04.004