Detection of Bundle Branch Block using Bat algorithm and Levenberg Marquardt Neural Network

Abstract

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.