GENETIC ALGORITHM-ANN AND PCA-ANN FOR ECG ARRHYTHMIA DETECTION
A Bundle Branch Block (BBB) is a delay or obstruction along electrical impulse pathways in the heart. The automated detection and classification of a BBB are important for prompt, accurate diagnosis and treatment of heart conditions, especially inaccurate identification, of left BBB. This design is based on a hybrid approach for the detection of BBB that uses a Genetic Algorithm (GA) in combination with Artificial Neural Networks (ANN) and Principal Component Analysis (PCA) in combination with Artificial Neural Network to improve classification accuracy. Nineteen temporal features and three morphological features were extracted and normalized for each heartbeat from standard ECG recordings obtained from the MIT-BIH Arrhythmia database. The GA-ANN Hybrid and PCA-ANN results are compared with the parameters i.e sensitivity, specificity, and accuracy in the presence of noise. Hybrid methods provide a better, more accurate identification for the presence of BBB from ECG recordings leading to more timely diagnosis and treatment outcomes.
Reference Paper: A Genetic Algorithm-Neural Network Wrapper Approach for Bundle Branch Block Detection
Author’s Name: Ragheed Allami, Andrew Stranieri, Venki Balasubramanian, and Herbert F Jelinek
Source: Computing in Cardiology
Year:2016
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