Heartbeat Classification using the Recurrent Neural Network based on the Developed Spider Monkey-Bird Swarm Optimization Algorithm- Proposed Method

Even though several methods are introduced to perform the heart beat classification by using the ECG signals, but classifying the heartbeat by analyzing the cardiac arrhythmia is still a challenging task. Hence, an effective RNN-based SM-BS optimization algorithm is introduced in this work, which is the combination of the SMO and the BSA algorithm. As the SMO and BSA are integrated together, the features from both the optimization will be utilized in the proposed work. As SMO uses the intelligent behavior and BSA mimics the foraging behavior, flight behavior, and vigilance behavior. Both these algorithms are effectively used to optimize the problem. Hence, this can be fused with the RNN to perform the beat classification in the proposed work.