Key result
A hybrid bio-inspired algorithm combining whale optimization with adaptive particle swarm optimization achieved 98.25% accuracy in detecting cardiac arrhythmias using the MIT-BIH dataset.
Why the study?
Human electrocardiogram data input for arrhythmia detection is error-prone and time-consuming, necessitating automated models for early detection.
Does a hybrid bio-inspired algorithm (WOA + APSO) improve the accuracy of cardiac arrhythmia detection from ECG signals compared to state-of-the-art methods?
Does a hybrid bio-inspired algorithm (WOA + APSO) improve the accuracy of cardiac arrhythmia detection from ECG signals compared to state-of-the-art methods?
A hybrid bio-inspired algorithm combining whale optimization and adaptive particle swarm optimization achieves 98.25% accuracy in detecting cardiac arrhythmias from ECG signals.
May aid automated arrhythmia screening; leaves open prospective validation before clinical adoption.
Studies indicate cardiac arrhythmia is one of the leading causes of death in the world. The risk of a stroke may be reduced when an irregular and fast heart rate is diagnosed. Since it is non-invasive, electrocardiograms are often used to detect arrhythmias. Human data input may be error-prone and time-consuming because of these limitations. For early detection of heart rhythm problems, it is best to use deep learning models. In this paper, a hybrid bio-inspired algorithm has been proposed by combining whale optimization (WOA) with adaptive particle swarm optimization (APSO). The WOA is a recently developed meta-heuristic algorithm. APSO is used to increase convergence speed. When compared to conventional optimization methods, the two techniques work better together. MIT-BIH dataset has been utilized for training, testing and validating this model. The recall, accuracy, and specificity are used to measure efficiency of the proposed method. The efficiency of the proposed method is compared with state-of-art methods and produced 98.25 % of accuracy.
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Digumarthi et al. (2023) studied Cardiac arrhythmia. Hybrid bio-inspired algorithm combining whale optimization (WOA) with adaptive particle swarm optimization (APSO) vs. State-of-art methods was evaluated on Accuracy. A hybrid bio-inspired algorithm combining whale optimization with adaptive particle swarm optimization achieved 98.25% accuracy in detecting cardiac arrhythmias using the MIT-BIH dataset.
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