MSCNet-FS: development of intelligent epileptic seizure anticipation model by multi serial cascaded network with feature Specific using scalogram images of EEG signal.
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Abstract
The early stage of the Epileptic Seizure Anticipation (ESA) model plays a significant part in supplying accurate medical care. In this research work, a novel Multi Serial Cascaded Network with Feature Specific model is developed. The scalogram images are given as input to a developed model. Here, the Target Feature Selection is performed optimally using the Improved Fitness Value Index-Archimedes Optimization (IFVI-AO) Algorithm. Finally, the selections of accurate features are subjected to 'Bi-directional Long Short-Term Memory (Bi-LSTM)'. The implemented model is validated and provides timely results to detect epileptic seizure disorder.
期刊介绍：
The primary aims of Computer Methods in Biomechanics and Biomedical Engineering are to provide a means of communicating the advances being made in the areas of biomechanics and biomedical engineering and to stimulate interest in the continually emerging computer based technologies which are being applied in these multidisciplinary subjects. Computer Methods in Biomechanics and Biomedical Engineering will also provide a focus for the importance of integrating the disciplines of engineering with medical technology and clinical expertise. Such integration will have a major impact on health care in the future.
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