Indian Journal of Science and Technology
Year: 2023, Volume: 16, Issue: 6, Pages: 391-400
Original Article
J Vishwesh1*, P Raviraj2
1Research Scholar, Department of Computer Science & Engineering, GSSS Institute of Engineering and Technology for Women, Mysuru, Affiliated to VTU, Belagavi, Karnataka, India
2Professor, Department of Computer Science & Engineering, GSSS Institute of Engineering and Technology for Women, Mysuru, Affiliated to VTU, Belagavi, Karnataka, India
*Corresponding Author
Email: [email protected]
Received Date:28 October 2022, Accepted Date:19 January 2023, Published Date:11 February 2023
Objectives: To develop an improved version of Differential Evolution (DE) algorithm to overcome the complexity in extracting the features from the Electroencephalogram (EEG) based Brain-Computer Interfaces (BCI) systems; To develop a Stacked Auto Encoder (SAE) for classifying motor imagery signals into left, right, feet and tongue movements, respectively. Methods: Improved Differential Evolution Optimization Algorithm (IDEOA) is proposed for the selection of features which is extracted by the hybrid CSP-CNN feature extraction model. Extracted features will undergo the classification process by using SAE. Findings: The proposed IDEOA has an accuracy of 97.34% compared to the existing Sinc-based convolutional neural networks that obtained 75.39% and TSGL-EEG-Net of 81.34%. Novelty: The proposed IDEOA improves the mutation strategy results in improved convergence effect. Keywords: BrainComputer Interfaces; Convolutional Neural Networks; Electroencephalogram; Improved Differential Evolution Optimization Algorithm; Stacked Auto Encoder
© 2023 Vishwesh & Raviraj. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)
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