PERFORMANCE EVALUATION OF IPE AND IE-AFFECTED PATIENTS USING A MODIFIED PSO AND ANFIS

Epilepsy, a complex neurological disorder, is particularly challenging to diagnose and manage when driven by genetic factors. This study focuses on the analysis of Idiopathic Partial Epilepsy (IPE) and Idiopathic Epilepsy (IE) in both children and women, using a novel approach combining Modified Par...

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Bibliographic Details
Published inJournal of mechanics of continua and mathematical sciences Vol. 20; no. 6; pp. 65 - 89
Main Authors Swain, Kaliprasanna, Tak, Tan Kuan, Upreti, Kamal, Kshirsagar, Pravin R., Krishnan, Sivaneasan Bala, Poonia, Ramesh Chandra, Mohapatra, Sumant Kumar, Ranjan Nayak, Sumya
Format Journal Article
LanguageEnglish
Published Institute of Mechanics of Continua and Mathematical Sciences 01.06.2025
Subjects
anfis
idiopathic epilepsy (ie)
idiopathic partial epilepsy (ipe)
modified particle swarm optimization (mpso)
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Summary:Epilepsy, a complex neurological disorder, is particularly challenging to diagnose and manage when driven by genetic factors. This study focuses on the analysis of Idiopathic Partial Epilepsy (IPE) and Idiopathic Epilepsy (IE) in both children and women, using a novel approach combining Modified Particle Swarm Optimization (MPSO) with a 9-rule Adaptive Neuro-Fuzzy Inference System (ANFIS). Four feature extraction techniques—Discrete Wavelet Transform (DWT), Shearlet Transform (SLT), Contourlet Transform (CLT), and Stockwell Transform (SWT)—are employed to process electroencephalogram (EEG) signals. The performance of the proposed MPSO-ANFIS model is evaluated and compared with existing methods. Results indicate that the SWT-ANFIS-MPSO method achieves superior classification accuracy for both IE and IPE patients, highlighting its potential to improve epilepsy diagnosis and treatment strategies.
ISSN:0973-8975
2454-7190
DOI:10.26782/jmcms.2025.06.00005