PERFORMANCE EVALUATION OF IPE AND IE-AFFECTED PATIENTS USING A MODIFIED PSO AND ANFIS Article Swipe
K. P. Swain
,
Kuan Tak Tan
,
Kamal Upreti
,
Pravin R. Kshirsagar
,
Sivaneasan Bala Krishnan
,
Ramesh Chandra Poonia
,
Sumant Kumar Mohapatra
,
Sridhara Nayak
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.26782/jmcms.2025.06.00005
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.26782/jmcms.2025.06.00005
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.
Related Topics
Concepts
Adaptive neuro fuzzy inference system
Particle swarm optimization
Epilepsy
Artificial intelligence
Pattern recognition (psychology)
Computer science
Discrete wavelet transform
Electroencephalography
Feature extraction
Wavelet transform
Machine learning
Wavelet
Fuzzy logic
Psychology
Fuzzy control system
Psychiatry
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.26782/jmcms.2025.06.00005
- OA Status
- diamond
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4411438745
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4411438745Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.26782/jmcms.2025.06.00005Digital Object Identifier
- Title
-
PERFORMANCE EVALUATION OF IPE AND IE-AFFECTED PATIENTS USING A MODIFIED PSO AND ANFISWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-06-14Full publication date if available
- Authors
-
K. P. Swain, Kuan Tak Tan, Kamal Upreti, Pravin R. Kshirsagar, Sivaneasan Bala Krishnan, Ramesh Chandra Poonia, Sumant Kumar Mohapatra, Sridhara NayakList of authors in order
- Landing page
-
https://doi.org/10.26782/jmcms.2025.06.00005Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
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https://doi.org/10.26782/jmcms.2025.06.00005Direct OA link when available
- Concepts
-
Adaptive neuro fuzzy inference system, Particle swarm optimization, Epilepsy, Artificial intelligence, Pattern recognition (psychology), Computer science, Discrete wavelet transform, Electroencephalography, Feature extraction, Wavelet transform, Machine learning, Wavelet, Fuzzy logic, Psychology, Fuzzy control system, PsychiatryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.process | 74 |
| abstract_inverted_index.(ANFIS). | 54 |
| abstract_inverted_index.Adaptive | 50 |
| abstract_inverted_index.Epilepsy | 26, 30 |
| abstract_inverted_index.Modified | 42 |
| abstract_inverted_index.Particle | 43 |
| abstract_inverted_index.Shearlet | 62 |
| abstract_inverted_index.accuracy | 101 |
| abstract_inverted_index.achieves | 98 |
| abstract_inverted_index.analysis | 22 |
| abstract_inverted_index.approach | 40 |
| abstract_inverted_index.children | 34 |
| abstract_inverted_index.compared | 88 |
| abstract_inverted_index.diagnose | 9 |
| abstract_inverted_index.employed | 72 |
| abstract_inverted_index.epilepsy | 113 |
| abstract_inverted_index.existing | 90 |
| abstract_inverted_index.factors. | 16 |
| abstract_inverted_index.indicate | 93 |
| abstract_inverted_index.methods. | 91 |
| abstract_inverted_index.proposed | 82 |
| abstract_inverted_index.signals. | 77 |
| abstract_inverted_index.superior | 99 |
| abstract_inverted_index.Epilepsy, | 0 |
| abstract_inverted_index.Inference | 52 |
| abstract_inverted_index.Stockwell | 69 |
| abstract_inverted_index.Transform | 60, 63, 66, 70 |
| abstract_inverted_index.combining | 41 |
| abstract_inverted_index.diagnosis | 114 |
| abstract_inverted_index.disorder, | 4 |
| abstract_inverted_index.evaluated | 86 |
| abstract_inverted_index.patients, | 107 |
| abstract_inverted_index.potential | 110 |
| abstract_inverted_index.treatment | 116 |
| abstract_inverted_index.Contourlet | 65 |
| abstract_inverted_index.Idiopathic | 24, 29 |
| abstract_inverted_index.MPSO-ANFIS | 83 |
| abstract_inverted_index.extraction | 57 |
| abstract_inverted_index.(SWT)—are | 71 |
| abstract_inverted_index.Neuro-Fuzzy | 51 |
| abstract_inverted_index.challenging | 7 |
| abstract_inverted_index.performance | 79 |
| abstract_inverted_index.strategies. | 117 |
| abstract_inverted_index.Optimization | 45 |
| abstract_inverted_index.highlighting | 108 |
| abstract_inverted_index.neurological | 3 |
| abstract_inverted_index.particularly | 6 |
| abstract_inverted_index.SWT-ANFIS-MPSO | 96 |
| abstract_inverted_index.classification | 100 |
| abstract_inverted_index.electroencephalogram | 75 |
| abstract_inverted_index.techniques—Discrete | 58 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 8 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.6800000071525574 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.2425635 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |