Prime-like structures in EEG signal matrices: A framework for analysing EEG signals in epilepsy
Epilepsy is a neurological condition affecting millions worldwide. It is characterised by recurrent seizures. Electroencephalography remains one of the important investigations into the diagnosis and management of epilepsy, imaging electrical activities of the brain to outline patterns that preced...
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Lviv Polytechnic National University
2025
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| Online Access: | http://umpir.ump.edu.my/id/eprint/44943/ http://umpir.ump.edu.my/id/eprint/44943/1/Prime-like%20structures%20in%20EEG%20signal%20matrices%20-%20A%20framework%20for%20analysing%20EEG%20signals%20in%20epilepsy.pdf |
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| author | Amirul Aizad, Ahmad Fuad Yuhani, Yusof A, Ruslan S., Zenian |
| author_facet | Amirul Aizad, Ahmad Fuad Yuhani, Yusof A, Ruslan S., Zenian |
| author_sort | Amirul Aizad, Ahmad Fuad |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Epilepsy is a neurological condition affecting millions worldwide. It is characterised by recurrent seizures. Electroencephalography remains one of the important investigations into the diagnosis and management of epilepsy, imaging electrical activities of the brain to outline patterns that precede seizures. Mathematical modeling of seizure patterns requires identifying specific antecedent features of seizures in EEG recordings. Better understanding of such patterns could contribute to better management and improvement in the quality of life for persons living with the condition. The research further proposes a new mathematical framework wherein simple signals from EEG can be imagined as an analog of primes, drawing their inspiration from number-theoretical and linear algebraic concepts. It is based on the definition of the GCD for EEG signal square matrices and a theorem that will prove the existence of infinitely many elementary EEG signals. The approach described below transforms the EEG data into square matrices and, by applying algebraic techniques, allows a systematic analysis of seizure activity. The results suggest that this framework provides a structured method for EEG signal processing, offering potential applications in seizure analysis and related neurological studies. |
| first_indexed | 2025-11-15T03:57:16Z |
| format | Article |
| id | ump-44943 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:57:16Z |
| publishDate | 2025 |
| publisher | Lviv Polytechnic National University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-449432025-07-09T00:42:29Z http://umpir.ump.edu.my/id/eprint/44943/ Prime-like structures in EEG signal matrices: A framework for analysing EEG signals in epilepsy Amirul Aizad, Ahmad Fuad Yuhani, Yusof A, Ruslan S., Zenian QA Mathematics Epilepsy is a neurological condition affecting millions worldwide. It is characterised by recurrent seizures. Electroencephalography remains one of the important investigations into the diagnosis and management of epilepsy, imaging electrical activities of the brain to outline patterns that precede seizures. Mathematical modeling of seizure patterns requires identifying specific antecedent features of seizures in EEG recordings. Better understanding of such patterns could contribute to better management and improvement in the quality of life for persons living with the condition. The research further proposes a new mathematical framework wherein simple signals from EEG can be imagined as an analog of primes, drawing their inspiration from number-theoretical and linear algebraic concepts. It is based on the definition of the GCD for EEG signal square matrices and a theorem that will prove the existence of infinitely many elementary EEG signals. The approach described below transforms the EEG data into square matrices and, by applying algebraic techniques, allows a systematic analysis of seizure activity. The results suggest that this framework provides a structured method for EEG signal processing, offering potential applications in seizure analysis and related neurological studies. Lviv Polytechnic National University 2025-06-07 Article PeerReviewed pdf en cc_by_nc_4 http://umpir.ump.edu.my/id/eprint/44943/1/Prime-like%20structures%20in%20EEG%20signal%20matrices%20-%20A%20framework%20for%20analysing%20EEG%20signals%20in%20epilepsy.pdf Amirul Aizad, Ahmad Fuad and Yuhani, Yusof and A, Ruslan and S., Zenian (2025) Prime-like structures in EEG signal matrices: A framework for analysing EEG signals in epilepsy. Mathematical Modeling and Computing, 12 (2). pp. 558-572. ISSN 2312-9794. (Published) https://doi.org/10.23939/mmc2025.02.558 https://doi.org/10.23939/mmc2025.02.558 |
| spellingShingle | QA Mathematics Amirul Aizad, Ahmad Fuad Yuhani, Yusof A, Ruslan S., Zenian Prime-like structures in EEG signal matrices: A framework for analysing EEG signals in epilepsy |
| title | Prime-like structures in EEG signal matrices: A framework for analysing EEG signals in epilepsy |
| title_full | Prime-like structures in EEG signal matrices: A framework for analysing EEG signals in epilepsy |
| title_fullStr | Prime-like structures in EEG signal matrices: A framework for analysing EEG signals in epilepsy |
| title_full_unstemmed | Prime-like structures in EEG signal matrices: A framework for analysing EEG signals in epilepsy |
| title_short | Prime-like structures in EEG signal matrices: A framework for analysing EEG signals in epilepsy |
| title_sort | prime-like structures in eeg signal matrices: a framework for analysing eeg signals in epilepsy |
| topic | QA Mathematics |
| url | http://umpir.ump.edu.my/id/eprint/44943/ http://umpir.ump.edu.my/id/eprint/44943/ http://umpir.ump.edu.my/id/eprint/44943/ http://umpir.ump.edu.my/id/eprint/44943/1/Prime-like%20structures%20in%20EEG%20signal%20matrices%20-%20A%20framework%20for%20analysing%20EEG%20signals%20in%20epilepsy.pdf |