EEG based Schizophrenia Detection using SPWVD-ViT Model

dc.contributor.authorŞeker, Mesut
dc.contributor.authorÖzerdem, Mehmet Siraç
dc.date.accessioned2025-03-08T18:27:27Z
dc.date.available2025-03-08T18:27:27Z
dc.date.issued2022
dc.departmentDicle Üniversitesi
dc.description.abstractSchizophrenia is a typical neurological disease that affects patients’ mental state, and daily behaviours. Combining image generation techniques with effective machine learning algorithms may accelerate treatment process, and possible early alert systems prevents diseases from reaching out crucial phase. The purpose of current study is to develop an automated EEG based schizophrenia detection with the Vision Transformer (ViT) model using Smoothed Pseudo Wigner Ville Distribution (SPWVD) time-frequency input images. EEG recordings from 35 schizophrenia (sch) and 35 healthy conditions (hc) are analyzed. We have used 5-fold cross validation for evaluation and testing of the method. Classification task is carried out as subject-independent and subject-dependent method. We reached out overall accuracy of 87% for subject-independent and 100% for subject-dependent approach for binary classification. While ViT has ben extensively used in Natural Language Processing (NLP) field, dividing input images within a sequence of embedded image patches via. transformer encoder is a practical way for medical image learning and developing diagnostic tools. SPWVD-ViT model is recommended as a disease detection tool not only for schizophrenia but other neurological symptoms.
dc.identifier.doi10.36222/ejt.1192140
dc.identifier.endpage144
dc.identifier.issn2536-5010
dc.identifier.issn2536-5134
dc.identifier.issue2
dc.identifier.startpage137
dc.identifier.urihttps://doi.org/10.36222/ejt.1192140
dc.identifier.urihttps://hdl.handle.net/11468/31004
dc.identifier.volume12
dc.language.isoen
dc.publisherHibetullah KILIÇ
dc.relation.ispartofEuropean Journal of Technique (EJT)
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_DergiPark_21250205
dc.subjectEEG
dc.subjectSchizophrenia
dc.subjectNeurological Disease
dc.subjectVision Transformer
dc.subjectDiagnosis
dc.subjectDetection
dc.subjectTime-frequency image
dc.titleEEG based Schizophrenia Detection using SPWVD-ViT Model
dc.typeArticle

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