Classification of stress and participation using physiological signals of children during serious game-based therapy

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dc.authorid0000-0002-3009-5448
dc.authorid0000-0001-9804-368X
dc.contributor.authorCoşkun, Buket
dc.contributor.authorErol Barkana, Duygun
dc.contributor.authorUzun, İsmail
dc.contributor.authorBostancı, Hilal
dc.contributor.authorTarakçı, Devrim
dc.date.accessioned2024-02-09T07:57:52Z
dc.date.available2024-02-09T07:57:52Z
dc.date.issued2023
dc.departmentİstanbul Medipol Üniversitesi, Sağlık Bilimleri Fakültesi, Ergoterapi Bölümü
dc.description.abstractThe study involves classifying stress and participation of children with special needs and typically developing children using the physiological signals collected during serious game-based therapy. Blood Volume Pulse (BVP), Electrodermal Activity (EDA), and Skin Temperature (ST) physiological signals were collected from 25 children with special needs (dyslexia, intellectual disabilities) and typically developing. The 98 features from the physiological signals were extracted and significant physiological features were found using an independent t-test. The most significant features are selected, and Support Vector Machines (SVM), k-Nearest Neighbors (kNN), Random Forest (RF), Decision Tree (DT), Logistic Regression (LR), Naïve Bayes (NB), and Artificial Neural Networks (ANN) machine-learning methods are used to classify stress/no-stress and participation/no-participation. The highest classification accuracy and F1-Score were obtained as 0.90 and 0.76, respectively, with the RF method using the significant features for stress/no-stress classification. For participation/no-participation, the highest classification accuracy and F1-Score were obtained as 0.80 and 0.70, respectively, with RF method using all features.
dc.identifier.citationCoşkun, B., Erol Barkana, D., Uzun, İ., Bostancı, H. ve Tarakçı, D. (2023). Classification of stress and participation using physiological signals of children during serious game-based therapy. Medical Technologies Congress, TIPTEKNO 2023. Famagusta, 10-12 November 2023. https://dx.doi.org/10.1109/TIPTEKNO59875.2023.10359219
dc.identifier.doi10.1109/TIPTEKNO59875.2023.10359219
dc.identifier.isbn9798350328967
dc.identifier.scopus2-s2.0-85182745521
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://dx.doi.org/10.1109/TIPTEKNO59875.2023.10359219
dc.identifier.urihttps://hdl.handle.net/20.500.12511/12257
dc.indekslendigikaynakScopus
dc.institutionauthorBostancı, Hilal
dc.institutionauthorTarakçı, Devrim
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartofMedical Technologies Congress, TIPTEKNO 2023en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/embargoedAccess
dc.subjectChildren With Special Needs
dc.subjectStress
dc.subjectParticipation
dc.subjectSerious Game-Based Therapy
dc.subjectPhysiological Signals
dc.subjectFeature Extraction
dc.subjectFeature Selection
dc.subjectClassification
dc.titleClassification of stress and participation using physiological signals of children during serious game-based therapy
dc.typeConference Object

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