Classification of Intensive-less Intensive and Related-Unrelated Tasks
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Tarih
2024
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Prof.Dr. İskender AKKURT
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
This study investigates the classification of electrical brain activity during intensive-less intensive and related-unrelated tasks. EEG signals were collected from 20 physically and mentally healthy university students (15 males, 5 females) residing in Adana and Hatay, Turkey, through 14 channels. Continuous Wavelet Transform analysis was applied for feature extraction. Subsequently, subject-dependent and subject-independent classifications were performed using the k-nearest Neighbour algorithm. In subjectdependent classification, the accuracy range for intensive-less intensive tasks varied between 77.6% and 89.8%, while the range for related-unrelated tasks was between 73.2% and 88%. Subject-independent classification yielded an accuracy of 79.2% for intensive-less intensive tasks and 77.5% for related unrelated tasks. © IJCESEN
Açıklama
Anahtar Kelimeler
Classification, ContinuousWavelet Transform, EEG, k-nearest Neighbor
Kaynak
International Journal of Computational and Experimental Science and Engineering
WoS Q Değeri
Scopus Q Değeri
Q4
Cilt
10
Sayı
2
