Automatic and Efficient Framework for Identifying Multiple Neurological Disorders From EEG Signals

The burden of neurological disorders is huge on global health and recognized as major causes of death and disability worldwide. There are more than 600 neurological diseases, but there is no unique automatic standard detection system yet to identify multiple neurological disorders using a single fra...

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Veröffentlicht in:	IEEE transactions on technology and society Jg. 4; H. 1; S. 76 - 86
Hauptverfasser:	Tawhid, Md. Nurul Ahad, Siuly, Siuly, Wang, Kate, Wang, Hua
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.03.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Artificial neural networks Autism Autism spectrum disorder Automatic programming Brain modeling cNN Computer aided diagnosis Convolutional neural networks Diagnosis eEG Electroencephalography Epilepsy Feature extraction Fourier transforms Medical imaging Mental disorders Neurological diseases neurological disorder Neurological disorders Parkinson's disease Public health Schizophrenia Signal classification Spectrogram time-frequency spectrogram image
ISSN:	2637-6415, 2637-6415
Online-Zugang:	Volltext
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