Selecting EEG channels and features using multi-objective optimization for accurate MCI detection: validation using leave-one-subject-out strategy

Effective management of dementia requires the timely detection of mild cognitive impairment (MCI). This paper introduces a multi-objective optimization approach for selecting EEG channels (and features) for the purpose of detecting MCI. Firstly, each EEG signal from each channel is decomposed into s...

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Vydané v:	Scientific reports Ročník 14; číslo 1; s. 12483 - 21
Hlavní autori:	Aljalal, Majid, Aldosari, Saeed A., Molinas, Marta, Alturki, Fahd A.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London Nature Publishing Group UK 30.05.2024 Nature Publishing Group Nature Portfolio
Predmet:	631/378/116/2396 639/166/985 692/53/2421 692/699/375 Accuracy Aged Algorithms Cognitive ability Cognitive Dysfunction - diagnosis Dementia disorders EEG EEG channel selection Electroencephalography - methods Entropy Feature selection Female Humanities and Social Sciences Humans Machine Learning Male MCI Middle Aged Multi-objective optimization multidisciplinary NSGA Science Science (multidisciplinary) Signal Processing, Computer-Assisted Wavelet Analysis Wavelet transforms EEG channel selection MCI Feature selection Multi-objective optimization NSGA Machine learning
ISSN:	2045-2322, 2045-2322
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