QLBP: Dynamic patterns-based feature extraction functions for automatic detection of mental health and cognitive conditions using EEG signals

Gulay Tasci, Mehmet Veysel Gun, Tugce Keles, Burak Tasci, Prabal Datta Barua, Irem Tasci, Sengul Dogan, Mehmet Baygin, Elizabeth Emma Palmer, Turker Tuncer, Chui Ping Ooi and U. Rajendra Acharya

Chaos, Solitons & Fractals, 2023, vol. 172, issue C

Abstract: Severe psychiatric disorders, including depressive disorders, schizophrenia spectrum disorders, and intellectual disability, have devastating impacts on vital life domains such as mental, psychosocial, and cognitive functioning and are correlated with an increased risk of mortality. Accurate symptom monitoring and early diagnosis are essential to optimize treatment and enhance patient outcomes. Electroencephalography (EEG) is a potential diagnostic and monitoring tool for mental health and cognitive disorders, as EEG signals are ideal inputs for machine learning models. In this paper, we propose a novel machine learning model for mental disorder detection based on EEG signals.

Keywords: Quantum LBP; Mental disorder detection; Signal classification (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:172:y:2023:i:c:s0960077923003739

DOI: 10.1016/j.chaos.2023.113472

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