Selection of Neural Oscillatory Features for Human Stress Classification with Single Channel EEG Headset.
A study on classification of psychological stress in humans using electroencephalography (EEG) is presented. The stress is classified using a correlation-based feature subset selection method that efficiently reduces the feature vector length. In this study, twenty-eight participants are involved by...
| Publicado en: | BioMed Research International pp. 1 - 9 |
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| Autores principales: | , , , , |
| Formato: | equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
12/23/2018
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=133710579&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 133710579 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 12/23/2018 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 133710579 133710579 133710579 10.1155/2018/1049257 133710579 ppf: 1 ppct: 8 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Selection of Neural Oscillatory Features for Human Stress Classification with Single Channel EEG Headset. aug: au: Umar Saeed, Sanay Muhammad Anwar, Syed Muhammad Majid, Muhammad Awais, Muhammad Alnowami, Majdi affil: Department of Computer Engineering, University of Engineering and Technology, Taxila 47050, Pakistan sug: subj: Brain Waves Evaluation Stress, Psychological Classification Electroencephalography Eye Physiology Stress, Psychological Diagnosis Human Questionnaires Validity ab: A study on classification of psychological stress in humans using electroencephalography (EEG) is presented. The stress is classified using a correlation-based feature subset selection method that efficiently reduces the feature vector length. In this study, twenty-eight participants are involved by filling in the perceived stress scale-10 (PSS-10) questionnaire and their EEG is also recorded in closed eye condition to measure the baseline stress. The recorded data is labelled on the basis of the stress level that is indicated by the participant's PSS score. The feature selection method has shown that, among the EEG oscillations, low beta, high beta, and low gamma are the most significant neural oscillations for classifying human stress. The proposed method not only reduces the time to build a classification model but also improves the classification accuracy up to 78.57% using a single channel wearable EEG device. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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