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An Experimental Framework for Assessing Emotions of Stroke Patients using Electroencephalogram (EEG)

Khairunizam, Wan, Yean, Choong Wen, Murugappan, Murugappan, Junoh, Ahmad Kadri, Razlan, Zuradzman M., Shahriman, AB, Mustafa, Wan Azani Wan, Bin Ibrahim, Zunaidi and Nurhafizah, Siti (2020) An Experimental Framework for Assessing Emotions of Stroke Patients using Electroencephalogram (EEG). Journal of Physics: Conference Series, 1529 (5). 052072. ISSN 1742-6596

Item Type: Article

Abstract

Abstract: This research aims to assess the emotional experiences of stroke patients using Electroencephalogram (EEG) signals. Since emotion and health are interrelated, thus it is important to analyse the emotional states of stroke patients for neurofeedback treatment. Moreover, the conventional methods for emotional assessment in stroke patients are based on observational approaches where the results can be fraud easily. The observational-based approaches are conducted by filling up the international standard questionnaires or face to face interview for symptom recognition from psychological reactions of patients and do not involve experimental study. This paper introduces an experimental framework for assessing emotions of the stroke patient. The experimental protocol is designed to induce six emotional states of the stroke patient in the form of video-audio clips. In the experiments, EEG data are collected from 3 groups of subjects, namely the stroke patients with left brain damage (LBD), the stroke patients with right brain damage (RBD), and the normal control (NC). The EEG signals exhibit nonlinear properties, hence the non-linear methods such as the Higher Order Spectra (HOS) could give more information on EEG in the signal’s analysis. Furthermore, the EEG classification works with a large amount of complex data, a simple mathematical concept is almost impossible to classify the EEG signal. From the investigation, the proposed experimental framework able to induce the emotions of stroke patient and could be acquired through EEG.

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Additional Information: ** From IOP Publishing via Jisc Publications Router ** History: ppub 05-2020; open-access 01-05-2020. ** Licence for this article: http://creativecommons.org/licenses/by/3.0/
Uncontrolled Keywords: Paper
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Identifiers

Item ID: 12140
Identification Number: https://doi.org/10.1088/1742-6596/1529/5/052072
ISSN: 1742-6596
URI: http://sure.sunderland.ac.uk/id/eprint/12140
Official URL: https://iopscience.iop.org/article/10.1088/1742-65...

Users with ORCIDS

ORCID for Zunaidi Bin Ibrahim: ORCID iD orcid.org/0000-0002-0246-1017

Catalogue record

Date Deposited: 23 Jun 2020 10:55
Last Modified: 30 Sep 2020 11:01

Contributors

Author: Zunaidi Bin Ibrahim ORCID iD
Author: Wan Khairunizam
Author: Choong Wen Yean
Author: Murugappan Murugappan
Author: Ahmad Kadri Junoh
Author: Zuradzman M. Razlan
Author: AB Shahriman
Author: Wan Azani Wan Mustafa
Author: Siti Nurhafizah

University Divisions

Faculty of Technology > School of Engineering

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