Optimal accuracy performance in music-based EEG signal using Matthew correlation coefficient advanced (MCCA)

Mahfuzah, Mustafa and Zarith Liyana, Zahari and Rafiuddin, Abdubrani (2021) Optimal accuracy performance in music-based EEG signal using Matthew correlation coefficient advanced (MCCA). Jurnal Teknologi, 83 (6). pp. 53-61. ISSN 0127-9696. (Published)

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The connection between music and human are very synonyms because music could reduce stress. The state of stress could be measured using EEG signal, an electroencephalogram (EEG) measurement which contains an arousal and valence index value. In previous studies, it is found that the Matthew Correlation Coefficient (MCC) performance accuracy is of 85±5%. The arousal indicates strong emotion, and valence indicates positive and negative degree of emotion. Arousal and valence values could be used to measure the accuracy performance. This research focuses on the enhance MCC parameter equation based on arousal and valence values to perform the maximum accuracy percentage in the frequency domain and time-frequency domain analysis. Twenty-one features were used to improve the significance of feature extraction results and the investigated arousal and valence value. The substantial feature extraction involved alpha, beta, delta and theta frequency bands in measuring the arousal and valence index formula. Based on the results, the arousal and valance index is accepted to be applied as parameters in the MCC equations. However, in certain cases, the improvement of the MCC parameter is required to achieve a high accuracy percentage and this research proposed Matthew correlation coefficient advanced (MCCA) in order to improve the performance result by using a six sigma method. In conclusion, the MCCA equation is established to enhance the existing MCC parameter to improve the accuracy percentage up to 99.9% for the arousal and valence index.

Item Type: Article
Additional Information: Indexed by Scopus
Uncontrolled Keywords: Accuracy; Arousal index; EEG; MCC and MCCA; Valence index
Subjects: T Technology > T Technology (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Institute of Postgraduate Studies
Faculty of Electrical and Electronic Engineering Technology
Depositing User: Mr Muhamad Firdaus Janih@Jaini
Date Deposited: 16 Jun 2022 01:50
Last Modified: 16 Jun 2022 01:50
URI: http://umpir.ump.edu.my/id/eprint/33106
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