Sayed Daud, Syarifah Noor Syakiylla and Sudirman, Rubita and Ramli, Norhafizah (2022) Electroencephalogram pattern under exposure of audio stimulation and verbal memory assessment. Journal Of Medical Device Technology, 1 (1). pp. 38-44. ISSN 2948-5436
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Official URL: http://dx.doi.org/10.11113/jmeditec.v1n1.15
Abstract
Discovering brain activities during mental and cognitive assessments is interesting research work. It aids people in understanding how the information is stimulated and processed in the brain. This recent work aims to investigate brain activities using electroencephalography (EEG) under audio and verbal memory assessment stimulation. Besides, the effect of audio on verbal memory performance was investigated based on behavioral data and its association with EEG patterns. The subject was required to memorize a list of words at three difficulties level under control conditions, listening to their favorite song, and exposure to ambient noise. The brain signal was acquired during the memorizing period using an EEG machine based 10-20 electrode placement system. The raw EEG signal was filtered using a Butterworth bandpass filter at 4 to 40 Hz. After that, the brain rhythms of alpha, beta, gamma, and theta were extracted from the EEG signal. The mean voltage and relative rhythm power were obtained to determine their pattern under provided stimulation. The findings indicated that the mean EEG voltage and relative rhythms power were the highest and the most influenced under audio stimulation for all assessment phases compared to the control condition. The relative rhythm power showed the increment and decrement trend relative to the control condition. Theta rhythms exhibit the highest relative power with the maximum value found in ambient noise stimulation. The behavioral data revealed that the subject memorized better the word lists in ambient noise conditions.
Item Type: | Article |
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Uncontrolled Keywords: | Electroencephalography pattern, Verbal memory, Brain rhythms, Relative power, Features, Ambient noise, Favorite song |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Divisions: | Electrical Engineering |
ID Code: | 104141 |
Deposited By: | Muhamad Idham Sulong |
Deposited On: | 17 Jan 2024 01:30 |
Last Modified: | 17 Jan 2024 01:30 |
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