脑电图
BETA(编程语言)
阿尔法(金融)
β节律
快速傅里叶变换
光谱密度
压力(语言学)
α波
心理学
语音识别
听力学
数学
计算机科学
神经科学
发展心理学
统计
医学
算法
结构效度
语言学
哲学
程序设计语言
心理测量学
作者
Tee Yi Wen,Siti Armiza Mohd Aris
出处
期刊:Indonesian Journal of Electrical Engineering and Computer Science
[Institute of Advanced Engineering and Science]
日期:2020-01-01
卷期号:17 (1): 175-175
被引量:50
标识
DOI:10.11591/ijeecs.v17.i1.pp175-182
摘要
<span>This paper presents an analysis of stress feature using the power ratio of frequency bands including Alpha to Beta and Theta to Beta. In this study, electroencephalography (EEG) acquisition tool was utilized to collect brain signals from 40 subjects and objectively reflected stress features induced by virtual reality (VR) technology. The EEG signals were analyzed using Welch’s fast Fourier transform (FFT) to extract power spectral density (PSD) features which represented the power of a signal distributed over a range of frequencies. Slow wave versus fast wave (SW/FW) of EEG has been studied to discriminate stress from resting baseline. The results showed the Alpha/Beta ratio and Theta/Beta ratio are negatively correlated with stress and indicated that the power ratios can discriminate the data characteristics of brainwaves for stress assessment.</span>
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