Individual alpha peak frequency based features for subject dependent EEG workload classification

• Main Authors: Lim, Wei Lun, Sourina, Olga, Wang, Lipo, Liu, Yisi
• 其他作者: School of Electrical and Electronic Engineering
• 格式: Conference or Workshop Item
• 語言: English
• 出版: 2021
• 主題: Engineering::Electrical and electronic engineering; Electroencephalography (EEG); Workload Classification
• 在線閱讀: https://hdl.handle.net/10356/146013
• 機構: Nanyang Technological University

The individual alpha peak frequency (IAPF) is an important biological indicator in Electroencephalogram (EEG) studies, with many research publications linking it to various cognitive functions. In this paper, we propose novel Power Spectral Density (PSD) alpha features based on IAPF to classify 2 an...