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

• Main Authors: Lim, Wei Lun, Sourina, Olga, Wang, Lipo, Liu, Yisi
• Other Authors: School of Electrical and Electronic Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2021
• Subjects: Engineering::Electrical and electronic engineering; Electroencephalography (EEG); Workload Classification
• Online Access: https://hdl.handle.net/10356/146013
• Institution: 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...