Mental State Detection Using Riemannian Geometry on Electroencephalogram Brain Signals

Mental State Detection Using Riemannian Geometry on Electroencephalogram Brain Signals

The goal of this study was to implement a Riemannian geometry (RG)-based algorithm to detect high mental workload (MWL) and mental fatigue (MF) using task-induced electroencephalogram (EEG) signals. In order to elicit high MWL and MF, the participants performed a cognitively demanding task in the fo...

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Bibliographic Details
Main Authors: Kostoglou, K. (Author), Müller-Putz, G.R (Author), Raggam, P. (Author), Wriessnegger, S.C (Author)
Format: Article
Language:English
Published: Frontiers Media S.A. 2021
Subjects:
accuracy
adult
algorithm
alpha rhythm
Article
band power features
EEG
electroencephalography
female
human
human experiment
male
mental fatigue
mental health
mental load
mental workload
n-back test
normal human
reaction time
Riemannian geometry
Riemannian geometry based algorithm
theta rhythm
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