Spatial-Spectral Identification Of Μ And Β Eeg Rhythm Sourcrs During Robot-Assisted Walking

Abstract

We are interested in studying cortical involvement during the gait to provide fundamental knowledge for stroke rehabilitation. In this work we analyze electroencephalographic (EEG) rhythms during a robot-assisted gait-training experiment from able-bodied participants. A computational 3D distributed source model based on individual anatomy was used to calculate EEG source maps. These functional brain topographies showed individual and event-related desynchronization (ERD) activity in the sensorimotor area, where the -ERD is located more focal and inter-subject consistent in the feet area than the -ERD. With this work we are providing a fully data-driven method capable to identify first, EEG rhythms for each subject individually without any spatial a priori region of interest and second, to localize these rhythmic changes on the cortical level.