Prediction of Isometric Handgrip Force from Graded Event-Related Desynchronization of the Sensorimotor Rhythm
Published in Journal of Neural Engineering, 2021
Recommended citation: Haddix et al. (2021). "Prediction of Isometric Handgrip Force from Graded Event-Related Desynchronization of the Sensorimotor Rhythm." Journal of Neural Engineering. 18(5). https://doi.org/10.1088/1741-2552/ac23c0
This study investigates whether different levels of isometric handgrip force can be decoded from electroencephalography (EEG) to provide graded command signals for brain-computer interfaces.
Fourteen healthy participants performed visually guided handgrip movements at different levels of force while EEG and grip force were recorded. Event-related desynchronization of the 8–30 Hz mu-beta sensorimotor rhythm varied with motor effort, demonstrating that EEG contains information that can distinguish different degrees of effort.
The findings support the feasibility of using intended motor effort as a graded control signal and suggest potential applications in brain-computer interfaces and rehabilitation following motor impairment.
Recommended citation: Haddix et al. (2021). “Prediction of Isometric Handgrip Force from Graded Event-Related Desynchronization of the Sensorimotor Rhythm.” Journal of Neural Engineering. 18(5).