Prediction of Isometric Handgrip Force from Graded Event-Related Desynchronization of the Sensorimotor Rhythm

Brain–computer interfaces (BCIs) show promise as a direct line of communication between the brain and the outside world that could benefit those with impaired motor function. But the commands available for BCI operation are often limited by the ability of the decoder to differentiate between the many distinct motor or cognitive tasks that can be visualized or attempted. Here, we attempt to decode the degree of effort in a specific movement task to produce a graded and more flexible command signal with 14 healthy human subjects who responded to visual cues by squeezing to different levels of predetermined force, guided by continuous visual feedback, while the EEG and grip force were monitored. We found that event-related desynchronization (ERD) of the 8–30 Hz mu-beta sensorimotor rhythm of the EEG is separable for different degrees of motor effort. Our results suggest that modeling and interactive feedback based on the intended level of motor effort is feasible. The observed trends suggest that different mechanisms may govern intermediate versus low and high degrees of motor effort. This may have utility in rehabilitative protocols for motor impairments.

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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.