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Updated: Oct 14, 2025

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
Published on: May 8, 2021
Skilled independent control of individual motor units via a non-invasive neuromuscular-machine interface
Emanuele Formento1, Paul Botros1, Jose M Carmena1,2
1Department of Electrical Engineering and Computer Sciences, University of California Berkeley, Berkeley, CA 94720, United States of America.
Abstract:
Objective.Brain-machine interfaces (BMIs) have the potential to augment human functions and restore independence in people with disabilities, yet a compromise between non-invasiveness and performance limits their relevance.Approach.Here, we hypothesized that a non-invasive neuromuscular-machine interface providing real-time neurofeedback of individual motor units within a muscle could enable independent motor unit control to an extent suitable for high-performance BMI applications.Main results.Over 6 days of training, eight participants progressively learned to skillfully and independently control three biceps brachii motor units to complete a 2D center-out task. We show that neurofeedback enabled motor unit activity that largely violated recruitment constraints observed during ramp-and-hold isometric contractions thought to limit individual motor unit controllability. Finally, participants demonstrated the suitability of individual motor units for powering general applications through a spelling task.Significance.These results illustrate the flexibility of the sensorimotor system and highlight individual motor units as a promising source of control for BMI applications.
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