Abstract
Abstract
Objective. Neural interfaces need to become more unobtrusive and socially acceptable to appeal to general consumers outside rehabilitation settings. Approach. We developed a non-invasive neural interface that provides access to spinal motor neuron activities from the wrist, which is the preferred location for a wearable. The interface decodes far-field potentials present at the tendon endings of the forearm muscles using blind source separation. First, we evaluated the reliability of the interface to detect motor neuron firings based on far-field potentials, and thereafter we used the decoded motor neuron activity for the prediction of finger contractions in offline and real-time conditions. Main results. The results showed that motor neuron activity decoded from the far-field potentials at the wrist accurately predicted individual and combined finger commands and therefore allowed for highly accurate real-time task classification. Significance. These findings demonstrate the feasibility of a non-invasive, neural interface at the wrist for precise real-time control based on the output of the spinal cord.
Funder
Academy of Finland, project “Hi-Fi BiNDIng”
EPSRC Centre for Doctoral Training in Neurotechnology for Life and Health
European Research Council, Synergy grant, project Natural BionicS
Meta
Subject
Cellular and Molecular Neuroscience,Biomedical Engineering
Cited by
6 articles.
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