Closed-loop neuroprosthetic control through spared neural activity enables proportional foot movements after spinal cord injury

OBJECTIVE: Loss of voluntary foot movement after spinal cord injury (SCI) can significantly limit independent mobility and quality of life. To improve motor output after injury, functional electrical stimulation (FES) is used to deliver stimulation pulses through the skin to affected muscles. While commercial FES systems typically use motion-based triggers, prior research shows that spared movement intent can be decoded after SCI using surface electromyography (EMG). Our aim is to assess how well spared neural signals of the lower limb after SCI can be decoded and used to control electrical stimulation for restoring foot movement. APPROACH: We developed a wearable machine-learning-powered neuroprosthetic that records EMG from the affected lower limb using a 32-channel electrode bracelet and enables closed-loop control of an FES device for foot movement restoration. MAIN RESULTS: Five participants with SCI used the predicted control signal to follow trajectories on a screen with their foot and achieve distinct motor activation patterns for foot flexion, extension, and inversion or eversion. Three of these participants also achieved 2 proportional activation levels during foot flexion/extension with >70% overall accuracy. To validate how these neural signals can be used for closed-loop neuroprosthetic control, two participants used their decoded activity to control an FES device and stimulate their affected foot. This resulted in an increased foot flexion range in every stimulated contraction for both participants, on average 33.6% and 40% of a functional healthy range, respectively (p < 0.001). One of the participants also achieved voluntary proportional control of up to 6 stimulation levels during foot flexion/extension. SIGNIFICANCE: These results suggest that wearable EMG decoding coupled with FES systems provides a scalable strategy for closed-loop neuroprosthetic control supporting voluntary foot movement.

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Publication Details

Journal
Journal of Neural Engineering
Published
2026-10-29
DOI
https://doi.org/10.1088/1741-2552/aebb64
Primary Topic
Spinal Cord Injury Research
Type
article
Field-Weighted Citation Impact
0.00

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article

Closed-loop neuroprosthetic control through spared neural activity enables proportional foot movements after spinal cord injury

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Journal of Neural Engineering
Spinal Cord Injury Research
article

Closed-loop neuroprosthetic control through spared neural activity enables proportional foot movements after spinal cord injury

article en

Abstract

OBJECTIVE: Loss of voluntary foot movement after spinal cord injury (SCI) can significantly limit independent mobility and quality of life. To improve motor output after injury, functional electrical stimulation (FES) is used to deliver stimulation pulses through the skin to affected muscles. While commercial FES systems typically use motion-based triggers, prior research shows that spared movement intent can be decoded after SCI using surface electromyography (EMG). Our aim is to assess how well spared neural signals of the lower limb after SCI can be decoded and used to control electrical stimulation for restoring foot movement. APPROACH: We developed a wearable machine-learning-powered neuroprosthetic that records EMG from the affected lower limb using a 32-channel electrode bracelet and enables closed-loop control of an FES device for foot movement restoration. MAIN RESULTS: Five participants with SCI used the predicted control signal to follow trajectories on a screen with their foot and achieve distinct motor activation patterns for foot flexion, extension, and inversion or eversion. Three of these participants also achieved 2 proportional activation levels during foot flexion/extension with >70% overall accuracy. To validate how these neural signals can be used for closed-loop neuroprosthetic control, two participants used their decoded activity to control an FES device and stimulate their affected foot. This resulted in an increased foot flexion range in every stimulated contraction for both participants, on average 33.6% and 40% of a functional healthy range, respectively (p < 0.001). One of the participants also achieved voluntary proportional control of up to 6 stimulation levels during foot flexion/extension. SIGNIFICANCE: These results suggest that wearable EMG decoding coupled with FES systems provides a scalable strategy for closed-loop neuroprosthetic control supporting voluntary foot movement.

Journal of Neural Engineering
Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
Deutsche Forschungsgemeinschaft, Bayerische Staatsministerium für Wirtschaft, Landesentwicklung und Energie, HORIZON EUROPE European Research Council
Good health and well-being
Openalex Percentile: Top 100%
Spinal Cord Injury Research
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