2038 Restoration of Proprioception Function Through a Bi-Directional Human-Device Neural Interface

INTRODUCTION: Neural prosthetic interfaces represent a promising therapeutic modality for patients who have experienced loss of extremity function from traumatic brain injury, stroke, spinal cord injury or limb amputation. Proprioception—an essential function for fine motor control, trajectory planning, and gait—remains challenging to restore within current neural prosthetic strategies as existing approaches rely on non-naturalistic afferent feedback delivered via off-target sensory pathways. The agonist-antagonist myoneural interface (AMI) was developed to enable proprioceptive feedback from a bionic limb. METHODS: We tested this hypothesis through evaluation of baseline lower-extremity EMG and fascicle strain dynamics, psychometric evaluation of sensory function in response to electrical stimulation, and joint-angle precision during open- and closed-loop neural control of an advanced robotic limb. RESULTS: We found that subjects with the AMI construct demonstrated superior proprioception function as measured by improved differentiation of both electrical activation and muscle fascicle stretch during efferent motor control as well as when receiving afferent feedback during closed-loop control of a powered robotic ankle prosthesis. CONCLUSIONS: The study validates the AMI approach for proprioceptive recovery, providing proof-of-principle for afferent torque force feedback and a blueprint for integration of proprioception function into advanced neural prosthetic systems. This work builds on the pioneering AMI framework, offering a significant step towards intuitive neural prosthetic control.

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Publication Details

Journal
Neurosurgery
Published
2025-03-14
DOI
https://doi.org/10.1227/neu.0000000000003360_2038
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
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article

2038 Restoration of Proprioception Function Through a Bi-Directional Human-Device Neural Interface

Tony Shu, Hugh Herr, Gabriel Friedman, S. Tim Yoon et al.
Neurosurgery
EEG and Brain-Computer Interfaces
article

2038 Restoration of Proprioception Function Through a Bi-Directional Human-Device Neural Interface

Tony Shu, Hugh Herr, Gabriel Friedman, S. Tim Yoon, Junqing Qiao, Peter Myers, Gabriel Feuerwerker
article en

Abstract

INTRODUCTION: Neural prosthetic interfaces represent a promising therapeutic modality for patients who have experienced loss of extremity function from traumatic brain injury, stroke, spinal cord injury or limb amputation. Proprioception—an essential function for fine motor control, trajectory planning, and gait—remains challenging to restore within current neural prosthetic strategies as existing approaches rely on non-naturalistic afferent feedback delivered via off-target sensory pathways. The agonist-antagonist myoneural interface (AMI) was developed to enable proprioceptive feedback from a bionic limb. METHODS: We tested this hypothesis through evaluation of baseline lower-extremity EMG and fascicle strain dynamics, psychometric evaluation of sensory function in response to electrical stimulation, and joint-angle precision during open- and closed-loop neural control of an advanced robotic limb. RESULTS: We found that subjects with the AMI construct demonstrated superior proprioception function as measured by improved differentiation of both electrical activation and muscle fascicle stretch during efferent motor control as well as when receiving afferent feedback during closed-loop control of a powered robotic ankle prosthesis. CONCLUSIONS: The study validates the AMI approach for proprioceptive recovery, providing proof-of-principle for afferent torque force feedback and a blueprint for integration of proprioception function into advanced neural prosthetic systems. This work builds on the pioneering AMI framework, offering a significant step towards intuitive neural prosthetic control.

NeurosurgeryVol. 71(Supplement_1)
Openalex Percentile: Top 95%
EEG and Brain-Computer Interfaces
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2038 Restoration of Proprioception Function Through a Bi-Directional Human-Device Neural Interface — Tony Shu, Hugh Herr, et al. · Neurosurgery (2025) | TGRS Research Map | TGRS