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Early feasibility of an embedded bi-directional brain-computer interface for ambulation

Jeffrey Lim, Po T. Wang, Won Joon Sohn, Claudia Serrano-Amenos, Mina Ibrahim, Derrick Lin, Shravan Thaploo, Susan J. Shaw, Michelle Armacost, Hui Gong, Brian Lee, Darrin Lee, Richard A. Andersen, Payam Heydari, Charles Y. Liu, Zoran Nenadić, Hui An

Year
2024
Citations
1

Abstract

Current treatments for paraplegia induced by spinal cord injury (SCI) are often limited by the severity of the injury. The accompanying loss of sensory and motor functions often results in reliance on wheelchairs, which in turn causes reduced quality of life and increased risk of co-morbidities. While brain-computer interfaces (BCIs) for ambulation have shown promise in restoring or replacing lower extremity motor functions, none so far have simultaneously implemented sensory feedback functions. Additionally, many existing BCIs for ambulation rely on bulky external hardware that make them ill-suited for non-research set-tings. Here, we present an embedded bi-directional BCI (BDBCI), that restores motor function by enabling neural control over a robotic gait exoskeleton (RGE) and delivers sensory feedback via direct cortical electrical stimulation (DCES) in response to RGE leg swing. A first demonstration with this system was performed with a single subject implanted with electrocorticography electrodes, achieving an average lag-optimized cross-correlation of 0.80±0.08 between cues and decoded states over 5 runs.

Keywords

Brain–computer interfaceComputer scienceInterface (matter)Human–computer interactionOperating systemElectroencephalographyNeurosciencePsychology

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