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| Autores principales: | , , , , , , , , , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2402.11776 |
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| author | Lim, Jeffrey Wang, Po T. Sohn, Wonjoon Serrano-Amenos, Claudia Ibrahim, Mina Lin, Derrick Thaploo, Shravan Shaw, Susan J. Armacost, Michelle Gong, Hui Lee, Brian Lee, Darrin Andersen, Richard A. Heydari, Payam Liu, Charles Y. Nenadic, Zoran Do, An H. |
| author_facet | Lim, Jeffrey Wang, Po T. Sohn, Wonjoon Serrano-Amenos, Claudia Ibrahim, Mina Lin, Derrick Thaploo, Shravan Shaw, Susan J. Armacost, Michelle Gong, Hui Lee, Brian Lee, Darrin Andersen, Richard A. Heydari, Payam Liu, Charles Y. Nenadic, Zoran Do, An H. |
| contents | 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 settings. 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$\pm$0.08 between cues and decoded states over 5 runs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_11776 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Early feasibility of an embedded bi-directional brain-computer interface for ambulation Lim, Jeffrey Wang, Po T. Sohn, Wonjoon Serrano-Amenos, Claudia Ibrahim, Mina Lin, Derrick Thaploo, Shravan Shaw, Susan J. Armacost, Michelle Gong, Hui Lee, Brian Lee, Darrin Andersen, Richard A. Heydari, Payam Liu, Charles Y. Nenadic, Zoran Do, An H. Quantitative Methods 92C55 Current treatments for paraplegia induced by spinal cord injury (SCI) are often limited by the severity of the injury. The accompanying loss of sensory and motor functions often results in reliance on wheelchairs, which in turn causes reduced quality of life and increased risk of co-morbidities. While brain-computer interfaces (BCIs) for ambulation have shown promise in restoring or replacing lower extremity motor functions, none so far have simultaneously implemented sensory feedback functions. Additionally, many existing BCIs for ambulation rely on bulky external hardware that make them ill-suited for non-research settings. Here, we present an embedded bi-directional BCI (BDBCI), that restores motor function by enabling neural control over a robotic gait exoskeleton (RGE) and delivers sensory feedback via direct cortical electrical stimulation (DCES) in response to RGE leg swing. A first demonstration with this system was performed with a single subject implanted with electrocorticography electrodes, achieving an average lag-optimized cross-correlation of 0.80$\pm$0.08 between cues and decoded states over 5 runs. |
| title | Early feasibility of an embedded bi-directional brain-computer interface for ambulation |
| topic | Quantitative Methods 92C55 |
| url | https://arxiv.org/abs/2402.11776 |