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Brain-computer interface controlled robotic gait orthosis

BACKGROUND: Excessive reliance on wheelchairs in individuals with tetraplegia or paraplegia due to spinal cord injury (SCI) leads to many medical co-morbidities, such as cardiovascular disease, metabolic derangements, osteoporosis, and pressure ulcers. Treatment of these conditions contributes to th...

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Autores principales: Do, An H, Wang, Po T, King, Christine E, Chun, Sophia N, Nenadic, Zoran
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3907014/
https://www.ncbi.nlm.nih.gov/pubmed/24321081
http://dx.doi.org/10.1186/1743-0003-10-111
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author Do, An H
Wang, Po T
King, Christine E
Chun, Sophia N
Nenadic, Zoran
author_facet Do, An H
Wang, Po T
King, Christine E
Chun, Sophia N
Nenadic, Zoran
author_sort Do, An H
collection PubMed
description BACKGROUND: Excessive reliance on wheelchairs in individuals with tetraplegia or paraplegia due to spinal cord injury (SCI) leads to many medical co-morbidities, such as cardiovascular disease, metabolic derangements, osteoporosis, and pressure ulcers. Treatment of these conditions contributes to the majority of SCI health care costs. Restoring able-body-like ambulation in this patient population can potentially reduce the incidence of these medical co-morbidities, in addition to increasing independence and quality of life. However, no biomedical solution exists that can reverse this loss of neurological function, and hence novel methods are needed. Brain-computer interface (BCI) controlled lower extremity prostheses may constitute one such novel approach. METHODS: One able-bodied subject and one subject with paraplegia due to SCI underwent electroencephalogram (EEG) recordings while engaged in alternating epochs of idling and walking kinesthetic motor imagery (KMI). These data were analyzed to generate an EEG prediction model for online BCI operation. A commercial robotic gait orthosis (RoGO) system (suspended over a treadmill) was interfaced with the BCI computer to allow for computerized control. The subjects were then tasked to perform five, 5-min-long online sessions where they ambulated using the BCI-RoGO system as prompted by computerized cues. The performance of this system was assessed with cross-correlation analysis, and omission and false alarm rates. RESULTS: The offline accuracy of the EEG prediction model averaged 86.30% across both subjects (chance: 50%). The cross-correlation between instructional cues and the BCI-RoGO walking epochs averaged across all subjects and all sessions was 0.812±0.048 (p-value <10(−4)). Also, there were on average 0.8 false alarms per session and no omissions. CONCLUSION: These results provide preliminary evidence that restoring brain-controlled ambulation after SCI is feasible. Future work will test the function of this system in a population of subjects with SCI. If successful, this may justify the future development of BCI-controlled lower extremity prostheses for free overground walking for those with complete motor SCI. Finally, this system can also be applied to incomplete motor SCI, where it could lead to improved neurological outcomes beyond those of standard physiotherapy.
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spelling pubmed-39070142014-02-12 Brain-computer interface controlled robotic gait orthosis Do, An H Wang, Po T King, Christine E Chun, Sophia N Nenadic, Zoran J Neuroeng Rehabil Research BACKGROUND: Excessive reliance on wheelchairs in individuals with tetraplegia or paraplegia due to spinal cord injury (SCI) leads to many medical co-morbidities, such as cardiovascular disease, metabolic derangements, osteoporosis, and pressure ulcers. Treatment of these conditions contributes to the majority of SCI health care costs. Restoring able-body-like ambulation in this patient population can potentially reduce the incidence of these medical co-morbidities, in addition to increasing independence and quality of life. However, no biomedical solution exists that can reverse this loss of neurological function, and hence novel methods are needed. Brain-computer interface (BCI) controlled lower extremity prostheses may constitute one such novel approach. METHODS: One able-bodied subject and one subject with paraplegia due to SCI underwent electroencephalogram (EEG) recordings while engaged in alternating epochs of idling and walking kinesthetic motor imagery (KMI). These data were analyzed to generate an EEG prediction model for online BCI operation. A commercial robotic gait orthosis (RoGO) system (suspended over a treadmill) was interfaced with the BCI computer to allow for computerized control. The subjects were then tasked to perform five, 5-min-long online sessions where they ambulated using the BCI-RoGO system as prompted by computerized cues. The performance of this system was assessed with cross-correlation analysis, and omission and false alarm rates. RESULTS: The offline accuracy of the EEG prediction model averaged 86.30% across both subjects (chance: 50%). The cross-correlation between instructional cues and the BCI-RoGO walking epochs averaged across all subjects and all sessions was 0.812±0.048 (p-value <10(−4)). Also, there were on average 0.8 false alarms per session and no omissions. CONCLUSION: These results provide preliminary evidence that restoring brain-controlled ambulation after SCI is feasible. Future work will test the function of this system in a population of subjects with SCI. If successful, this may justify the future development of BCI-controlled lower extremity prostheses for free overground walking for those with complete motor SCI. Finally, this system can also be applied to incomplete motor SCI, where it could lead to improved neurological outcomes beyond those of standard physiotherapy. BioMed Central 2013-12-09 /pmc/articles/PMC3907014/ /pubmed/24321081 http://dx.doi.org/10.1186/1743-0003-10-111 Text en Copyright © 2013 Do et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Do, An H
Wang, Po T
King, Christine E
Chun, Sophia N
Nenadic, Zoran
Brain-computer interface controlled robotic gait orthosis
title Brain-computer interface controlled robotic gait orthosis
title_full Brain-computer interface controlled robotic gait orthosis
title_fullStr Brain-computer interface controlled robotic gait orthosis
title_full_unstemmed Brain-computer interface controlled robotic gait orthosis
title_short Brain-computer interface controlled robotic gait orthosis
title_sort brain-computer interface controlled robotic gait orthosis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3907014/
https://www.ncbi.nlm.nih.gov/pubmed/24321081
http://dx.doi.org/10.1186/1743-0003-10-111
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