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Adaptive multichannel FES neuroprosthesis with learning control and automatic gait assessment

BACKGROUND: FES (Functional Electrical Stimulation) neuroprostheses have long been a permanent feature in the rehabilitation and gait support of people who had a stroke or have a Spinal Cord Injury (SCI). Over time the well-known foot switch triggered drop foot neuroprosthesis, was extended to a mul...

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Autores principales: Müller, Philipp, del Ama, Antonio J., Moreno, Juan C., Schauer, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7048130/
https://www.ncbi.nlm.nih.gov/pubmed/32111245
http://dx.doi.org/10.1186/s12984-020-0640-7
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author Müller, Philipp
del Ama, Antonio J.
Moreno, Juan C.
Schauer, Thomas
author_facet Müller, Philipp
del Ama, Antonio J.
Moreno, Juan C.
Schauer, Thomas
author_sort Müller, Philipp
collection PubMed
description BACKGROUND: FES (Functional Electrical Stimulation) neuroprostheses have long been a permanent feature in the rehabilitation and gait support of people who had a stroke or have a Spinal Cord Injury (SCI). Over time the well-known foot switch triggered drop foot neuroprosthesis, was extended to a multichannel full-leg support neuroprosthesis enabling improved support and rehabilitation. However, these neuroprostheses had to be manually tuned and could not adapt to the persons’ individual needs. In recent research, a learning controller was added to the drop foot neuroprosthesis, so that the full stimulation pattern during the swing phase could be adapted by measuring the joint angles of previous steps. METHODS: The aim of this research is to begin developing a learning full-leg supporting neuroprosthesis, which controls the antagonistic muscle pairs for knee flexion and extension, as well as for ankle joint dorsi- and plantarflexion during all gait phases. A method was established that allows a continuous assessment of knee and foot joint angles with every step. This method can warp the physiological joint angles of healthy subjects to match the individual pathological gait of the subject and thus allows a direct comparison of the two. A new kind of Iterative Learning Controller (ILC) is proposed which works independent of the step duration of the individual and uses physiological joint angle reference bands. RESULTS: In a first test with four people with an incomplete SCI, the results showed that the proposed neuroprosthesis was able to generate individually fitted stimulation patterns for three of the participants. The other participant was more severely affected and had to be excluded due to the resulting false triggering of the gait phase detection. For two of the three remaining participants, a slight improvement in the average foot angles could be observed, for one participant slight improvements in the averaged knee angles. These improvements where in the range of 4(circ)at the times of peak dorsiflexion, peak plantarflexion, or peak knee flexion. CONCLUSIONS: Direct adaptation to the current gait of the participants could be achieved with the proposed method. The preliminary first test with people with a SCI showed that the neuroprosthesis can generate individual stimulation patterns. The sensitivity to the knee angle reset, timing problems in participants with significant gait fluctuations, and the automatic ILC gain tuning are remaining issues that need be addressed. Subsequently, future studies should compare the improved, long-term rehabilitation effects of the here presented neuroprosthesis, with conventional multichannel FES neuroprostheses.
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spelling pubmed-70481302020-03-05 Adaptive multichannel FES neuroprosthesis with learning control and automatic gait assessment Müller, Philipp del Ama, Antonio J. Moreno, Juan C. Schauer, Thomas J Neuroeng Rehabil Research BACKGROUND: FES (Functional Electrical Stimulation) neuroprostheses have long been a permanent feature in the rehabilitation and gait support of people who had a stroke or have a Spinal Cord Injury (SCI). Over time the well-known foot switch triggered drop foot neuroprosthesis, was extended to a multichannel full-leg support neuroprosthesis enabling improved support and rehabilitation. However, these neuroprostheses had to be manually tuned and could not adapt to the persons’ individual needs. In recent research, a learning controller was added to the drop foot neuroprosthesis, so that the full stimulation pattern during the swing phase could be adapted by measuring the joint angles of previous steps. METHODS: The aim of this research is to begin developing a learning full-leg supporting neuroprosthesis, which controls the antagonistic muscle pairs for knee flexion and extension, as well as for ankle joint dorsi- and plantarflexion during all gait phases. A method was established that allows a continuous assessment of knee and foot joint angles with every step. This method can warp the physiological joint angles of healthy subjects to match the individual pathological gait of the subject and thus allows a direct comparison of the two. A new kind of Iterative Learning Controller (ILC) is proposed which works independent of the step duration of the individual and uses physiological joint angle reference bands. RESULTS: In a first test with four people with an incomplete SCI, the results showed that the proposed neuroprosthesis was able to generate individually fitted stimulation patterns for three of the participants. The other participant was more severely affected and had to be excluded due to the resulting false triggering of the gait phase detection. For two of the three remaining participants, a slight improvement in the average foot angles could be observed, for one participant slight improvements in the averaged knee angles. These improvements where in the range of 4(circ)at the times of peak dorsiflexion, peak plantarflexion, or peak knee flexion. CONCLUSIONS: Direct adaptation to the current gait of the participants could be achieved with the proposed method. The preliminary first test with people with a SCI showed that the neuroprosthesis can generate individual stimulation patterns. The sensitivity to the knee angle reset, timing problems in participants with significant gait fluctuations, and the automatic ILC gain tuning are remaining issues that need be addressed. Subsequently, future studies should compare the improved, long-term rehabilitation effects of the here presented neuroprosthesis, with conventional multichannel FES neuroprostheses. BioMed Central 2020-02-28 /pmc/articles/PMC7048130/ /pubmed/32111245 http://dx.doi.org/10.1186/s12984-020-0640-7 Text en © The Author(s) 2020 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Müller, Philipp
del Ama, Antonio J.
Moreno, Juan C.
Schauer, Thomas
Adaptive multichannel FES neuroprosthesis with learning control and automatic gait assessment
title Adaptive multichannel FES neuroprosthesis with learning control and automatic gait assessment
title_full Adaptive multichannel FES neuroprosthesis with learning control and automatic gait assessment
title_fullStr Adaptive multichannel FES neuroprosthesis with learning control and automatic gait assessment
title_full_unstemmed Adaptive multichannel FES neuroprosthesis with learning control and automatic gait assessment
title_short Adaptive multichannel FES neuroprosthesis with learning control and automatic gait assessment
title_sort adaptive multichannel fes neuroprosthesis with learning control and automatic gait assessment
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7048130/
https://www.ncbi.nlm.nih.gov/pubmed/32111245
http://dx.doi.org/10.1186/s12984-020-0640-7
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