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Assessment of biofeedback rehabilitation in post-stroke patients combining fMRI and gait analysis: a case study
BACKGROUND: The ability to walk independently is a primary goal for rehabilitation after stroke. Gait analysis provides a great amount of valuable information, while functional magnetic resonance imaging (fMRI) offers a powerful approach to define networks involved in motor control. The present stud...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3984495/ https://www.ncbi.nlm.nih.gov/pubmed/24716475 http://dx.doi.org/10.1186/1743-0003-11-53 |
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author | Del Din, Silvia Bertoldo, Alessandra Sawacha, Zimi Jonsdottir, Johanna Rabuffetti, Marco Cobelli, Claudio Ferrarin, Maurizio |
author_facet | Del Din, Silvia Bertoldo, Alessandra Sawacha, Zimi Jonsdottir, Johanna Rabuffetti, Marco Cobelli, Claudio Ferrarin, Maurizio |
author_sort | Del Din, Silvia |
collection | PubMed |
description | BACKGROUND: The ability to walk independently is a primary goal for rehabilitation after stroke. Gait analysis provides a great amount of valuable information, while functional magnetic resonance imaging (fMRI) offers a powerful approach to define networks involved in motor control. The present study reports a new methodology based on both fMRI and gait analysis outcomes in order to investigate the ability of fMRI to reflect the phases of motor learning before/after electromyographic biofeedback treatment: the preliminary fMRI results of a post stroke subject’s brain activation, during passive and active ankle dorsal/plantarflexion, before and after biofeedback (BFB) rehabilitation are reported and their correlation with gait analysis data investigated. METHODS: A control subject and a post-stroke patient with chronic hemiparesis were studied. Functional magnetic resonance images were acquired during a block-design protocol on both subjects while performing passive and active ankle dorsal/plantarflexion. fMRI and gait analysis were assessed on the patient before and after electromyographic biofeedback rehabilitation treatment during gait activities. Lower limb three-dimensional kinematics, kinetics and surface electromyography were evaluated. Correlation between fMRI and gait analysis categorical variables was assessed: agreement/disagreement was assigned to each variable if the value was in/outside the normative range (gait analysis), or for presence of normal/diffuse/no activation of motor area (fMRI). RESULTS: Altered fMRI activity was found on the post-stroke patient before biofeedback rehabilitation with respect to the control one. Meanwhile the patient showed a diffuse, but more limited brain activation after treatment (less voxels). The post-stroke gait data showed a trend towards the normal range: speed, stride length, ankle power, and ankle positive work increased. Preliminary correlation analysis revealed that consistent changes were observed both for the fMRI data, and the gait analysis data after treatment (R > 0.89): this could be related to the possible effects BFB might have on the central as well as on the peripheral nervous system. CONCLUSIONS: Our findings showed that this methodology allows evaluation of the relationship between alterations in gait and brain activation of a post-stroke patient. Such methodology, if applied on a larger sample subjects, could provide information about the specific motor area involved in a rehabilitation treatment. |
format | Online Article Text |
id | pubmed-3984495 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-39844952014-04-13 Assessment of biofeedback rehabilitation in post-stroke patients combining fMRI and gait analysis: a case study Del Din, Silvia Bertoldo, Alessandra Sawacha, Zimi Jonsdottir, Johanna Rabuffetti, Marco Cobelli, Claudio Ferrarin, Maurizio J Neuroeng Rehabil Research BACKGROUND: The ability to walk independently is a primary goal for rehabilitation after stroke. Gait analysis provides a great amount of valuable information, while functional magnetic resonance imaging (fMRI) offers a powerful approach to define networks involved in motor control. The present study reports a new methodology based on both fMRI and gait analysis outcomes in order to investigate the ability of fMRI to reflect the phases of motor learning before/after electromyographic biofeedback treatment: the preliminary fMRI results of a post stroke subject’s brain activation, during passive and active ankle dorsal/plantarflexion, before and after biofeedback (BFB) rehabilitation are reported and their correlation with gait analysis data investigated. METHODS: A control subject and a post-stroke patient with chronic hemiparesis were studied. Functional magnetic resonance images were acquired during a block-design protocol on both subjects while performing passive and active ankle dorsal/plantarflexion. fMRI and gait analysis were assessed on the patient before and after electromyographic biofeedback rehabilitation treatment during gait activities. Lower limb three-dimensional kinematics, kinetics and surface electromyography were evaluated. Correlation between fMRI and gait analysis categorical variables was assessed: agreement/disagreement was assigned to each variable if the value was in/outside the normative range (gait analysis), or for presence of normal/diffuse/no activation of motor area (fMRI). RESULTS: Altered fMRI activity was found on the post-stroke patient before biofeedback rehabilitation with respect to the control one. Meanwhile the patient showed a diffuse, but more limited brain activation after treatment (less voxels). The post-stroke gait data showed a trend towards the normal range: speed, stride length, ankle power, and ankle positive work increased. Preliminary correlation analysis revealed that consistent changes were observed both for the fMRI data, and the gait analysis data after treatment (R > 0.89): this could be related to the possible effects BFB might have on the central as well as on the peripheral nervous system. CONCLUSIONS: Our findings showed that this methodology allows evaluation of the relationship between alterations in gait and brain activation of a post-stroke patient. Such methodology, if applied on a larger sample subjects, could provide information about the specific motor area involved in a rehabilitation treatment. BioMed Central 2014-04-09 /pmc/articles/PMC3984495/ /pubmed/24716475 http://dx.doi.org/10.1186/1743-0003-11-53 Text en Copyright © 2014 Del Din 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 credited. |
spellingShingle | Research Del Din, Silvia Bertoldo, Alessandra Sawacha, Zimi Jonsdottir, Johanna Rabuffetti, Marco Cobelli, Claudio Ferrarin, Maurizio Assessment of biofeedback rehabilitation in post-stroke patients combining fMRI and gait analysis: a case study |
title | Assessment of biofeedback rehabilitation in post-stroke patients combining fMRI and gait analysis: a case study |
title_full | Assessment of biofeedback rehabilitation in post-stroke patients combining fMRI and gait analysis: a case study |
title_fullStr | Assessment of biofeedback rehabilitation in post-stroke patients combining fMRI and gait analysis: a case study |
title_full_unstemmed | Assessment of biofeedback rehabilitation in post-stroke patients combining fMRI and gait analysis: a case study |
title_short | Assessment of biofeedback rehabilitation in post-stroke patients combining fMRI and gait analysis: a case study |
title_sort | assessment of biofeedback rehabilitation in post-stroke patients combining fmri and gait analysis: a case study |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3984495/ https://www.ncbi.nlm.nih.gov/pubmed/24716475 http://dx.doi.org/10.1186/1743-0003-11-53 |
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