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Model-based variables for the kinematic assessment of upper-extremity impairments in post-stroke patients

BACKGROUND: Common scales for clinical evaluation of post-stroke upper-limb motor recovery are often complemented with kinematic parameters extracted from movement trajectories. However, there is no a general consensus on which parameters to use. Moreover, the selected variables may be redundant and...

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Autores principales: Panarese, Alessandro, Pirondini, Elvira, Tropea, Peppino, Cesqui, Benedetta, Posteraro, Federico, Micera, Silvestro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5016877/
https://www.ncbi.nlm.nih.gov/pubmed/27609062
http://dx.doi.org/10.1186/s12984-016-0187-9
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author Panarese, Alessandro
Pirondini, Elvira
Tropea, Peppino
Cesqui, Benedetta
Posteraro, Federico
Micera, Silvestro
author_facet Panarese, Alessandro
Pirondini, Elvira
Tropea, Peppino
Cesqui, Benedetta
Posteraro, Federico
Micera, Silvestro
author_sort Panarese, Alessandro
collection PubMed
description BACKGROUND: Common scales for clinical evaluation of post-stroke upper-limb motor recovery are often complemented with kinematic parameters extracted from movement trajectories. However, there is no a general consensus on which parameters to use. Moreover, the selected variables may be redundant and highly correlated or, conversely, may incompletely sample the kinematic information from the trajectories. Here we sought to identify a set of clinically useful variables for an exhaustive but yet economical kinematic characterization of upper limb movements performed by post-stroke hemiparetic subjects. METHODS: For this purpose, we pursued a top-down model-driven approach, seeking which kinematic parameters were pivotal for a computational model to generate trajectories of point-to-point planar movements similar to those made by post-stroke subjects at different levels of impairment. RESULTS: The set of kinematic variables used in the model allowed for the generation of trajectories significantly similar to those of either sub-acute or chronic post-stroke patients at different time points during the therapy. Simulated trajectories also correctly reproduced many kinematic features of real movements, as assessed by an extensive set of kinematic metrics computed on both real and simulated curves. When inspected for redundancy, we found that variations in the variables used in the model were explained by three different underlying and unobserved factors related to movement efficiency, speed, and accuracy, possibly revealing different working mechanisms of recovery. CONCLUSION: This study identified a set of measures capable of extensively characterizing the kinematics of upper limb movements performed by post-stroke subjects and of tracking changes of different motor improvement aspects throughout the rehabilitation process. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12984-016-0187-9) contains supplementary material, which is available to authorized users.
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spelling pubmed-50168772016-09-10 Model-based variables for the kinematic assessment of upper-extremity impairments in post-stroke patients Panarese, Alessandro Pirondini, Elvira Tropea, Peppino Cesqui, Benedetta Posteraro, Federico Micera, Silvestro J Neuroeng Rehabil Research BACKGROUND: Common scales for clinical evaluation of post-stroke upper-limb motor recovery are often complemented with kinematic parameters extracted from movement trajectories. However, there is no a general consensus on which parameters to use. Moreover, the selected variables may be redundant and highly correlated or, conversely, may incompletely sample the kinematic information from the trajectories. Here we sought to identify a set of clinically useful variables for an exhaustive but yet economical kinematic characterization of upper limb movements performed by post-stroke hemiparetic subjects. METHODS: For this purpose, we pursued a top-down model-driven approach, seeking which kinematic parameters were pivotal for a computational model to generate trajectories of point-to-point planar movements similar to those made by post-stroke subjects at different levels of impairment. RESULTS: The set of kinematic variables used in the model allowed for the generation of trajectories significantly similar to those of either sub-acute or chronic post-stroke patients at different time points during the therapy. Simulated trajectories also correctly reproduced many kinematic features of real movements, as assessed by an extensive set of kinematic metrics computed on both real and simulated curves. When inspected for redundancy, we found that variations in the variables used in the model were explained by three different underlying and unobserved factors related to movement efficiency, speed, and accuracy, possibly revealing different working mechanisms of recovery. CONCLUSION: This study identified a set of measures capable of extensively characterizing the kinematics of upper limb movements performed by post-stroke subjects and of tracking changes of different motor improvement aspects throughout the rehabilitation process. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12984-016-0187-9) contains supplementary material, which is available to authorized users. BioMed Central 2016-09-08 /pmc/articles/PMC5016877/ /pubmed/27609062 http://dx.doi.org/10.1186/s12984-016-0187-9 Text en © The Author(s). 2016 Open AccessThis 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
Panarese, Alessandro
Pirondini, Elvira
Tropea, Peppino
Cesqui, Benedetta
Posteraro, Federico
Micera, Silvestro
Model-based variables for the kinematic assessment of upper-extremity impairments in post-stroke patients
title Model-based variables for the kinematic assessment of upper-extremity impairments in post-stroke patients
title_full Model-based variables for the kinematic assessment of upper-extremity impairments in post-stroke patients
title_fullStr Model-based variables for the kinematic assessment of upper-extremity impairments in post-stroke patients
title_full_unstemmed Model-based variables for the kinematic assessment of upper-extremity impairments in post-stroke patients
title_short Model-based variables for the kinematic assessment of upper-extremity impairments in post-stroke patients
title_sort model-based variables for the kinematic assessment of upper-extremity impairments in post-stroke patients
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5016877/
https://www.ncbi.nlm.nih.gov/pubmed/27609062
http://dx.doi.org/10.1186/s12984-016-0187-9
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