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Wearable kinesthetic system for capturing and classifying upper limb gesture in post-stroke rehabilitation
BACKGROUND: Monitoring body kinematics has fundamental relevance in several biological and technical disciplines. In particular the possibility to exactly know the posture may furnish a main aid in rehabilitation topics. In the present work an innovative and unobtrusive garment able to detect the po...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2005
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1079930/ https://www.ncbi.nlm.nih.gov/pubmed/15743530 http://dx.doi.org/10.1186/1743-0003-2-8 |
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author | Tognetti, Alessandro Lorussi, Federico Bartalesi, Raphael Quaglini, Silvana Tesconi, Mario Zupone, Giuseppe De Rossi, Danilo |
author_facet | Tognetti, Alessandro Lorussi, Federico Bartalesi, Raphael Quaglini, Silvana Tesconi, Mario Zupone, Giuseppe De Rossi, Danilo |
author_sort | Tognetti, Alessandro |
collection | PubMed |
description | BACKGROUND: Monitoring body kinematics has fundamental relevance in several biological and technical disciplines. In particular the possibility to exactly know the posture may furnish a main aid in rehabilitation topics. In the present work an innovative and unobtrusive garment able to detect the posture and the movement of the upper limb has been introduced, with particular care to its application in post stroke rehabilitation field by describing the integration of the prototype in a healthcare service. METHODS: This paper deals with the design, the development and implementation of a sensing garment, from the characterization of innovative comfortable and diffuse sensors we used to the methodologies employed to gather information on the posture and movement which derive from the entire garments. Several new algorithms devoted to the signal acquisition, the treatment and posture and gesture reconstruction are introduced and tested. RESULTS: Data obtained by means of the sensing garment are analyzed and compared with the ones recorded using a traditional movement tracking system. CONCLUSION: The main results treated in this work are summarized and remarked. The system was compared with a commercial movement tracking system (a set of electrogoniometers) and it performed the same accuracy in detecting upper limb postures and movements. |
format | Text |
id | pubmed-1079930 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2005 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-10799302005-04-15 Wearable kinesthetic system for capturing and classifying upper limb gesture in post-stroke rehabilitation Tognetti, Alessandro Lorussi, Federico Bartalesi, Raphael Quaglini, Silvana Tesconi, Mario Zupone, Giuseppe De Rossi, Danilo J Neuroengineering Rehabil Research BACKGROUND: Monitoring body kinematics has fundamental relevance in several biological and technical disciplines. In particular the possibility to exactly know the posture may furnish a main aid in rehabilitation topics. In the present work an innovative and unobtrusive garment able to detect the posture and the movement of the upper limb has been introduced, with particular care to its application in post stroke rehabilitation field by describing the integration of the prototype in a healthcare service. METHODS: This paper deals with the design, the development and implementation of a sensing garment, from the characterization of innovative comfortable and diffuse sensors we used to the methodologies employed to gather information on the posture and movement which derive from the entire garments. Several new algorithms devoted to the signal acquisition, the treatment and posture and gesture reconstruction are introduced and tested. RESULTS: Data obtained by means of the sensing garment are analyzed and compared with the ones recorded using a traditional movement tracking system. CONCLUSION: The main results treated in this work are summarized and remarked. The system was compared with a commercial movement tracking system (a set of electrogoniometers) and it performed the same accuracy in detecting upper limb postures and movements. BioMed Central 2005-03-02 /pmc/articles/PMC1079930/ /pubmed/15743530 http://dx.doi.org/10.1186/1743-0003-2-8 Text en Copyright © 2005 Tognetti 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 Tognetti, Alessandro Lorussi, Federico Bartalesi, Raphael Quaglini, Silvana Tesconi, Mario Zupone, Giuseppe De Rossi, Danilo Wearable kinesthetic system for capturing and classifying upper limb gesture in post-stroke rehabilitation |
title | Wearable kinesthetic system for capturing and classifying upper limb gesture in post-stroke rehabilitation |
title_full | Wearable kinesthetic system for capturing and classifying upper limb gesture in post-stroke rehabilitation |
title_fullStr | Wearable kinesthetic system for capturing and classifying upper limb gesture in post-stroke rehabilitation |
title_full_unstemmed | Wearable kinesthetic system for capturing and classifying upper limb gesture in post-stroke rehabilitation |
title_short | Wearable kinesthetic system for capturing and classifying upper limb gesture in post-stroke rehabilitation |
title_sort | wearable kinesthetic system for capturing and classifying upper limb gesture in post-stroke rehabilitation |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1079930/ https://www.ncbi.nlm.nih.gov/pubmed/15743530 http://dx.doi.org/10.1186/1743-0003-2-8 |
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