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Intelligent Therapy Assistant (ITA) for cognitive rehabilitation in patients with acquired brain injury
BACKGROUND: This paper presents the design, development and first evaluation of an algorithm, named Intelligent Therapy Assistant (ITA), which automatically selects, configures and schedules rehabilitation tasks for patients with cognitive impairments after an episode of Acquired Brain Injury. The I...
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/PMC4115474/ https://www.ncbi.nlm.nih.gov/pubmed/25038823 http://dx.doi.org/10.1186/1472-6947-14-58 |
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author | Solana, Javier Cáceres, César García-Molina, Alberto Chausa, Paloma Opisso, Eloy Roig-Rovira, Teresa Menasalvas, Ernestina Tormos-Muñoz, José M Gómez, Enrique J |
author_facet | Solana, Javier Cáceres, César García-Molina, Alberto Chausa, Paloma Opisso, Eloy Roig-Rovira, Teresa Menasalvas, Ernestina Tormos-Muñoz, José M Gómez, Enrique J |
author_sort | Solana, Javier |
collection | PubMed |
description | BACKGROUND: This paper presents the design, development and first evaluation of an algorithm, named Intelligent Therapy Assistant (ITA), which automatically selects, configures and schedules rehabilitation tasks for patients with cognitive impairments after an episode of Acquired Brain Injury. The ITA is integrated in “Guttmann, Neuro Personal Trainer” (GNPT), a cognitive tele-rehabilitation platform that provides neuropsychological services. METHODS: The ITA selects those tasks that are more suitable for the specific needs of each patient, considering previous experiences, and improving the personalization of the treatment. The system applies data mining techniques to cluster the patients according their cognitive impairment profile. Then, the algorithm rates every rehabilitation task, based on its cognitive structure and the clinical impact of executions done by similar patients. Finally, it configures the most suitable degree of difficulty, depending on the impairment of the patient and his/her evolution during the treatment. RESULTS: The ITA has been evaluated during 18 months by 582 patients. In order to evaluate the effectiveness of the ITA, a comparison between the traditional manual planning procedure and the one presented in this paper has been done, taking into account: a) the selected tasks assigned to rehabilitation sessions; b) the difficulty level configured for the sessions; c) and the improvement of their cognitive capacities after completing treatment. CONCLUSIONS: The obtained results reveal that the rehabilitation treatment proposed by the ITA is as effective as the one performed manually by therapists, arising as a new powerful support tool for therapists. The obtained results make us conclude that the proposal done by the ITA is very close to the one done by therapists, so it is suitable for real treatments. |
format | Online Article Text |
id | pubmed-4115474 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-41154742014-08-05 Intelligent Therapy Assistant (ITA) for cognitive rehabilitation in patients with acquired brain injury Solana, Javier Cáceres, César García-Molina, Alberto Chausa, Paloma Opisso, Eloy Roig-Rovira, Teresa Menasalvas, Ernestina Tormos-Muñoz, José M Gómez, Enrique J BMC Med Inform Decis Mak Research Article BACKGROUND: This paper presents the design, development and first evaluation of an algorithm, named Intelligent Therapy Assistant (ITA), which automatically selects, configures and schedules rehabilitation tasks for patients with cognitive impairments after an episode of Acquired Brain Injury. The ITA is integrated in “Guttmann, Neuro Personal Trainer” (GNPT), a cognitive tele-rehabilitation platform that provides neuropsychological services. METHODS: The ITA selects those tasks that are more suitable for the specific needs of each patient, considering previous experiences, and improving the personalization of the treatment. The system applies data mining techniques to cluster the patients according their cognitive impairment profile. Then, the algorithm rates every rehabilitation task, based on its cognitive structure and the clinical impact of executions done by similar patients. Finally, it configures the most suitable degree of difficulty, depending on the impairment of the patient and his/her evolution during the treatment. RESULTS: The ITA has been evaluated during 18 months by 582 patients. In order to evaluate the effectiveness of the ITA, a comparison between the traditional manual planning procedure and the one presented in this paper has been done, taking into account: a) the selected tasks assigned to rehabilitation sessions; b) the difficulty level configured for the sessions; c) and the improvement of their cognitive capacities after completing treatment. CONCLUSIONS: The obtained results reveal that the rehabilitation treatment proposed by the ITA is as effective as the one performed manually by therapists, arising as a new powerful support tool for therapists. The obtained results make us conclude that the proposal done by the ITA is very close to the one done by therapists, so it is suitable for real treatments. BioMed Central 2014-07-19 /pmc/articles/PMC4115474/ /pubmed/25038823 http://dx.doi.org/10.1186/1472-6947-14-58 Text en Copyright © 2014 Solana et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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 Article Solana, Javier Cáceres, César García-Molina, Alberto Chausa, Paloma Opisso, Eloy Roig-Rovira, Teresa Menasalvas, Ernestina Tormos-Muñoz, José M Gómez, Enrique J Intelligent Therapy Assistant (ITA) for cognitive rehabilitation in patients with acquired brain injury |
title | Intelligent Therapy Assistant (ITA) for cognitive rehabilitation in patients with acquired brain injury |
title_full | Intelligent Therapy Assistant (ITA) for cognitive rehabilitation in patients with acquired brain injury |
title_fullStr | Intelligent Therapy Assistant (ITA) for cognitive rehabilitation in patients with acquired brain injury |
title_full_unstemmed | Intelligent Therapy Assistant (ITA) for cognitive rehabilitation in patients with acquired brain injury |
title_short | Intelligent Therapy Assistant (ITA) for cognitive rehabilitation in patients with acquired brain injury |
title_sort | intelligent therapy assistant (ita) for cognitive rehabilitation in patients with acquired brain injury |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4115474/ https://www.ncbi.nlm.nih.gov/pubmed/25038823 http://dx.doi.org/10.1186/1472-6947-14-58 |
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