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Descripción
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| 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. | |
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Internacional
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Si |
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JCR del ISI
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Si |
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Título de la revista
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BMC Medical Informatics and Decision Making |
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ISSN
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1472-6947 |
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Factor de impacto JCR
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1,5 |
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Información de impacto
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Volumen
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14 |
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DOI
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10.1186/1472-6947-14-58 |
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Número de revista
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58 |
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Desde la página
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online |
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Hasta la página
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online |
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Mes
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JULIO |
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Ranking
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13 de 25 (Q3) |