Personalized Exergames Language: A Novel Approach to the Automatic Generation of Personalized Exergames for Stroke Patients

Physical rehabilitation of stroke patients is based on the daily execution of exercises with face-to-face supervision by therapists. This model cannot be sustained in the long term, due to the involved economic costs, the growing number of patients, and the aging population. Remote rehabilitation to...

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Veröffentlicht in:Applied sciences 2020-10, Vol.10 (20), p.7378
Hauptverfasser: Vallejo, David, Gmez-Portes, Cristian, Albusac, Javier, Glez-Morcillo, Carlos, Castro-Schez, Jose Jesus
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Sprache:eng
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Zusammenfassung:Physical rehabilitation of stroke patients is based on the daily execution of exercises with face-to-face supervision by therapists. This model cannot be sustained in the long term, due to the involved economic costs, the growing number of patients, and the aging population. Remote rehabilitation tools have emerged to address this unmet clinical need, but they face the double challenge of motivating patients and ensuring an effective remote rehabilitation. In this context, exergames allow patients to play while performing repetitive therapeutic tasks in a safe and ecological environment. This work proposes the design of Personalized Exergames Language (PEL), a language whose sentences can be processed via software in order to automatically generate exergames. The definition of exergames through PEL, guided by an effective methodology of the design and generation of personalized exergames, will include both game mechanics and the necessary metrics to monitor, guide, and adapt the rehabilitation of each patient. The integration of authoring tools are considered to visually guide the therapist when designing exergames. A study has been carried out with stroke patients and therapists from a hospital and two community centers, in order to evaluate several exergames, automatically generated using PEL, in terms of usability, understanding, and suitability.
ISSN:2076-3417
2076-3417
DOI:10.3390/app10207378