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Sensors 2018, 18(11), 3671; https://doi.org/10.3390/s18113671

Ambient Intelligence Environment for Home Cognitive Telerehabilitation

1
LoUISE Research Group, Research Institute of Informatics, University of Castilla-La Mancha, 02071 Albacete, Spain
2
LoUISE Research Group, Computing Systems Department, University of Castilla-La Mancha, 02071 Albacete, Spain
3
Department of Physical Therapy, Occupational Therapy Division, Faculty of Health Sciences, University of Granada, 18016 Granada, Spain
4
CIBERSAM, Biomedical Research Networking Centre in Mental Health, 28029 Madrid, Spain
*
Author to whom correspondence should be addressed.
Received: 26 September 2018 / Revised: 19 October 2018 / Accepted: 25 October 2018 / Published: 29 October 2018
(This article belongs to the Special Issue New Trends in Ambient Intelligence Applications)
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Abstract

Higher life expectancy is increasing the number of age-related cognitive impairment cases. It is also relevant, as some authors claim, that physical exercise may be considered as an adjunctive therapy to improve cognition and memory after strokes. Thus, the integration of physical and cognitive therapies could offer potential benefits. In addition, in general these therapies are usually considered boring, so it is important to include some features that improve the motivation of patients. As a result, computer-assisted cognitive rehabilitation systems and serious games for health are more and more present. In order to achieve a continuous, efficient and sustainable rehabilitation of patients, they will have to be carried out as part of the rehabilitation in their own home. However, current home systems lack the therapist’s presence, and this leads to two major challenges for such systems. First, they need sensors and actuators that compensate for the absence of the therapist’s eyes and hands. Second, the system needs to capture and apply the therapist’s expertise. With this aim, and based on our previous proposals, we propose an ambient intelligence environment for cognitive rehabilitation at home, combining physical and cognitive activities, by implementing a Fuzzy Inference System (FIS) that gathers, as far as possible, the knowledge of a rehabilitation expert. Moreover, smart sensors and actuators will attempt to make up for the absence of the therapist. Furthermore, the proposed system will feature a remote monitoring tool, so that the therapist can supervise the patients’ exercises. Finally, an evaluation will be presented where experts in the rehabilitation field showed their satisfaction with the proposed system. View Full-Text
Keywords: computer-assisted telerehabilitation; pervasive computing; ambient assisted living; wearable sensor; electroencephalogram (EEG) headset; Kinect; haptic stimulus; fuzzy inference system; distributed system; serious game computer-assisted telerehabilitation; pervasive computing; ambient assisted living; wearable sensor; electroencephalogram (EEG) headset; Kinect; haptic stimulus; fuzzy inference system; distributed system; serious game
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Oliver, M.; Teruel, M.A.; Molina, J.P.; Romero-Ayuso, D.; González, P. Ambient Intelligence Environment for Home Cognitive Telerehabilitation. Sensors 2018, 18, 3671.

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