Ambient Intelligence Environment for Home Cognitive Telerehabilitation
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 ther...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2018-10-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/18/11/3671 |
| _version_ | 1811278131127910400 |
|---|---|
| author | Miguel Oliver Miguel A. Teruel José Pascual Molina Dulce Romero-Ayuso Pascual González |
| author_facet | Miguel Oliver Miguel A. Teruel José Pascual Molina Dulce Romero-Ayuso Pascual González |
| author_sort | Miguel Oliver |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-13T00:30:18Z |
| format | Article |
| id | doaj.art-b13378fab39140419558a2b13f0c2d2e |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T00:30:18Z |
| publishDate | 2018-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-b13378fab39140419558a2b13f0c2d2e2022-12-22T03:10:30ZengMDPI AGSensors1424-82202018-10-011811367110.3390/s18113671s18113671Ambient Intelligence Environment for Home Cognitive TelerehabilitationMiguel Oliver0Miguel A. Teruel1José Pascual Molina2Dulce Romero-Ayuso3Pascual González4LoUISE Research Group, Research Institute of Informatics, University of Castilla-La Mancha, 02071 Albacete, SpainLoUISE Research Group, Research Institute of Informatics, University of Castilla-La Mancha, 02071 Albacete, SpainLoUISE Research Group, Computing Systems Department, University of Castilla-La Mancha, 02071 Albacete, SpainDepartment of Physical Therapy, Occupational Therapy Division, Faculty of Health Sciences, University of Granada, 18016 Granada, SpainLoUISE Research Group, Computing Systems Department, University of Castilla-La Mancha, 02071 Albacete, SpainHigher 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.https://www.mdpi.com/1424-8220/18/11/3671computer-assisted telerehabilitationpervasive computingambient assisted livingwearable sensorelectroencephalogram (EEG) headsetKinecthaptic stimulusfuzzy inference systemdistributed systemserious game |
| spellingShingle | Miguel Oliver Miguel A. Teruel José Pascual Molina Dulce Romero-Ayuso Pascual González Ambient Intelligence Environment for Home Cognitive Telerehabilitation Sensors computer-assisted telerehabilitation pervasive computing ambient assisted living wearable sensor electroencephalogram (EEG) headset Kinect haptic stimulus fuzzy inference system distributed system serious game |
| title | Ambient Intelligence Environment for Home Cognitive Telerehabilitation |
| title_full | Ambient Intelligence Environment for Home Cognitive Telerehabilitation |
| title_fullStr | Ambient Intelligence Environment for Home Cognitive Telerehabilitation |
| title_full_unstemmed | Ambient Intelligence Environment for Home Cognitive Telerehabilitation |
| title_short | Ambient Intelligence Environment for Home Cognitive Telerehabilitation |
| title_sort | ambient intelligence environment for home cognitive telerehabilitation |
| topic | computer-assisted telerehabilitation pervasive computing ambient assisted living wearable sensor electroencephalogram (EEG) headset Kinect haptic stimulus fuzzy inference system distributed system serious game |
| url | https://www.mdpi.com/1424-8220/18/11/3671 |
| work_keys_str_mv | AT migueloliver ambientintelligenceenvironmentforhomecognitivetelerehabilitation AT miguelateruel ambientintelligenceenvironmentforhomecognitivetelerehabilitation AT josepascualmolina ambientintelligenceenvironmentforhomecognitivetelerehabilitation AT dulceromeroayuso ambientintelligenceenvironmentforhomecognitivetelerehabilitation AT pascualgonzalez ambientintelligenceenvironmentforhomecognitivetelerehabilitation |