ArticleSensors (Basel, Switzerland)2018
Ambient Intelligence Environment for Home Cognitive Telerehabilitation.
Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
8 citing papers in PubMed, 38 citations in OpenAlex.
- Feasibility assessment of textile electromyography sensors for a wearable telehealth biofeedback system.Wearable technologies · 2025Article
- Artificial Intelligence-Driven Serious Games in Health Care: Scoping Review.JMIR serious games · 2022Article
- Telemedicine as a strategic intervention for cognitive rehabilitation in MS patients during COVID-19.Acta neurologica Belgica · 2022Review
- TV Interaction as a Non-Invasive Sensor for Monitoring Elderly Well-Being at Home.Sensors (Basel, Switzerland) · 2021Article
- Directing and Orienting ICT Healthcare Solutions to Address the Needs of the Aging Population.Healthcare (Basel, Switzerland) · 2021Review
- Fostering Sustainability through Visualization Techniques for Real-Time IoT Data: A Case Study Based on Gas Turbines for Electricity Production.Sensors (Basel, Switzerland) · 2020Article
- Self-Regulation in Children with Neurodevelopmental Disorders "SR-MRehab: Un Colegio Emocionante": A Protocol Study.International journal of environmental research and public health · 2020Article
- Mobile Applications in Evaluations of Knee Joint Kinematics: A Pilot Study.Sensors (Basel, Switzerland) · 2019Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.