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.
The learning of programming is a field of research with relevant studies and publications for more than 25 years. Since its inception, it has been shown that its difficulty lies in the high level of abstraction required to understand certain programming concepts. However, this level can be reduced by using tools and graphic representations that motivate students and facilitate their understanding, associating real-world elements with specific programming concepts. Thus, this paper proposes the use of an intelligent tutoring system (ITS) that helps during the learning of programming by using a notation based on a metaphor of roads and traffic signs represented by 3D graphics in an augmented reality (AR) environment. These graphic visualizations can be generated automatically from the source code of the programs thanks to the modular and scalable design of the system. Students can use them by leveraging the available feedback system, and teachers can also use them in order to explain programming concepts during the classes. This work highlights the flexibility and extensibility of the proposal through its application in different use cases that we have selected as examples to show how the system could be exploited in a multitude of real learning scenarios.
Physical rehabilitation of people who suffer from some motor disability involves an intensive treatment to reduce pain and improve quality of life. Research studies have proven the benefits of technologies based on home-rehabilitation, which complement regular therapy in hospitals. Although there is a significant number of studies that face this challenge when dealing with adults, it has not been explored with young people. In this research article, we focus on this population, since the repetition of physical exercises decreases the youth’s motivation, which entails a high risk of dropping out of therapy. That is why we present a systematic mapping study of the techniques, devices, and methods used to address home rehabilitation for children and teenagers. The conclusions indicate that it is essential to use gamification techniques to adopt a plug-and-play metaphor, based on natural interaction mechanisms and on the use of non-intrusive devices, and to customize the rehabilitation process for each individual along with a methodology. We also present the improvements applied to an existing gamification-based software prototype for home rehabilitation. In this system, physical exercises can be customized, laying the foundations to promote precision rehabilitation within the context of young people.
Stroke represents a global concern that currently affects a significant part of the world's population. Physical rehabilitation plays a fundamental role for stroke patients to recover mobility and improve quality of life. This process is costly, considering that patients must attend face-to-face rehabilitation sessions in hospitals or rehabilitation centers. Plus, there is a lack of specialized medical staff, who are usually insufficient to properly address the growing number of stroke patients that need physical rehabilitation. This situation has been exacerbated by the COVID-19 pandemic, as some of the human resources have been devoted to fight against the pandemic, and the physical presence of rehabilitation patients in hospitals has been severely limited. This paper proposes PhyRe Up!, a novel remote rehabilitation system that uses mixed reality and gamification techniques. PhyRe Up! has been devised for stroke patients to perform therapeutic exercises at home, with great precision, and with the potential supervision of clinicians. The system aims to increase the patient's motivation as well as maintaining the quality of performance for the exercises, similar to the obtained levels when attending face-to-face sessions with therapists. The underlying architecture combines declarative, procedural, and conditional knowledge to manage the rehabilitation process, which offers flexibility and scalability to enhance the capabilities of the proposed system. Experimental results highlight how the combination of mixed reality and gamification significantly influences the accuracy of rehabilitation exercises previously defined by therapists. Particularly, the conducted experiments in the first validation phase of PhyRe Up! shows that our proposal drastically reduces the intermediate steps required to complete an exercise thanks to the provided visual feedback. The accuracy with which the patient performs the assessed exercise for the first time is greater than when using traditional rehabilitation techniques.
Stroke is among the top 10 leading causes of death and disability around the world. Patients who suffer from this disease usually perform physical exercises at home to improve their condition. These exercises are recommended by therapists based on the patient’s progress level, and may be remotely supervised by them if technology is an option for both. At this point, two major challenges must be faced. The first one is the lack of specialized medical staff to remotely handle the growing number of stroke patients. The second one is the difficulty of dynamically adapt the patient’s therapy plan in real time whilst they rehabilitate at home, since their evolution varies as the rehabilitation process progresses. In this context, we present a fuzzy system that is able to automatically adapt the rehabilitation plan of stroke patients. The use of fuzzy logic greatly facilitates the monitoring and guidance of stroke patients. Moreover, the system is capable of automatically generating modifications of existent exercises whilst considering their particularities at any given time. A preliminary experiment was conducted to show the advantages of the proposal, and the results suggest that the application of fuzzy logic may help make correct decisions based on the patient’s progress level.
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