Computer games are a promising tool to support rehabilitation at home. It is widely recognized that rehabilitation games should (i) be nicely integrated in general-purpose rehabilitation stations, (ii) adhere to the constraints posed by the clinical protocols, (iii) involve movements that are functional to reach the rehabilitation goal, and (iv) adapt to the patients' current status and progress. However, the vast majority of existing rehabilitation games are stand-alone applications (not integrated in a patient station), that rarely adapt to the patients' condition. In this paper, we present the first prototype of the patient rehabilitation station we developed that integrates video games for rehabilitation with methods of computational intelligence both for on-line monitoring the movements' execution during the games and for adapting the gameplay to the patients' status. The station employs a fuzzy system to monitor the exercises execution, on-line, according to the clinical constraints defined by the therapist at configuration time, and to provide direct feedback to the patients. At the same time, it applies real-time adaptation (using the Quest Bayesian adaptive approach) to modify the gameplay according both (i) to the patient current performance and progress and (ii) to the exercise plan specified by the therapist. Finally, we present one of the games available in our patient stations (designed in tight cooperation with therapists) that integrates monitoring functionalities with in-game self-adaptation to provide the best support possible to patients during their routine.

Background: Post-stroke recovery benefits from structured, intense, challenging, and repetitive therapy. Exergames have emerged as promising to achieve sustained therapy practice and patient motivation. This study assessed the usability and effects of exergames on balance and gait. Subjects and Methods: Sixteen elderly participants were provided with the study intervention based on five newly developed exergames. The participants were required to attend 36 training sessions; lasting for 20 minutes each. Adherence, attrition and acceptance were assessed together with (1) Berg Balance Scale, (2) 7-m Timed Up and Go, (3) Short Physical Performance Battery, (4) force platform stance tests, and (5) gait analysis. Results: Thirteen participants completed the study (18.8 percent attrition), without missing a single training session (100 percent adherence). Participants showed high acceptance of the intervention. Only minor adaptations in the program were needed based on the users' feedback. No changes in center of pressure area during quiet stance on both stable and unstable surfaces and no changes of walking parameters were detected. Scores for the Berg Balance Scale ( P =0.007; r =0.51), the 7-m Timed Up and Go ( P =0.002; r =0.56), and the Short Physical Performance Battery ( P =0.013; r =0.48) increased significantly with moderate to large effect sizes. Conclusion: Participants evaluated the usability of the virtual reality training intervention positively. Results indicate that the intervention improves gait- and balance-related physical performance measures in untrained elderly. The present results warrant a clinical explorative study investigating the usability and effectiveness of the exergame-based program in stroke patients.

Computer games are a promising tool to support intensive rehabilitation. However, at present, they do not incorporate the supervision provided by a real therapist and do not allow safe and effective use at a patient's home. We show how specifically tailored computational intelligence based techniques allow extending exergames with functionalities that make rehabilitation at home effective and safe. The main function is in monitoring the correctness of motion, which is fundamental in avoiding developing wrong motion patterns, making rehabilitation more harmful than effective. Fuzzy systems enable us to capture the knowledge of the therapist and to provide real-time feedback of the patient's motion quality with a novel informative color coding applied to the patient's avatar. This feedback is complemented with a therapist avatar that, in extreme cases, explains the correct way to carry out the movements required by the exergames. The avatar also welcomes the patient and summarizes the therapy results to him/her. Text to speech and simple animation improve the engagement. Another important element is adaptation. Only the proper level of challenge exercises can be both effective and safe. For this reason exergames can be fully configured by therapists in terms of speed, range of motion, or accuracy. These parameters are then tuned during exercise to the patient's performance through a Bayesian framework that also takes into account input from the therapist. A log of all the interaction data is stored for clinicians to assess and tune the therapy, and to advise patients. All this functionality has been added to a classical game engine that is extended to embody a virtual therapist aimed at supervising the motion, which is the final goal of the exergames for rehabilitation. This approach can be of broad interest in the serious games domain. Preliminary results with patients and therapists suggest that the approach can maintain a proper challenge level while keeping the patient motivated, safe, and supervised.

BACKGROUND: Video-games are becoming a common tool to guide patients through rehabilitation because of their power of motivating and engaging their users. Video-games may also be integrated into an infrastructure that allows patients, discharged from

The recent availability of advanced video game interfaces (such as the Microsoft Kinect, the Nintendo WiiMote and Balance Board) is creating interesting opportunities to provide low-cost rehabilitation at-home for patients. In this context, video games are rising as promising tools to guide patients through their recovery experience and to increase their motivation throughout the rehabilitation path. However, to be applied to clinical scenarios, video games must be designed to adhere to the clinical requirements and to meet doctors/patients expectations. They also need to be integrated within multi-level platforms that can allow different levels of monitoring, e.g., at a personal level by the therapist, at the hospital level by the doctors, and at the regional level by the government agencies. In this paper, we overview an intelligent game engine for the at-home rehabilitation of stroke patients The engine provides several games that implement actual rehabilitation exercises and have been developed in strict collaboration with therapists. It is integrated in a patient station that provides several types of monitoring and feedback using virtual and/or human therapists.