Issue No. 01 - March (2016 vol. 8)
Michele Pirovano , Department of Computer Science, Università degli Studi di Milano, Milano, Italy
Renato Mainetti , Department of Computer Science, Università degli Studi di Milano, Milano, Italy
Gabriel Baud-Bovy , Robotics, Brain and Cognitive Sciences Department, Istituto Italiano di Tecnologia, Genoa, Italy
Pier Luca Lanzi , Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy
N. Alberto Borghese , Department of Computer Science, Università degli Studi di Milano, Milano, Italy
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.
avatars, computer animation, feedback, fuzzy systems, patient rehabilitation, patient treatment, serious games (computing)
M. Pirovano, R. Mainetti, G. Baud-Bovy, P. L. Lanzi and N. A. Borghese, "Intelligent Game Engine for Rehabilitation (IGER)," in IEEE Transactions on Computational Intelligence and AI in Games, vol. 8, no. 1, pp. 43-55, 2016.