Description of a Self-adaptive Architecture for Upper-limb Rehabilitation

Alexis Heloir; Fabrizio Nunnari; Sylvain Haudegond; Yoann Lebrun; Christophe Kolski

In: Proceedings of the 8th International Conference on Pervasive Computing Technologies for Healthcare. International ICST Conference on Pervasive Computing Technologies for Healthcare (Pervasive Health-14), 8th International Conference on Pervasive Computing Technologies for Healthcare, Brussels, Belgium, Pages 317-320, PervasiveHealth '14, ISBN 978-1-63190-011-2, ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering), 2014.


This paper presents a natural and intuitive user interface architecture that uses a consumer-range 3D hand capture device to interactively edit objects in 3D space. While running, the system monitors the user’s behaviors and performance in order to maintain an up-to-date model of the user. This model then drives on the fly the re-arrangement and re-parameterization of a rule-based system that controls the interaction. A preliminary user study let us define the initial parameters of this self-adaptive system. We believe that the self-adaptive aspects of the architecture we propose is well suited to the problematics of rehabilitation. This system can, from the beginning, adapt to both the user’s impairments and needs, then follow and adapt its interaction logic according to the user’s progress. Such a system would, for instance, enable a clinician or a therapist to design tailored rehabilitation activities accounting for the patient’s exact physical and physiological condition.

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Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence