Publikation

Design and Evaluation of a Self Adaptive Architecture for Upper-Limb Rehabilitation

Alexis Heloir, Fabrizio Nunnari, Sylvain Haudegond, Clémentine Havrez, Yoann Lebrun, Christophe Kolski

In: M. Habib Fardoun , M. Victor R. Penichet , M. Daniyal Alghazzawi . ICTs for Improving Patients Rehabilitation Research Techniques: Second International Workshop, REHAB 2014, Oldenburg, Germany, May 20-23, 2014, Revised Selected Papers. Kapitel Design and Evaluation of a Self Adaptive Architect Seiten 196-209 ISBN 978-3-662-48645-0 Springer Berlin, Heidelberg 2015.

Abstrakt

This chapter presents an intuitive user interface based on a self-adaptive architecture. It uses a consumer-range 3D hand capture device that allows its users 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 user model. This model then drives the re-arrangement and reparameterization of a rule-based system that controls the interaction. A user study let us define the initial parameters of this self-adaptive system. This preliminary study was conducted in a 3D infographics and animation school on 15 students. The study was both qualitative and quantitative: the qualitative evaluation consisted of a SUMI evaluation questionnaire while the quantitative evaluation consisted of analysing manually annotated recordings of the subjects together with a fine-grained log of the interaction mechanics. We believe that the self-adaptive aspects of the system is well suited to the problematics of rehabilitation. This system could, 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.

Weitere Links

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence