Abstract
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.
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Notes
- 1.
http://www.xbox.com/kinect (10 September 2014).
- 2.
http://www.leapmotion.com (10 September 2014).
- 3.
http://supinfocom.rubika-edu.com/ (10 September 2014).
- 4.
http://www.autodesk.fr/products/3ds-max/overview (10 September 2014).
- 5.
http://www.autodesk.fr/products/maya/overview (10 September 2014).
- 6.
http://www.blender.org/ (10 September 2014).
- 7.
http://slsi.dfki.de/software-and-resources/ (10 September 2014).
- 8.
http://sumi.ucc.ie/ (10 September 2014).
- 9.
“windows, icons, menus, pointer”.
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Acknowledgment
Authors would especially like to thank the students who participated to the study as well as Azad Lusbaronian, head of studies at Supinfocom / Rubika SAS for his involvement and the essential help he provided.
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Heloir, A., Nunnari, F., Haudegond, S., Havrez, C., Lebrun, Y., Kolski, C. (2015). Design and Evaluation of a Self Adaptive Architecture for Upper-Limb Rehabilitation. In: Fardoun, H., R. Penichet, V., Alghazzawi, D. (eds) ICTs for Improving Patients Rehabilitation Research Techniques. REHAB 2014. Communications in Computer and Information Science, vol 515. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48645-0_17
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