Demos
Demonstrations provide researchers and practitioners with an exciting and interactive opportunity to present their systems, artifacts and/or research prototypes, either at a regular session or at the technical exhibition. In any case, it is required to avoid a commercial format, even if the demo consists of presenting a business product or service. Instead, the presentation should focus on technical aspects.
Any written support materials may be distributed locally but not published in the proceedings. Authors who already present a paper at the conference may apply for a demonstration, to complement but not to replace their paper presentation. Demonstrations can also be made by sponsor companies or as a mixed initiative involving researchers and industrial partners.
Demonstrations are based on an informal setting that encourages presenters and participants to engage in discussions about the presented work. This is an opportunity for the participants to disseminate practical results of their research and to network with other applied researchers or business partners.
Concerning the format of the demo, we can accommodate it either as a demonstration in a booth (physical area of 4 sq. meter, with a table and 2 chairs) at the exhibition area, as a poster or as a 20 min oral presentation at a session especially set up for demonstrations. It is also possible to organize the presentation of the same demo in more than one format.
Please contact the
event secretariat.
A Vision-based Training System for Stroke Survivors
Lecturer
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Renato Baptista
University of Luxembourg
Luxembourg
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Brief Bio
Renato Baptista completed the Integrated Master in Electrical and Computer Engineering of the Faculty of Sciences and Technology of the University of Coimbra, Portugal in 2013. His M.Sc. thesis was in Computer Vision area with the title: "Face Recognition in Low Quality Video Images via Sparse Encoding". From 2014 to 2016, he worked as an optical fiber splicer/technician in Luxembourg. His research interests are within the areas of computer vision, machine learning and robotics.
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Abstract
This demo presents a developed vision-based system for the home-based rehabilitation of stroke survivors in the context of the European project H2020 “STARR”. This system is composed of two connected Kinect-based applications: a therapist-side application and . This vision-based system provides a set of functionalities that are to be personalized for each patient by therapists. The functionalities in question consist in: 1) Feedback proposals guiding a personalized exercise session, 2) Posture monitoring optimizing effectiveness of the session, 3) Assessment of the quality of the motion. The personalization happens through a defined set of parameters calibrated per patient for both the upper limb and the lower limb where each time the healthy side is taken as a reference for the impaired side. The proposed system may be adapted to other applications such as guidance of training for sports at a professional level. The two described applications as well as the different functionalities will be shown during this demo.