Visual and human-interpretable feedback for assisting physical activity

Goncalves Almeida Antunes, Michel; Baptista, Renato; Demisse, Girum; Aouada, Djamila; Ottersten, Björn

Reference : Visual and human-interpretable feedback for assisting physical activity


	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/28312

Title :	Visual and human-interpretable feedback for assisting physical activity
Language :	English
Author, co-author :	Goncalves Almeida Antunes, Michel [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Baptista, Renato [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Demisse, Girum [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Aouada, Djamila [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Ottersten, Björn [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Publication date :	2016
Main document title :	European Conference on Computer Vision (ECCV) Workshop on Assistive Computer Vision and Robotics Amsterdam,
Peer reviewed :	Yes
Audience :	International
Event name :	European Conference on Computer Vision (ECCV) Workshop on Assistive Computer Vision and Robotics Amsterdam,
Event date :	9-10-2016
Abstract :	[en] Physical activity is essential for stroke survivors for recovering some autonomy in daily life activities. Post-stroke patients are initially subject to physical therapy under the supervision of a health professional, but due to economical aspects, home based rehabilitation is eventually suggested. In order to support the physical activity of stroke patients at home, this paper presents a system for guiding the user in how to properly perform certain actions and movements. This is achieved by presenting feedback in form of visual information and human-interpretable messages. The core of the proposed approach is the analysis of the motion required for aligning body-parts with respect to a template skeleton pose, and how this information can be presented to the user in form of simple recommendations. Experimental results in three datasets show the potential of the proposed framework.
Permalink :	http://hdl.handle.net/10993/28312

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