Visual and human-interpretable feedback for assisting physical activity

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Abstract

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.

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Antunes, M., Baptista, R., Demisse, G., Aouada, D., & Ottersten, B. (2016). Visual and human-interpretable feedback for assisting physical activity. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9914 LNCS, pp. 115–129). Springer Verlag. https://doi.org/10.1007/978-3-319-48881-3_9

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