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Multi-sensor exercise-based interactive games for fall prevention and rehabilitation

 
: Santos, A.; Guimaraes, V.; Matos, N.; Cevada, J.; Ferreira, C.; Sousa, I.

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Institute of Electrical and Electronics Engineers -IEEE-; Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering -ICST-, Brussels:
9th International Conference on Pervasive Computing Technologies for Healthcare, PervasiveHealth 2015. Proceedings : Istanbul, Turkey, May 20 - 23, 2015
Piscataway, NJ: IEEE, 2015
ISBN: 978-1-4799-8097-0
ISBN: 978-1-63190-045-7
S.65-71
International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) <9, 2015, Istanbul>
Englisch
Konferenzbeitrag
Fraunhofer AICOS ()

Abstract
According to statistics, one in every three adults ageing 65 or older falls every year. Every fall may lead to long-term consequences due to fractures or even neurological damages. These consequences have severe impact in their quality of life, independence and confidence, ultimately increasing the risk of early death. Moreover, the risk of falling increases as age advances. Fortunately, several studies reveal that specific exercise programmes may help in reducing the risk of falling if performed correctly and frequently. However, user engagement and adherence to these programmes are still low mainly due to motivational factors, since interventions are usually long, unadapted and unchallenging. In this paper, a new solution is presented, which uses the concept of interactive games using motion sensors to tackle low adherence (through gaming motivation) and help in physical rehabilitation and reduce fall risk on elderly people by improving balance, muscle strength and mobility. It is intended to be used in community or domestic unsupervised contexts and supports relatively inexpensive sensing equipment (currently Kinect®, Leap Motion®, Orbotix Sphero® and Smartphones) and common platforms (desktop and mobile). Tests were already undertaken with several individuals ageing 65 or more and the results were analysed and discussed, being generally positive, despite some issues in the movement detection algorithms.

: http://publica.fraunhofer.de/dokumente/N-418066.html