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Virtual Reality as Assessment Tool of the Risk of Falls in the Elderly

We present an assessment tool, based on virtual reality technology, for predicting motor control, attentional or cognitive factors of risk of falls in the elderly. Falls are the leading cause of accidents among the elderly. Each year, it affects 1 in 4 people over the age of 65. In order to better understand and predict this risk of falling, we developed an immersion solution that can collect and identify various indicators of the risk of falling. This easy-to-use solution automates the experimental protocol and the data collection of indicators, and immerses the patient in realistic everyday situations. Our virtual reality device, uses a total of 6 sensors worn by the patient to capture a kinematic of the complete body and generate a virtual avatar in real time to the patient. These kinematic data, replayable for the health practitioner, train a digital process. The scientific experiment, patient-centered, is based on 6 tests of motor or attentional disturbances, requiring global functional abilities. The results obtained showed that for high-risk fall patients, the longer completion times and the number of steps for the different tests compared to low-risk fall patients. Specifically, the introduction of manual and cognitive tasks affects high-risk fall patients more significantly.

Fall, Motor Control, Aging, Immersive Virtual Reality

Fabien Clanché, Gabin Personeni, Alexandre Renaux, Frédéric Muhla, Thierry Bastogne, et al. (2023). Virtual Reality as Assessment Tool of the Risk of Falls in the Elderly. International Journal of Sensors and Sensor Networks, 11(1), 11-17.

Copyright © 2023 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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