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.
Published in | International Journal of Sensors and Sensor Networks (Volume 11, Issue 1) |
DOI | 10.11648/j.ijssn.20231101.12 |
Page(s) | 11-17 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2023. Published by Science Publishing Group |
Fall, Motor Control, Aging, Immersive Virtual Reality
[1] | INSERM “Activité physique et prévention des chutes chez les personnes âgées”. Paris: Inserm, 2015, pp. 71–110. |
[2] | J. A. Painter et S. J. Elliott, “Influence of Gender on Falls”, Physical & Occupational Therapy in Geriatrics, 2009, vol. 27, pp. 387-404. |
[3] | J. T. Hanlon, L. R. Landerman, G. G. Fillenbaum et S. Studenski, “Falls in African American and white community-dwelling elderly residents ”, The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 2002, vol. 57, pp. 473-478. |
[4] | C. Léon et F. Beck, “Les comportements de santé des 55-85 ans analyses du Baromètre santé 2010”, Inpes éd., 2014. |
[5] | D. Podsiadlo et S. Richardson “The timed ‘Up & Go’: a test of basic functional mobility for frail elderly persons”, Journal of the American Geriatric Society, 1991, vol. 39, pp. 142-148. |
[6] | T. Herman, N. Giladi et J. M. Hausdorff, “Properties of the ‘timed up and go’test: more than meets the eye”, Gerontology, 2011, vol. 57, pp. 203- 210. |
[7] | R. W. Bohannon, “Reference values for the timed up and go test: a descriptive meta-analysis”, Journal of geriatric physical therapy, 2006, vol. 29, pp. 64-68. |
[8] | M. E. Tinetti, M. Speechleu et S. F. Ginter, “Risk factors for falls among elderly persons living in the community”, New England journal of medicine, 1988, vol. 319, pp. 1701-1707. |
[9] | A. A. Rizzo, M. Schultheis, K. A. Kerns et C. Mateer, “Analysis of assets for virtual reality applications in neuropsychology”, Neuropsychological rehabilitation, 2004, vol. 14, pp. 207-239. |
[10] | T. D. Parsons, “Virtual reality for enhanced ecological validity and experimental control in the clinical, affective and social neurosciences”, Frontiers in human neuroscience, 2015, vol. 9, p. 660. |
[11] | L. Lundin-Olsson, L. Nyberg, et Y. Gustafson, “Attention, frailty, and falls: the effect of a manual task on basic mobility”, Journal of the American Geriatric Society, 1998, vol. 46, pp. 758-761. |
[12] | R. C. Vance, D. G. Healy, R. Galvin, et H. P. French, “Dual tasking with the timed “up & go” test improves detection of risk of falls in people with Parkinson disease”, Physical therapy, 2015, vol. 95, pp. 95-102. |
[13] | S. N. Robinovitch, F. Feldman, Y. Yang, R. Schonnop, P. M. Leung, T. Sarraf, J. Sims-Gould et M. Loughin, “Video capture of the circumstances of falls in elderly people residing in long-term care: an observational study”, The Lancet, 2013, vol. 381, pp. 47-54. |
[14] | M. J. D. Caetano, S. R. Lord, D. Schoene, P. H. S. Pelicioni, D. L. Sturnieks et J. C. Menant, “Age-related changes in gait adaptability in response to unpredictable obstacles and stepping targets”, Gait & posture, 2016, vol. 46, pp. 35-41. |
[15] | H-C. Chen, J. A. Ashton-Miller, N. B. Alexander et A. B. Schultz, “Age- related changes in gait adaptability in response to unpredictable obstacles and stepping targets”, Gait & posture, 2016, vol. 46, pp. 35-41. |
[16] | F. Pieruccini-Faria et M. Montero-Odasso, “Obstacle Negotiation, Gait Variability, and Risk of Falling: Results From the ‘Gait and Brain Study’.”, The Journals of Gerontology, 2019, vol. 74, pp. 1422-1428. |
[17] | F. Pieruccini-Faria, Y. Sarquis-Adamson et M. Montero-Odasso, “Mild cognitive impairment affects obstacle negotiation in older adults: results from ‘gait and brain study’.”, Gerontology, 2019, vol. 65, pp. 164-173. |
[18] | D. T. Lai, S. B. Taylor et R. K. Begg, “Prediction of foot clearance parameters as a precursor to forecasting the risk of tripping and falling”, Human movement science, 2012, vol. 31, pp. 271-283. |
[19] | L. J. Hettinger et G. E. Riccio, “Visually induced motion sickness in virtual environments”, Presence: Teleoperators and Virtual Environments, 1992, vol. 1, pp. 306-310. |
[20] | Y. Pan et A. Steed. How foot tracking matters: The impact of an animated self-avatar on interaction, embodiment and presence in shared virtual environments”, Frontiers in Robotics and AI, 2019, vol. 6, p. 104. |
[21] | Steed, A., Y. Pan, F. Zisch et W. Steptoe. “The impact of a self-avatar on cognitive load in immersive virtual reality”, IEEE virtual reality (VR), 2016, pp. 67-76. |
[22] | B. J. Mohler, S. H. Creem-Regehr, W. B. Thompson et H. H. Bülthoff, “The effect of viewing a self-avatar on distance judgments in an HMD- based virtual environment”, Presence: Teleoperators and Virtual Environments, 2010, vol. 19, pp. 230-242. |
[23] | D. Tolani, A. Goswami, N. I. Badler, “Real-Time Inverse Kinematics Techniques for Anthropomorphic Limbs”, Graphical Models, 2000, vol. 62, pp 353-388. |
[24] | M. E. Tinetti, D. Richman et L. Powell, “Falls efficacy as a measure of fear of falling”, Journal of gerontology, 1990, vol. 45, pp. 239-243. |
[25] | G. I. J. M. Kempen, L. Yardley, J. C. M. Van Haastregt, G. A. R. Zijlstra, N. Beyer, K. Hauer et C. Todd, “The Short FES-I: a shortened version of the falls efficacy scale-international to assess fear of falling”, Age and ageing, 2008, vol. 37, pp. 45-50. |
[26] | F. Mourey, P. Manckoundia et P. Pfitzenmeyer, “La peur de tomber et ses conséquences: mise au point”, Les cahiers de l’année gérontologique, 2009, vol. 1, pp. 102-108. |
[27] | R. Vitório, F. Pieruccini-Faria, F. Stella, S. Gobbi et L. T. B. Gobbi, “Effects of obstacle height on obstacle crossing in mild Parkinson's disease”, Gait & Posture, 2010, vol. 31, pp. 143-146. |
APA Style
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. https://doi.org/10.11648/j.ijssn.20231101.12
ACS Style
Fabien Clanché; Gabin Personeni; Alexandre Renaux; Frédéric Muhla; Thierry Bastogne, et al. Virtual Reality as Assessment Tool of the Risk of Falls in the Elderly. Int. J. Sens. Sens. Netw. 2023, 11(1), 11-17. doi: 10.11648/j.ijssn.20231101.12
AMA Style
Fabien Clanché, Gabin Personeni, Alexandre Renaux, Frédéric Muhla, Thierry Bastogne, et al. Virtual Reality as Assessment Tool of the Risk of Falls in the Elderly. Int J Sens Sens Netw. 2023;11(1):11-17. doi: 10.11648/j.ijssn.20231101.12
@article{10.11648/j.ijssn.20231101.12, author = {Fabien Clanché and Gabin Personeni and Alexandre Renaux and Frédéric Muhla and Thierry Bastogne and Gérome Gauchard}, title = {Virtual Reality as Assessment Tool of the Risk of Falls in the Elderly}, journal = {International Journal of Sensors and Sensor Networks}, volume = {11}, number = {1}, pages = {11-17}, doi = {10.11648/j.ijssn.20231101.12}, url = {https://doi.org/10.11648/j.ijssn.20231101.12}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijssn.20231101.12}, abstract = {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.}, year = {2023} }
TY - JOUR T1 - Virtual Reality as Assessment Tool of the Risk of Falls in the Elderly AU - Fabien Clanché AU - Gabin Personeni AU - Alexandre Renaux AU - Frédéric Muhla AU - Thierry Bastogne AU - Gérome Gauchard Y1 - 2023/06/27 PY - 2023 N1 - https://doi.org/10.11648/j.ijssn.20231101.12 DO - 10.11648/j.ijssn.20231101.12 T2 - International Journal of Sensors and Sensor Networks JF - International Journal of Sensors and Sensor Networks JO - International Journal of Sensors and Sensor Networks SP - 11 EP - 17 PB - Science Publishing Group SN - 2329-1788 UR - https://doi.org/10.11648/j.ijssn.20231101.12 AB - 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. VL - 11 IS - 1 ER -