Since fall has been identified as the number one cause of death and injury of old people, development of technologies for prediction and prevention of falls is highly needed, especially for the aging society. This paper presents a preliminary study of using two indices related to dynamic stability of a human body in standing and walking for the potential application of predicting the risk of falls. The dynamic stability index for standing measures the degree of alignment between the center of mass and the center of pressure of a human body when the human is intended to standing still. The dynamic stability index for walking is derived from the well-known inverted pendulum model of human walking dynamics. The two indices can be easily computed from the test data measured by a 3D motion capture system and an instrumented treadmill. As a pilot study, five older adults who have recent history of falls were tested and another five older regular adults were also tested as a control group. The test data showed that the values of the indices for the two groups are clearly distinguishable. This is a good indication that the proposed indices have a good potential for predicting the risk of falls of older adults. This finding encourages further research along the line.
- Dynamic Systems and Control Division
A Pilot Study of Dynamic Stability Indices for Potential Application of Identifying Older Adult Fallers
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Zhang, L, Ma, O, & Wood, R. "A Pilot Study of Dynamic Stability Indices for Potential Application of Identifying Older Adult Fallers." Proceedings of the ASME 2012 5th Annual Dynamic Systems and Control Conference joint with the JSME 2012 11th Motion and Vibration Conference. Volume 2: Legged Locomotion; Mechatronic Systems; Mechatronics; Mechatronics for Aquatic Environments; MEMS Control; Model Predictive Control; Modeling and Model-Based Control of Advanced IC Engines; Modeling and Simulation; Multi-Agent and Cooperative Systems; Musculoskeletal Dynamic Systems; Nano Systems; Nonlinear Systems; Nonlinear Systems and Control; Optimal Control; Pattern Recognition and Intelligent Systems; Power and Renewable Energy Systems; Powertrain Systems. Fort Lauderdale, Florida, USA. October 17–19, 2012. pp. 1-9. ASME. https://doi.org/10.1115/DSCC2012-MOVIC2012-8562
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