Slip-induced fall-risk assessment based on regular gait pattern in older adults |
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| Institution: | 1. Department of Orthopedic Surgery, Bayreuth Hospital, Bayreuth, Bavaria, Germany;2. Department of Neurology, Bayreuth Hospital, Bayreuth, Bavaria, Germany;3. Sport and Exercise Science Research Centre, School of Applied Sciences, London South Bank University, London, United Kingdom;1. Department of Kinesiology, University of Texas at El Paso, El Paso, TX 79968, USA;2. Department of Radiation Oncology University of Miami School of Medicine, Miami, FL 33136, USA;1. School of Psychology, College of Life & Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK;2. Institute of Sport & Exercise Science, University of Worcester, Henwick Grove, Worcester WR2 6AJ, UK;3. Faculty of Health & Sport Sciences, University of Agder, Kristiansand, Norway;4. PA Consulting Group Ltd., Cambridge Technology Centre, Melbourn, Herts. SG8 6DP, UK;5. Research Institute for Sport & Exercise Sciences, Liverpool John Moores University, Liverpool, UK;1. Department of Mechanical Engineering, University of Alberta, Donadeo Innovation Centre for Engineering, Edmonton, Alberta T6G 1H9, Canada;2. Department of Medicine, University of Alberta, Katz Group Centre, Edmonton, Alberta T6G 2E1, Canada;3. Glenrose Rehabilitation Hospital, Alberta Health Services, 10230 – 111 Avenue NW, Edmonton, Alberta T5G 0B7, Canada;1. Institute of Biomechanics and Orthopaedics, German Sport University Cologne, Am Sportpark Müngersdorf 6, 50933 Cologne, Germany;2. Department of Training and Movement Sciences, Humboldt-University of Berlin, Germany;3. Faculty of Mathematics and Technology, University of Applied Sciences Koblenz, RheinAhrCampus Remagen, Germany;1. Sport and Exercise Science Research Centre, School of Applied Sciences, London South Bank University, London, United Kingdom;2. Centre of Sport and Regenerative Medicine, LANS Medicum, Hamburg, Germany;3. Institute of Biomechanics and Orthopaedics, German Sport University Cologne, Cologne, Germany |
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| Abstract: | Aging-associated fall-risk assessment is crucial for fall prevention. Thus, this study aimed to develop a prognostic model to predict fall-risk following an unexpected over-ground slip perturbation based on normal gait pattern in healthy older adults. 112 healthy older adults who experienced a novel slip in a safe laboratory environment were included. Their slip trial and natural walking trial immediately prior to it were analyzed. To identify the best fall-risk predictive model, gait related variables including step length, segment angles, center of mass state, and ground reaction force (GRF) were determined and inputted into a stepwise logistic regression. The optimal slip-induced fall prediction model was based on the right thigh angle at slipping foot touchdown (TD), the maximum GRF of the slipping limb after TD, and the momentum change from TD to recovery foot liftoff (LO), with an overall prediction accuracy of 75.9%, predicting 74.5% of falls (sensitivity) and 77.2% of recoveries (specificity). Conversely, a model based on clinical and demographic measures predicted 78.2% of falls and 47.4% of recoveries, resulting in a much lower overall accuracy of 62.5%. The fall-risk model based on normal gait pattern which was developed for slip-induced perturbations in healthy older adults was able to provide a high predictive accuracy. This information could provide insight about the ideal normal gait measures which could be used to contribute towards development of therapeutic strategies related to dynamic balance and fall prevention to enhance preventive interventions in populations with high-risk for slip-induced falls. |
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| Keywords: | Fall-risk Slip Fall prediction model Gait pattern |
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