Mobility-related Indicators of Ageing in Late Adulthood: A Neural Network Analysis (67342)

Session Information: Aging and Gerontology
Session Chair: Yiqi Wangliu

Monday, 3 April 2023 09:00
Session: Session 1
Room: Room B (Live Stream)
Presentation Type:Live-Stream Presentation

All presentation times are UTC + 9 (Asia/Tokyo)

Mobility and gait performance have been characterised as indicators of functional declines in older adults and are associated with increased frailty and risk of falls. In addition, an active lifestyle has positive effects on healthy ageing. The aim of this study was to examine the roles of mobility-related parameters and physical activity as predictors of the ageing process in late adulthood through a neural network analysis method. Fifty-five active and sedentary older adults (71.96±5.67 yrs) formed the sample and were divided into two age groups (65-74yrs and 75-85yrs). All participants completed a Timed Up and Go test (TUG) as well as a 2min self-paced straight-line walking task. Gait-related variables were 10m walking speed, cadence (step/min), interlimb coordination, swing time asymmetry and variability in stride and double-support times. A multilayer perceptron neural network analysis method was used to estimate the importance of mobility-related parameters associated with ageing. The model produced good accuracy (Error=1.52, correct prediction=81.8%) and sensitivity (0.75) to predict age groups. The most important mobility-related parameters were walking cadence (100%), stride time variability (94%), physical activity (67%), TUG (55%) and double-support time variability (50%). In conclusion, these findings suggest that in late adulthood, the mobility-related indicators of ageing are multidimensional and the changes in gait timing, gait variability, functional performance and lifestyle should be emphasised in intervention design for healthy ageing.

Mohsen Shafizadeh, Sheffield Hallam University, United Kingdom
Andrew Barnes, Sheffield Hallam University, United Kingdom
Stuart Bonner, Sheffield Hallam University, United Kingdom
Shahab Parvinpour, The University of Kharazmy, Iran
Jonathan Fraser, Sheffield Hallam University, United Kingdom

About the Presenter(s)
Dr Mohsen Shafizadeh teaches motor control and movement analysis on the sport and exercise science-related degrees. Current research interests include ageing, disabilities, physical activity and cognitive-motor functions.

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Posted by Clive Staples Lewis

Last updated: 2023-02-23 23:45:00