Human Gait Pattern Analysis and Modelling


M. Palaniswami;
Post Doctoral Research Fellow: Ahsan Khandoker, Daniel T. H. Lai, Slaven Marusic.

Student: Chandan Karmakar.

Rezaul Begg, Victoria University.

Introduction: Understanding the underlying mechanisms and associated deficits in movement dynamics across the lifespan and the effects of pathological conditions, such as falls, will lead to many applications in the design and evaluation of diagnostic and assessment methods for human movement.
Significance: Falls and injuries during walking in older adults are a major public health issue and cost Australia $498million pa; these costs are projected to triple by 2051 if falls rates remain unchanged (Moller, 2003). But they may be preventable if risk factors can be identified.
Applications: The developed methods may be used to assess age-related decline in gait control, the associated risk of sustaining a fall, and determining the effects of exercise interventions and treatments.
Challenges: This project addresses specific research questions: RQ1: What are the key features and variability indices (statistical and nonlinear, e.g., Poincare plots, Approximate entropy, Detrended Fluctuation Analysis, wavelet based fractal correlations etc) that characterise dynamic steady-state control during locomotion? RQ2: How are these features and indices influenced by more challenging gait tasks, such as walking on inclined surfaces? RQ3: How do gait variability and control mechanisms change due to ageing and pathology, for example falling behaviour?
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