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Gait Phase Detection of Stair Ambulation using Inertial Measurement of Lower Limb

thesis
posted on 30.09.2021, 03:10 by MICHAEL STANLEY
Accurate and timely detection is a crucial component in the operation of wearable assistive devices. Stair climbing is an activity with fewer investigation than level walking, yet a crucial and physically more demanding gait in daily life. This thesis develops an adaptive approach in determining the gait phases of stair climbing in real-time. It is tested on healthy individuals, and its performance is compared to machine learning approaches commonly used in literature.

History

Principal supervisor

Chao Chen

Year of Award

2021

Department, School or Centre

Mechanical and Aerospace Engineering

Course

Doctor of Philosophy

Degree Type

DOCTORATE

Faculty

Faculty of Engineering

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