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Lower Body Gait Kinematics Estimation Using Foot Kinetics

thesis
posted on 13.03.2020, 07:34 by SAAVEETHYA SIVAKUMAR
This research proposes a Wavelet Neural Network based lower body joint angle estimation protocol using foot kinetics. The project reduces reliance on multiple body-mounted sensors and sets a future trend for gait monitoring. This is achieved through feature extraction of Ground Reaction Forces of primary gait events. Users will be able to acquire a full lower body kinematics profile by only using foot kinetics of preliminary gait events. The estimation model is a fast and easy tool, that is beneficial for clinicians to monitor gait in outdoor environments on daily basis to identify and monitor gait disorders.

History

Campus location

Malaysia

Principal supervisor

Alpha Agape Gopalai

Additional supervisor 1

Darwin Gouwanda

Additional supervisor 2

King Hann Lim

Year of Award

2020

Department, School or Centre

School of Engineering (Monash University Malaysia)

Course

Doctor of Philosophy

Degree Type

DOCTORATE

Exports