Lower Body Gait Kinematics Estimation Using Foot Kinetics
SAAVEETHYA SIVAKUMAR
10.26180/5e6b3775da070
https://bridges.monash.edu/articles/thesis/Lower_Body_Gait_Kinematics_Estimation_Using_Foot_Kinetics/11980053
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.
2020-03-13 07:34:12
Gait
Kinematics
Kinetics
Artificial Neural Networks
Knowledge Representation and Machine Learning
Artificial Intelligence and Image Processing
Biomechanics
Biomedical Instrumentation
Signal Processing