Gait trajectory prediction via extreme learning machine

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Gait trajectory prediction via extreme learning machine

In this thesis, an algorithm to estimate the gait trajectory based upon the electromyography (EMG) signal is proposed. The algorithm is developed using Extreme Learning Machine (ELM). Experiments were conducted to acquire the gait parameters from 20 healthy human subjects. EMG signals from Tibialis...

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Bibliographic Details
Main Author:	Lim, Han Leong
Format:	Thesis (University of Nottingham only)
Language:	English
Published:	2021
Subjects:	gait trajectory electromyography signal extreme learning machine architecture artificial neural network machine learning
Online Access:	https://eprints.nottingham.ac.uk/63929/

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