Walking State Detection from Electromyographic Signals towards the Control of Prosthetic Limbs
Date
2013-09Abstract
This paper presents experiments in the use of an Electromyographic sensor to determine whether a person is standing, walking or running. The output of the sensor was captured and processed in a variety of different ways to extract those features that were seen to be changing as the movement state of the person changed. Experiments were carried out by adjusting the parameters used for the collection of the features. These extracted features where then passed to a set of Artificial Neural Networks trained to recognise each state. This methodology exhibits an accuracy needed to control a prosthetic leg.
Description
Citation : Hardaker, P., Passow, B. N. and Elizondo, D. (2013) Walking State Detection from Electromyographic Signals towards the Control of Prosthetic Limbs. Proceedings of the 13th Annual Workshop on Computational Intelligence' (UKCI'13), Guildford, United Kingdom, 9-11 September 2013.
Research Group : DIGITS
Research Group : Centre for Computational Intelligence
Research Group : Centre for Computational Intelligence
Research Institute : Institute of Artificial Intelligence (IAI)
Peer Reviewed : Yes