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An EMG signal processing system for control of an ankle-foot orthosis

  • Artur J. Gmerek
  • , Mohammadreza Davoodi
  • , Nader Meskin
  • , Fadi Jaber
  • Department of Electrical Engineering, Qatar University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

This paper presents an electromyographic (EMG)based digital processing system for estimating foot direction of motion and force exerted from muscles of the human lower leg. This information can be used in the control frameworks of ankle-foot orthoses (AFOs). In essence, it is usually necessary to estimate the ankle's muscles voluntary contraction (VC) and user's intention of motion in order to control an AFO in a reliable and effective way. Consequently, a data processing system is developed that can designate these parameters from EMG signals. The voluntary contraction is calculated based on the root mean square (RMS) of EMG signals, and the direction of motion is estimated by using a feature-based classifier. The experiments are performed on five healthy, sitting subjects and the methodology consists of selecting discriminative features and using basic classifiers. The results of this work show that the direction of motion can be estimated in real-time with high accuracy.

Original languageEnglish
Title of host publication2017 4th International Conference on Control, Decision and Information Technologies, CoDIT 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages444-449
Number of pages6
ISBN (Electronic)9781509064656
DOIs
StatePublished - 8 Nov 2017
Externally publishedYes
Event4th International Conference on Control, Decision and Information Technologies, CoDIT 2017 - Barcelona, Spain
Duration: 5 Apr 20177 Apr 2017

Publication series

Name2017 4th International Conference on Control, Decision and Information Technologies, CoDIT 2017
Volume2017-January

Conference

Conference4th International Conference on Control, Decision and Information Technologies, CoDIT 2017
Country/TerritorySpain
CityBarcelona
Period5/04/177/04/17

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