Hand posture and gesture recognition using MYO armband and spectral collaborative representation based classification

Ali Boyali, Naohisa Hashimoto, Osamu Matsumoto

Research output: Chapter in Book/Report/Conference proceedingConference contribution

30 Citations (Scopus)

Abstract

In this paper, we propose the use of Collaborative based Representation in Spectral Domain to recognize the postures and gestures from the Electromyography (EMG) recordings acquired by a recently introduced sensor; Thalmic Labs' MYO armband. The recognition accuracy obtained for a set of six hand gestures and postures is promising with an accuracy over 97 % which is a competent result in the related literature. The algorithms are developed for creating an intuitive human machine interface for navigating a robotic wheelchair.

Original languageEnglish
Title of host publication2015 IEEE 4th Global Conference on Consumer Electronics, GCCE 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages200-201
Number of pages2
ISBN (Electronic)9781479987511
DOIs
Publication statusPublished - 2016 Feb 3
Externally publishedYes
Event4th IEEE Global Conference on Consumer Electronics, GCCE 2015 - Osaka, Japan
Duration: 2015 Oct 272015 Oct 30

Publication series

Name2015 IEEE 4th Global Conference on Consumer Electronics, GCCE 2015

Other

Other4th IEEE Global Conference on Consumer Electronics, GCCE 2015
Country/TerritoryJapan
CityOsaka
Period15/10/2715/10/30

Keywords

  • Collaborative based Classification
  • EMG gesture recognition
  • MYO armband

ASJC Scopus subject areas

  • Instrumentation
  • Biotechnology
  • Computer Networks and Communications
  • Signal Processing
  • Electrical and Electronic Engineering

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