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Recognition of hand gestures with different prior postures using EMG signals

  • Journal of Internet of Things and Convergence
  • Abbr : JKIOTS
  • 2023, 9(6), pp.1-6
  • Publisher : The Korea Internet of Things Society
  • Research Area : Engineering > Computer Science > Internet Information Processing
  • Received : September 20, 2023
  • Accepted : November 20, 2023
  • Published : December 29, 2023

Hyun-Tae Choi 1 Deok-Hwa Kim 1 Won-Du Chang 1

1부경대학교

Accredited

ABSTRACT

Hand gesture recognition is an essential technology for the people who have difficulties using spoken language to communicate. Electromyogram (EMG), which is often utilized for hand gesture recognition, is expected to have difficulties in hand gesture recognition because its people's movements varies depending on prior postures, but the study on this subject is rare. In this study, we conducted tests to confirm if the prior postures affect on the accuracy of gesture recognition. Data were recorded from 20 subjects with different prior postures. We achieved average accuracies of 89.6% and 52.65% when the prior states between the training and test data were unique and different, respectively. The accuracy was increased when both prior states were considered, which confirmed the need to consider a variety of prior states in hand gesture recognition with EMG.

Citation status

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