Vowel Recognition Based on Surface Electromyography with Electrode Grid on Submental Region

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  • KUBO Takatomi
    Graduate School of Information Science, Nara Institute of Science and Technology
  • TODA Tomoki
    Graduate School of Information Science, Nara Institute of Science and Technology
  • YOSHIDA Masaki
    Faculty of Biomedical Engineering, Osaka Electro-Communication University
  • HATTORI Takumu
    The Hyogo Institute of Assistive Technology
  • IKEDA Kazushi
    Graduate School of Information Science, Nara Institute of Science and Technology

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説明

This paper proposes the use of electrode grid for Japanese vowel recognition based on surface electromyography (sEMG). Previous studies have indicated the potential effectiveness of sEMG-based speech recognition, not only for healthy people, but also for dysarthric patients. In these studies, however, disc electrodes or parallel bar electrodes were used and located empirically, although there exist relatively small muscles in proximity to each other in the face or neck region. In order to avoid missing out information about speech, we examined the effectiveness of using an electrode grid, which consists of densely-spaced multielectrodes. In our experiments, we measured sEMG signals from the submental region with the electrode grid during the production of 5 vowel sounds. Continuous hidden Markov models were applied to the sEMG signals for vowel recognition. We compared the recognition accuracies between the two methods: One was based on signals from all channels and the other was based on virtually reconstructed single bipolar signal. The former achieved considerably higher recognition accuracy than the latter. This result indicates that using electrode grid is more effective in extracting information for sEMG-based speech recognition.

収録刊行物

  • 生体医工学

    生体医工学 50 (1), 38-46, 2012

    公益社団法人 日本生体医工学会

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