Myoelectric control has been traditionally used in clinical applications, but from recently, there has been an increasing interest in applying this approach for more general human-machine interfacing. Here, we present NeuraLoop, a compact system for the simultaneous recording of electrical muscle activity (EMG) and delivery of electrotactile stimulation. The system uses a matrix electrode with 32 stimulation and 32 recording pads, thereby allowing high- resolution EMG recording for gesture recognition and spatially distributed stimulation for high-fidelity haptic feedback. We demonstrated the system by using NeuraLoop to detect and classify micro-gestures, which are quick, small, and transient movements, often used to interact with consumer devices. The preliminary results are encouraging although there is room for improvement. Future work will increase gesture classification performance and add haptic feedback, opening opportunities for many relevant applications of bidirectional human-machine interfacing using gesture recognition and electrotactile haptics.

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NeuraLoop: A System for Bidirectional High-Bandwidth Interfacing Using Myoelectric Signals and Electrotactile Feedback

  • Strahinja Dosen,
  • Hans Henrik Dalgaard,
  • Alice Ghislaine Colette Rey,
  • Elias Thomassen Dam,
  • Nikola Jorgovanovic,
  • Matija Strbac,
  • Luis Pelaez Murciego,
  • Erika Geraldina Spaich

摘要

Myoelectric control has been traditionally used in clinical applications, but from recently, there has been an increasing interest in applying this approach for more general human-machine interfacing. Here, we present NeuraLoop, a compact system for the simultaneous recording of electrical muscle activity (EMG) and delivery of electrotactile stimulation. The system uses a matrix electrode with 32 stimulation and 32 recording pads, thereby allowing high- resolution EMG recording for gesture recognition and spatially distributed stimulation for high-fidelity haptic feedback. We demonstrated the system by using NeuraLoop to detect and classify micro-gestures, which are quick, small, and transient movements, often used to interact with consumer devices. The preliminary results are encouraging although there is room for improvement. Future work will increase gesture classification performance and add haptic feedback, opening opportunities for many relevant applications of bidirectional human-machine interfacing using gesture recognition and electrotactile haptics.