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A hybrid BCI-based environmental control system using SSVEP and EMG signals

  • Xiaoke Chai*
  • , Zhimin Zhang
  • , Yangting Lu
  • , Guitong Liu
  • , Tengyu Zhang
  • , Haijun Niu
  • *Corresponding author for this work
  • Beihang University
  • National Research Center for Rehabilitation Technical Aids

Research output: Contribution to journalConference articlepeer-review

Abstract

The paper developed a hybrid Brain–computer interface (hBCI) home environmental control system for paralytics’ active and assisted living, by integrating single channel Electromyography (EMG) of occlusal movement and steady state visual evoked potentials (SSVEP). The system was designed as three-level interface, besides the idle state interface, for work state there are one main interface and five sub-interfaces. The main interface included five visual stimulus corresponding to different devices such as nursing bed, wheelchair, telephone, television and lamps, the sub-interfaces present control function of those devices. Gazing at stimuli at different frequencies corresponding to a certain function can select a device or device action. Several particular occlusal patterns respectively are used to confirm the selected function, return from sub-interface to main interface and switch on/off the system. Ten healthy subjects without any training completed the virtual system verification experiment, the averaged target selection accuracy based on SSVEP achieved 96.3%. Moreover with a simple clench action for target confirmation, the false positive rate was minimized to zero, which improved the control accuracy. This indicated that Combining SSVEP and EMG can effectively enhance the security and interactivity of the environmental control system.

Original languageEnglish
Pages (from-to)59-63
Number of pages5
JournalIFMBE Proceedings
Volume68
Issue number3
DOIs
StatePublished - 2019
EventWorld Congress on Medical Physics and Biomedical Engineering, WC 2018 - Prague, Czech Republic
Duration: 3 Jun 20188 Jun 2018

Keywords

  • Electromyography (EMG)
  • Environmental control
  • Hybrid brain computer interface
  • Paralytics
  • Steady state visual evoked potential (SSVEP)

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