Implementation of a control system for a power wheelchair with induction of a β/α ratio by visual feedback

Yudai Iida, Ryota Horie

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

1 Citation (Scopus)

Abstract

Techniques using electroencephalography (EEG)-based brain computer interfaces (BCIs) have been developed and are eagerly anticipated as novel interfaces for controlling power wheelchairs. In addition to the BCIs, smart glass technology has been developed. In our previous study, we propose a prototype of an intuitive control system for a power wheelchair; this system comprises a simple EEG recorder, smart glass, and a microcomputer. Using this system, the power wheelchair moves straight ahead when a user concentrates, stops when the user blinks, and turns left or right when the user tilt his/her neck to the left or right, respectively. A β/α ratio as an indicator of the concentration and blinks are detected from raw EEG waves, and the tilting of the neck is detected by acceleration sensors in the smart glass. In this study, we proposed a new control system which display the visual feedback of the β/α ratio on the smart glass to induce user's concentration. Our results show that during the experiment, the system successfully worked and induced for the β/α ratio in specific concentrating states.

Original languageEnglish
Title of host publication2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4772-4775
Number of pages4
Volume2016-October
ISBN (Electronic)9781457702204
DOIs
Publication statusPublished - 2016 Oct 13
Event38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 - Orlando, United States
Duration: 2016 Aug 162016 Aug 20

Other

Other38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
Country/TerritoryUnited States
CityOrlando
Period16/8/1616/8/20

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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