Low complexity real time BCI for stroke rehabilitation

Tsung Pen Chou, Wan Ru Wang, Tian-Sheuan Chang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Stroke rehabilitation with EEG-based brain computer interface enables interaction within injury neurons and restoration of original functions in motor area of brain. However, many approaches usually require high complexity for reliable detection and result in achieving real time computation difficultly. This study proposes a real time low complexity BCI interface for stroke rehabilitation, which is based on Filter-Bank Common Spatial Pattern (FBCSP) method. For reducing complexity purpose, EEG channels (electrodes) are reduced from 19 channels to 4 channels which are Fz, C3, Cz, and C4. Furthermore, the filter bank is reduced from five bands to three bands which are 4-7Hz, 8-12Hz, and 13-30Hz. We also develop a real time scheme by using one-second timing window for EEG analysis and adaptive algorithm to fit time-varying EEG. This approach not only reduces 87% computational complexity but also shows over 80% accuracy for offline analysis and 68% accuracy for online implementation within one-second response time.

Original languageEnglish
Title of host publication2015 IEEE International Conference on Digital Signal Processing, DSP 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages809-812
Number of pages4
ISBN (Electronic)9781479980581, 9781479980581
DOIs
StatePublished - 9 Sep 2015
EventIEEE International Conference on Digital Signal Processing, DSP 2015 - Singapore, Singapore
Duration: 21 Jul 201524 Jul 2015

Publication series

NameInternational Conference on Digital Signal Processing, DSP
Volume2015-September

Conference

ConferenceIEEE International Conference on Digital Signal Processing, DSP 2015
CountrySingapore
CitySingapore
Period21/07/1524/07/15

Keywords

  • BCI
  • FBCSP
  • Low complexity
  • Real time
  • Stroke rehabilitation

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