The brain computer interface using flash visual evoked potential and independent component analysis

Po Lei Lee*, Jen Chuen Hsieh, Chi Hsun Wu, Kuo Kai Shyu, Shyan Shiou Chen, Tzu Chen Yeh, Yu Te Wu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

41 Citations (Scopus)

Abstract

In this study flashing stimuli such as digits or letters are displayed on a LCD screen to induce flash visual evoked potentials (FVEPs). The aim of the proposed interface is to generate desired strings while one stares at target stimulus one after one. To effectively extract visually-induced neural activities with superior signal-to-noise ratio independent component analysis (ICA) is employed to decompose the measured EEG and task-related components are subsequently selected for data reconstruction. In addition all the flickering sequences are designed to be mutually independent in order to remove the contamination induced by surrounding non-target stimuli from the ICA-recovered signals. Since FVEPs are time-locked and phase-locked to flash onsets of gazed stimulus segmented epochs from ICA-recovered signals based on flash onsets of gazed stimulus will be sharpen after averaging whereas those based on flash onsets of non-gazed stimuli will be suppressed after averaging. The stimulus inducing the largest averaged FVEPs is identified as the gazed target and corresponding digit or letter is sent out. Five subjects were asked to gaze at each stimulus. The mean detection accuracy resulted from averaging 15 epochs was 99.7%. Another experiment was to generate a specified string '0287513694E'. The mean accuracy and information transfer rates were 83% and 23.06 bits/min respectively.

Original languageEnglish
Pages (from-to)1641-1654
Number of pages14
JournalAnnals of Biomedical Engineering
Volume34
Issue number10
DOIs
Publication statusPublished - 2006 Oct
Externally publishedYes

Keywords

  • Brain computer interface (BCI)
  • Electroencephalography (EEG)
  • Flash visual evoked potential (FVEP)
  • Independent component analysis (ICA)

ASJC Scopus subject areas

  • Biomedical Engineering

Fingerprint

Dive into the research topics of 'The brain computer interface using flash visual evoked potential and independent component analysis'. Together they form a unique fingerprint.

Cite this