Real-time embedded EEG-based brain-computer interface

Li-Wei Ko*, I. Ling Tsai, Fu Shu Yang, Jen Feng Chung, Shao Wei Lu, Tzyy Ping Jung, Chin-Teng Lin

*Corresponding author for this work

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

5 Scopus citations


Online artifact rejection, feature extraction, and pattern recognition are essential to advance the Brain Computer Interface (BCI) technology so as to be practical for real-world applications. The goals of BCI system should be a small size, rugged, lightweight, and have low power consumption to meet the requirements of wearability, portability, and durability. This study proposes and implements a moving-windowed Independent Component Analysis (ICA) on a battery-powered, miniature, embedded BCI. This study also tests the embedded BCI on simulated and real EEG signals. Experimental results indicated that the efficacy of the online ICA decomposition is comparable with that of the offline version of the same algorithm, suggesting the feasibility of ICA for online analysis of EEG in a BCI. To demonstrate the feasibility of the wearable embedded BCI, this study also implements an online spectral analysis to the resultant component activations to continuously estimate subject's task performance in near real time.

Original languageEnglish
Title of host publicationAdvances in Neuro-Information Processing - 15th International Conference, ICONIP 2008, Revised Selected Papers
Number of pages8
EditionPART 2
StatePublished - 21 Sep 2009
Event15th International Conference on Neuro-Information Processing, ICONIP 2008 - Auckland, New Zealand
Duration: 25 Nov 200828 Nov 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume5507 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference15th International Conference on Neuro-Information Processing, ICONIP 2008
CountryNew Zealand

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