Estimating cognitive state using EEG signals

Tian Lan, Andre Adami, Deniz Erdogmus, Misha Pavel

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

4 Scopus citations


Using EEG signals to estimate cognitive state has drawn increasing attention in recently years, especially in the context of brain-computer interface (BCI) design. However, this goal is extremely difficult because, in addition to the complex relationships between the cognitive state and EEG signals that yields the non-stationarity of the features extracted from EEG signals, there are artefacts introduced by eye blinks and head and body motion. In this paper, we present a classification system, which can estimate the subject's cognitive state from the measured EEG signals. In the proposed system, a mutual information based method is employed to reduce the dimensionality of the features as well as to increase the robustness of the system. A committee of three classifiers was implemented and the majority voting results of the committee are taken to be the final decisions. The results of a preliminary test with data from freely moving subjects performing various tasks as opposed to the strictly controlled experimental set-ups of BCI provide strong support for this approach.

Original languageEnglish (US)
Title of host publication13th European Signal Processing Conference, EUSIPCO 2005
Number of pages4
StatePublished - 2005
Externally publishedYes
Event13th European Signal Processing Conference, EUSIPCO 2005 - Antalya, Turkey
Duration: Sep 4 2005Sep 8 2005

Publication series

Name13th European Signal Processing Conference, EUSIPCO 2005


Other13th European Signal Processing Conference, EUSIPCO 2005

ASJC Scopus subject areas

  • Signal Processing


Dive into the research topics of 'Estimating cognitive state using EEG signals'. Together they form a unique fingerprint.

Cite this