Reducing nonstationary effects on motor imagery BCI using Constant-Q FBCSP

Raheleh Mohammadi, Ali Mahloojifar, DH Coyle

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


Electroencephalogram (EEG) signals used in brain computer interfaces (BCIs) change over time, both within a single session and between sessions. Factors such as change in strategy by the user, sensorimotor learning, user fatigue, small differences in electrode position and muscular activity result in nonstationary EEG dynamics. Dealing with these characteristics when transferring from the calibration to a feedback session is a challenging but critical issue in BCI applications. To cope with this problem, a framework based on constant-Q filter bank Common Spatial Patterns (FBCSP) and Linear Discriminant Analysis (LDA) is proposed. This framework has been applied on dataset IVc from the BCI Competition III. Results show that the proposed method compares favorably with an adaptive framework such as covariate shift adaptation in tackling the nonstationarity in BCIs.
Original languageEnglish
Title of host publicationUnknown Host Publication
PublisherHindawi Publishing Corporation
Number of pages5
Publication statusPublished (in print/issue) - 2012
EventThe 19th Iranian Conference on Biomedical Engineering (ICBME) - Iran
Duration: 1 Jan 2012 → …


ConferenceThe 19th Iranian Conference on Biomedical Engineering (ICBME)
Period1/01/12 → …


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