Das, Koel and Rizzuto, Daniel S. and Nenadic, Zoran (2009) Mental state estimation for brain-computer interfaces. IEEE Transactions on Biomedical Engineering, 56 (8). pp. 2114-2122. ISSN 0018-9294 http://resolver.caltech.edu/CaltechAUTHORS:20090812-114159458
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Mental state estimation is potentially useful for the development of asynchronous brain-computer interfaces. In this study, four mental states have been identified and decoded from the electrocorticograms (ECoGs) of six epileptic patients, engaged in a memory reach task. A novel signal analysis technique has been applied to high-dimensional, statistically sparse ECoGs recorded by a large number of electrodes. The strength of the proposed technique lies in its ability to jointly extract spatial and temporal patterns, responsible for encoding mental state differences. As such, the technique offers a systematic way of analyzing the spatiotemporal aspects of brain information processing and may be applicable to a wide range of spatiotemporal neurophysiological signals.
|Additional Information:||© Copyright 2009 IEEE. Manuscript received March 6, 2008; revised September 16, 2008 and January 20, 2009. First published May 19, 2009; current version published July 15, 2009. The authors would like to acknowledge the anonymous reviewers and the editorial staff of this journal.|
|Subject Keywords:||Brain--computer interfaces (BCIs); classification; curse of dimensionality; electrocorticograms (ECoGs); feature extraction; mental states; small sample size problem. Controlled Indexing: bioelectric phenomena; biomedical electrodes; biomedical electronics; brain; brain-computer interfaces; decoding feature extraction; medical disorders; medical signal processing; neurophysiology; patient diagnosis; spatiotemporal phenomena; statistical analysis. Non-controlled Indexing: asynchronous brain-computer interface; brain information processing; brain mental state estimation; electrocorticogram electrode decoding; epileptic patient neurophysiological memory reach task; signal analysis technique; signal temporal pattern extraction; spatiotemporal neurophysiological signal; statistically sparse ECoG recording.|
|Usage Policy:||No commercial reproduction, distribution, display or performance rights in this work are provided.|
|Deposited By:||Jason Perez|
|Deposited On:||12 Aug 2009 21:33|
|Last Modified:||26 Dec 2012 11:11|
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