Literature DB >> 15188869

Brain-computer interface design for asynchronous control applications: improvements to the LF-ASD asynchronous brain switch.

Jaimie F Borisoff1, Steve G Mason, Ali Bashashati, Gary E Birch.   

Abstract

The low-frequency asynchronous switch design (LF-ASD) was introduced as a direct brain-computer interface (BCI) technology for asynchronous control applications. The LF-ASD operates as an asynchronous brain switch (ABS) which is activated only when a user intends control and maintains an inactive state output when the user is not meaning to control the device (i.e., they may be idle, thinking about a problem, or performing some other action). Results from LF-ASD evaluations have shown promise, although the reported error rates are too high for most practical applications. This paper presents the evaluation of four new LF-ASD designs with data collected from individuals with high-level spinal cord injuries and able-bodied subjects. These new designs incorporated electroencephalographic energy normalization and feature space dimensionality reduction. The error characteristics of the new ABS designs were significantly better than the LF-ASD design with true positive rate increases of approximately 33% for false positive rates in the range of 1%-2%. The results demonstrate that the dimensionality of the LF-ASD feature space can be reduced without performance degradation. The results also confirm previous findings that spinal cord-injured subjects can operate ABS designs to the same ability as able-bodied subjects.

Entities:  

Mesh:

Year:  2004        PMID: 15188869     DOI: 10.1109/TBME.2004.827078

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  16 in total

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5.  The point of no return in vetoing self-initiated movements.

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6.  Decoding onset and direction of movements using Electrocorticographic (ECoG) signals in humans.

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7.  Self-paced (asynchronous) BCI control of a wheelchair in virtual environments: a case study with a tetraplegic.

Authors:  Robert Leeb; Doron Friedman; Gernot R Müller-Putz; Reinhold Scherer; Mel Slater; Gert Pfurtscheller
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8.  Automatic artefact removal in a self-paced hybrid brain- computer interface system.

Authors:  Xinyi Yong; Mehrdad Fatourechi; Rabab K Ward; Gary E Birch
Journal:  J Neuroeng Rehabil       Date:  2012-07-27       Impact factor: 4.262

9.  Application of a hybrid wavelet feature selection method in the design of a self-paced brain interface system.

Authors:  Mehrdad Fatourechi; Gary E Birch; Rabab K Ward
Journal:  J Neuroeng Rehabil       Date:  2007-04-30       Impact factor: 4.262

10.  Towards development of a 3-state self-paced brain-computer interface.

Authors:  Ali Bashashati; Rabab K Ward; Gary E Birch
Journal:  Comput Intell Neurosci       Date:  2007
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