A brain-controlled switch for asynchronous control applications

Asynchronous control applications are an important class of application that has not received much attention from the brain-computer interface (BCI) community. This work provides a design for an asynchronous BCI switch and performs the first extensive evaluation of an asynchronous device in attentiv...

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Bibliographic Details
Published in:IEEE transactions on biomedical engineering 2000-10, Vol.47 (10), p.1297-1307
Main Authors: Mason, S.G., Birch, G.E.
Format: Article
Language:English
Subjects:
Adult
Algorithms
Biological and medical sciences
Brain
Brain computer interfaces
Communication Aids for Disabled
Electrodes
Electrodiagnosis. Electric activity recording
Electroencephalography
Electroencephalography - instrumentation
Equipment Design
Error analysis
Frequency
Human computer interaction
Humans
Investigative techniques, diagnostic techniques (general aspects)
Male
Medical sciences
Miscellaneous. Technology
Motor Cortex - physiology
Performance evaluation
Prototypes
ROC Curve
Signal design
Signal Processing, Computer-Assisted - instrumentation
Studies
Switches
User-Computer Interface
Variable speed drives
Wavelet analysis
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Summary:Asynchronous control applications are an important class of application that has not received much attention from the brain-computer interface (BCI) community. This work provides a design for an asynchronous BCI switch and performs the first extensive evaluation of an asynchronous device in attentive, spontaneous electroencephalographic (EEG) signals. The switch design [named the low-frequency asynchronous switch design (LF-ASD)] is based on a new feature set related to imaginary movements in the 1-4 Hz frequency range. This new feature set was identified from a unique analysis of EEG using a bi-scale wavelet. Offline evaluations of a prototype switch demonstrated hit (true positive) rates in the range of 38%-81% with corresponding false positive rates in the range of 0.3%-11.6%. The performance of the LF-ASD was contrasted with two other ASDs: one based on mu-power features and another based on the outlier processing method (OPM) algorithm. The minimum mean error rates for the LF-ASD were shown to be significantly lower than either of these other two switch designs.
ISSN:0018-9294
1558-2531
DOI:10.1109/10.871402