Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Control of a Virtual Hand Using a Brain-Computer Interface System

Control of a Virtual Hand Using a Brain-Computer Interface System

Aziz, Nida

Paperback

Technology & Engineering

ISBN10: 384430441X
ISBN13: 9783844304411
Publisher: Lap Lambert Academic Pub
Published: Feb 1 2011
Pages: 104
Weight: 0.36
Height: 0.25 Width: 6.00 Depth: 9.00
Language: English
An Asynchronous BCI was designed using non-cue based data collected from several participants in two separate sessions with different protocols. Several different features were extracted and evaluated using the DBI and the best of these, the joint time- frequency (JTF) feature, was chosen for detecting onset and classifying mental tasks. For onset detection, two different methods were employed and compared on the basis of classification performance obtained from confusion matrices, repeatability and ease of application. Different classifiers were tested for onset detection of which Linear Discriminant Analysis (LDA) classifier showed better results. The classified onset using JTF features and LDA classifier was then used to select the active period data in both sessions, which was then sent to the mental task classifier. Mental Task classification was done using Neural Networks, Support Vector Machines and LDA. The performance of the mental task classifier was also evaluated using confusion matrices. A virtual hand was developed graphically in MATLAB and was programmed to move in 6 different directions according to the classified outputs.

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