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EEG Analysis of Imagined Speech

EEG Analysis of Imagined Speech

Sadaf Iqbal, Muhammed Shanir P.P., Yusuf Uzzaman Khan, Omar Farooq
Copyright: © 2020 |Pages: 14
ISBN13: 9781522592730|ISBN10: 1522592733|EISBN13: 9781522592747
DOI: 10.4018/978-1-5225-9273-0.ch033
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MLA

Iqbal, Sadaf, et al. "EEG Analysis of Imagined Speech." Disruptive Technology: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2020, pp. 679-692. https://doi.org/10.4018/978-1-5225-9273-0.ch033

APA

Iqbal, S., Shanir P.P., M., Khan, Y. U., & Farooq, O. (2020). EEG Analysis of Imagined Speech. In I. Management Association (Ed.), Disruptive Technology: Concepts, Methodologies, Tools, and Applications (pp. 679-692). IGI Global. https://doi.org/10.4018/978-1-5225-9273-0.ch033

Chicago

Iqbal, Sadaf, et al. "EEG Analysis of Imagined Speech." In Disruptive Technology: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 679-692. Hershey, PA: IGI Global, 2020. https://doi.org/10.4018/978-1-5225-9273-0.ch033

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Abstract

Scalp electroencephalogram (EEG) is one of the most commonly used methods to acquire EEG data for brain-computer interfaces (BCIs). Worldwide a large number of people suffer from disabilities which impair normal communication. Communication BCIs are an excellent tool which helps the affected patients communicate with others. In this paper scalp EEG data is analysed to discriminate between the imagined vowel sounds /a/, /u/ and no action or rest as control state. Mean absolute deviation (MAD) and Arithmetic mean are used as features to classify data into one of the classes /a/, /u/ or rest. With high classification accuracies of 87.5-100% for two class problem and 78.33-96.67% for three class problem that have been obtained in this work, this algorithm can be used in communication BCIs, to develop speech prosthesis and in synthetic telepathy systems.

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