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Interpreting Brain Waves

Interpreting Brain Waves

Noran Magdy El-Kafrawy, Doaa Hegazy, Mohamed F. Tolba
Copyright: © 2017 |Pages: 20
ISBN13: 9781522522294|ISBN10: 1522522298|EISBN13: 9781522522300
DOI: 10.4018/978-1-5225-2229-4.ch030
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MLA

El-Kafrawy, Noran Magdy, et al. "Interpreting Brain Waves." Handbook of Research on Machine Learning Innovations and Trends, edited by Aboul Ella Hassanien and Tarek Gaber, IGI Global, 2017, pp. 695-714. https://doi.org/10.4018/978-1-5225-2229-4.ch030

APA

El-Kafrawy, N. M., Hegazy, D., & Tolba, M. F. (2017). Interpreting Brain Waves. In A. Hassanien & T. Gaber (Eds.), Handbook of Research on Machine Learning Innovations and Trends (pp. 695-714). IGI Global. https://doi.org/10.4018/978-1-5225-2229-4.ch030

Chicago

El-Kafrawy, Noran Magdy, Doaa Hegazy, and Mohamed F. Tolba. "Interpreting Brain Waves." In Handbook of Research on Machine Learning Innovations and Trends, edited by Aboul Ella Hassanien and Tarek Gaber, 695-714. Hershey, PA: IGI Global, 2017. https://doi.org/10.4018/978-1-5225-2229-4.ch030

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Abstract

BCI (Brain-Computer Interface) gives you the power to manipulate things around you just by thinking of what you want to do. It allows your thoughts to be interpreted by the computer and hence act upon it. This could be utilized in helping disabled people, remote controlling of robots or even getting personalized systems depending upon your mood. The most important part of any BCI application is interpreting the brain signalsasthere are many mental tasks to be considered. In this chapter, the authors focus on interpreting motor imagery tasks and more specifically, imagining left hand, right hand, foot and tongue. Interpreting the signal consists of two main steps: feature extraction and classification. For the feature extraction,Empirical Mode Decomposition (EMD) was used and for the classification,the Support Vector Machine (SVM) with Radial Basis Function (RBF) kernel was used. The authors evaluated this system using the BCI competition IV dataset and reached a very promising accuracy.

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