EEG signals classifications of motor imagery using adaptive neuro-fuzzy inference system and interval type-2 fuzzy system
by Shereen A. El-aal; Rabie A. Ramadan; Neveen I. Ghali
International Journal of Intelligent Systems Technologies and Applications (IJISTA), Vol. 16, No. 2, 2017

Abstract: Brain computer interface (BCI) techniques are used to help disabled people to translate brain signals to control commands imitating specific human thinking based on electroencephalography (EEG) signal processing. The paper tries to accurately classify motor imagery imagination tasks, e.g., left and right hand movement. The paper utilises different methods for such classification including: (1) adaptive neuro fuzzy inference system (ANFIS); (2) K-nearest neighbour (KNN); (3) linear discriminant analysis (LDA) and (4) interval Type-2 fuzzy system (IT2-FS) classifiers. In addition, with ANFIS approach, different clustering methods are examined such as Subtractive clustering, fuzzy C-means clustering and K-means clustering. At the same time, subtractiveType-2 clustering is applied to the received signals. The paper focuses on three different features which are AR coefficients, Band Power Frequency, and common spatial pattern (CSP). The classification accuracies with two optimal channels C3 and C4 are investigated.

Online publication date: Sun, 21-May-2017

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Intelligent Systems Technologies and Applications (IJISTA):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com