A novel method of motor imagery classification using eeg signal.

Journal: Artificial intelligence in medicine
Published Date: Dec 31, 2019

Abstract

A subject of extensive research interest in the Brain Computer Interfaces (BCIs) niche is motor imagery (MI), where users imagine limb movements to control the system. This interest is owed to the immense potential for its applicability in gaming, neuro-prosthetics and neuro-rehabilitation, where the user's thoughts of imagined movements need to be decoded. Electroencephalography (EEG) equipment is commonly used for keeping track of cerebrum movement in BCI systems. The EEG signals are recognized by feature extraction and classification. The current research proposes a Hybrid-KELM (Kernel Extreme Learning Machine) method based on PCA (Principal Component Analysis) and FLD (Fisher's Linear Discriminant) for MI BCI classification of EEG data. The performance and results of the method are demonstrated using BCI competition dataset III, and compared with those of contemporary methods. The proposed method generated an accuracy of 96.54%.

Authors

  • Venkatachalam K
    School of CSE, VIT Bhopal University, Bhopal, India. Electronic address: venkatme83@gmail.com.
  • Devipriya A
    Department of IT, Sri Krishna College of Engineering and Technology, Coimbatore, India. Electronic address: itdevipriya@gmail.com.
  • Maniraj J
    Department of Mechanical Engineering, KIT, Coimbatore, India. Electronic address: maniraj_j@rediffmail.com.
  • Sivaram M
    Department of Computer Networking, Lebanese French University, Erbil, Kurdistan Region, Iraq. Electronic address: sivaram.murugan@lfu.edu.krd.
  • Ambikapathy A
    Department of EEE, Galgotias College of Engineering and Technology, Greater Noida, India. Electronic address: ami_ty21@yahoo.com.
  • S Amiri Iraj
    Computational Optics Research Group, Advanced Institute of Materials Science, Ton Duc Thang University, Ho Chi Minh City, Viet Nam; Faculty of Applied Sciences, Ton Duc Thang University, Ho Chi Minh City, Viet Nam. Electronic address: irajsadeghamiri@tdtu.edu.vn.

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