EEG Based Patient Monitoring System for Mental Alertness Using Adaptive Neuro-Fuzzy Approach

Begum, Dilshad;Ravikumar, K. M.;Mathew, James;Kubakaddi, Sanjeev;Yadav, Rajeev
(2015) Journal of Medical and Bioengineering — Vol. 4, n° 1, p. 59-66 (2015)

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Authors
  • Begum, DilshadGhousia College of Engineering, Ramanagar, Bangalore, India
    Author
  • Ravikumar, K. M.VTU-Regional Office, Mysore, India
    Author
  • Mathew, JamesUCLouvain
    Author
  • Kubakaddi, SanjeevITIE Knowledge Solutions, Bangalore, India
    Author
  • Yadav, RajeevGenia Photonics Inc, Laval, Canada
    Author
Abstract
Recent electrophysiological studies support command-specific changes in the electroencephalography (EEG) that have promoted their intensive application in the noninvasive brain computer interfaces (BCI). However, EEG is plagued by a variety of interferences and noises, thereby demanding better accuracy and stability for its application in the neuroprosthetic devices. Here we investigate wavelets and adaptive neuro-fuzzy classification algorithms to enhance the classification accuracy of cognitive tasks. Using a standard cognitive EEG dataset, we demonstrate improved performance in the classification accuracy with the proposed system. 
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Begum, D., Ravikumar, K. M., Mathew, J., Kubakaddi, S., & Yadav, R. (2015). EEG Based Patient Monitoring System for Mental Alertness Using Adaptive Neuro-Fuzzy Approach. Journal of Medical and Bioengineering, 4(1), 59-66. https://doi.org/10.12720/jomb.4.1.59-66 (Original work published 2015)