Browsing M. Murugappan, Dr. by Author "musawali@yahoo.com"

Now showing items 1-8 of 8

    • Classification of driver drowsiness level using wireless EEG 

      Mousa Kadhim, Wali; Murugappan, Muthusamy, Dr.; R. Badlishah, Ahmad, Prof. Dr. (Przegląd Elektrotechniczny, 2013)
      In this work, wireless Electroencephalogram (EEG) signals are used to classify the driver drowsiness levels (neutral, drowsy, high drowsy and sleep stage1) based on Discrete Wavelet Packet Transform (DWPT). Two statistical ...

    • Development of EEG data acquisition device by using single board computer 

      Wali, Mousa Kadhim; Murugappan, M., Dr.; R. Badlishah, Ahmad, Prof. Dr. (Inderscience Enterprises Ltd., 2013)
      Electroencephalogram (EEG) plays a vital role in several medical diagnosis (brain tumour detection, Alzheimer disease, epilepsy, etc.), engineering applications (emotion detection, drowsiness detection, stress assessment, ...

    • Development of EEG data acquisition device by using TS7800 Single Board Computer (SBC) 

      Mousa K. Wali; Murugappan, M., Dr.; R. Badlishah, Ahmad, Assoc. Prof. Dr. (Universiti Malaysia Perlis (UniMAP)School of Mechatronic Engineering, 2012-02-27)
      Electroencephalogram (EEG) plays a vital role in several medical diagnosis (brain tumor detection, Alzheimer disease, epilepsy, etc), engineering applications (emotion detection, drowsiness detection, stress assessment, ...

    • Mathematical implementation of hybrid fast fourier transform and discrete wavelet transform for developing graphical user interface using visual basic for signal processing applications 

      Wali, Mousa Kadhim; Murugappan, M., Dr.; R. Badlishah, Ahmad, Prof. Dr. (World Scientific Publishing Co. Pte Ltd, 2012)
      In recent years, the application of discrete wavelet transform (DWT) on biosignal processing has made a significant impact on developing several applications. However, the existing user-friendly software based on graphical ...

    • PNN based driver drowsiness level classification using EEG 

      Mousa Kadhim, Wali; Murugappan, Muthusamy, Dr.; R. Badlishah, Ahmad, Prof. Dr. (JATIT & LLS. All rights reserved, 2013-06)
      In this work, we classify the driver drowsiness level (awake, drowsy, high drowsy and sleep stage1) based on different wavelets and probabilistic neural network classifier using wireless EEG signals. Deriving the amplitude ...

    • Subtractive fuzzy classifier based driver distraction levels classification using EEG 

      Wali, Mousa Kadhim; Murugappan, M., Dr.; R. Badlishah, Ahmad, Prof. Dr. (Society of Physical Therapy Science, 2013)
      [Purpose] In earlier studies of driver distraction, researchers classified distraction into two levels (not distracted, and distracted). This study classified four levels of distraction (neutral, low, medium, high). [Subjects ...

    • Subtractive fuzzy classifier based driver drowsiness levels classification using EEG 

      Murugappan, M., Dr.; Wali, Mousa Kadhim; R. Badlishah, Ahmad, Prof. Dr.; Murugappan, Subbulakshmi (IEEE Conference Publications, 2013-04)
      Driver drowsiness is one of the major causes for several road accidents over the world. In this study, Electroencephalogram (EEG) signals were acquired using 14 electrodes from 50 subjects. All the electrodes are placed ...

    • Wavelet packet transform based driver distraction level classification using EEG 

      Wali, Mousa Kadhim; Murugappan, M., Dr.; R. Badlishah, Ahmad, Prof. Dr. (Mathematical Problems in Engineering, 2013)
      We classify the driver distraction level (neutral, low, medium, and high) based on different wavelets and classifiers using wireless electroencephalogram (EEG) signals. 50 subjects were used for data collection using 14 ...