Browsing School of Mechatronic Engineering (Articles) by Subject "EEG"

Now showing items 1-5 of 5

    • Asymmetric ratio and FCM based salient channel selection for human emotion detection using EEG 

      Mohamad Rizon, Mohamed Juhari; Murugappan, M.; Ramachandran, Nagarajan; Sazali, Yaacob (World Scientific abd Engineering Academy and Scoiety (WSEAS), 2008)
      Electroencephalogram (EEG) is one of the most reliable physiological signals used for detecting the emotional states of human brain. We propose Asymmetric Ratio (AR) based channel selection for human emotion recognition ...

    • 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 ...

    • EEG based detection of conductive and sensorineural hearing loss using artificial neural networks 

      Pandiyan, Paulraj Murugesa , Prof. Dr.; Subramaniam, Kamalraj; Sazali, Yaacob, Prof. Dr.; Abdul Hamid, Adom, Prof. Dr.; Hema, C. R. (Advanced Institute of Convergence IT, 2013-05)
      In this paper, a simple method has been proposed to distinguish the normal and abnormal hearing subjects (conductive or sensorineural hearing loss) using acoustically stimulated EEG signals. Auditory Evoked Potential (AEP) ...

    • An investigation on visual and audiovisual stimulus based emotion recognition using EEG 

      Murugappan, M.; Mohd Rizon, Mohammed Juhari; Nagarajan, Ramachandran, Prof. Dr.; Sazali, Yaacob, Prof. (Inderscience Enterprises Ltd., 2009-01)
      In this paper, we investigate the possibility of using visual and audio visual stimulus for detecting the human emotion by measuring electroencephalogram (EEG). Visual and audiovisual stimulus based protocols is designed ...

    • 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 ...