Browsing M. Murugappan, Dr. by Subject "EEG"

Now showing items 1-13 of 13

    • Appraising human emotions using time frequency analysis based EEG alpha band features 

      M. Murugappan; Ramachandran, Nagarajan; Sazali, Yaacob (Institute of Electrical and Electronics Engineering (IEEE), 2009-07-25)
      In recent years, assessing human emotions through Electroencephalogram (EEG) is become one of the active research area in Brain Computer Interface (BCI) development. The combination of surface Laplacian filtering, ...

    • 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 ...

    • Comparison of different wavelet features from EEG signals for classifying human emotions 

      Murugappan, Muthusamy, Dr.; Nagarajan, Ramachandran, Prof. Dr.; Sazali, Yaacob, Prof. Dr. (Institute of Electrical and Electronics Engineering (IEEE), 2009-10-04)
      In recent years, estimation of human emotions from Electroencephalogram (EEG) signals plays a vital role on developing intellectual Brain Computer Interface (BCI) devices. In this work, we have collected the EEG signals ...

    • 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, ...

    • Emotion classification in Parkinson's disease by higher-order spectra and power spectrum features using EEG signals: a comparative study 

      Yuvaraj, Rajamanickam; Murugappan, M., Dr.; Norlinah, Mohamed Ibrahim; Mohammad Iqbal, Omar@Ye Htut, Assoc. Prof. Dr.; Sundaraj, Kenneth, Prof. Dr.; Khairiyah, Mohamad; Palaniappan, Ramaswamy; Satiyan, Marimuthu (World Scientific Publishing Co. Pte Ltd, 2014-03)
      Deficits in the ability to process emotions characterize several neuropsychiatric disorders and are traits of Parkinson's disease (PD), and there is need for a method of quantifying emotion, which is currently performed ...

    • 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 ...

    • Modified energy based time-frequency features for classifying human emotions using EEG 

      M., Murugappan; R., Nagarajan; Sazali, Yaacob (Universiti Malaysia Perlis, 2009-10-11)
      In this paper we summarize the emotion recognition from the electroencephalogram (EEG) signals. The combination of surface Laplacian filtering, time-frequency analysis (Wavelet Transform) and linear classifiers are used ...

    • 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 ...

    • Time-frequency analysis of EEG signals for human emotion detection 

      Murugappan, Muthusamy, Dr.; M.Rizon; R., Nagarajan; Sazali, Yaacob, Prof. Dr.; Hazry, Desa, Assoc. Prof. Dr.; Zunaidi, Ibrahim (Springer Berlin Heidelberg, 2008)
      This paper proposes an emotion recognition system from EEG (Electroencephalogram) signals. The main objective of this work is to compare the efficacy of classifying human emotions using two discrete wavelet transform (DWT) ...

    • Wireless EEG signals based neuromarketing system using Fast Fourier Transform (FFT) 

      Murugappan, M., Dr.; Murugappan, Subbulakshmi; Balaganapathy; Gerard, Celestin (IEEE Conference Publications, 2014-03)
      his work aims to identify the most preferred brand on automotive in Malaysia through wireless EEG signals. A group of four major vehicle brand advertisements such as Toyota, Audi, Proton and Suzuki is considered on this ...