Now showing items 1-4 of 4

    • 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 ...
    • Electromyogram signal based human emotion classification using KNN and LDA 

      Murugappan, M., Dr. (IEEE Conference Publications, 2011-06)
      In this paper, we presents Electromyogram (EMG) signal based human emotion classification using K Nearest Neighbor (KNN) and Linear Discriminant Analysis (LDA). Five most dominating emotions such as: happy, disgust, fear, ...
    • Emotion recognition from electrocardiogram signals using Hilbert Huang Transform 

      Selvaraj, Jerritta; Murugappan, M., Dr.; Wan Khairunizam, Wan Ahmad, Dr.; Sazali, Yaacob, Prof. Dr. (IEEE Conference Publications, 2012-10)
      Equipping robots and computers with emotional intelligence is becoming important in Human-Computer Interaction (HCI). Bio-signal based methods are found to be reliable and accurate than conventional methods as they directly ...
    • Human emotions classification and EEG channel reduction: A review 

      Intan Farlina Zaimatulaili, Mohd Idris; Murugappan, M., Dr.; Wan Khairunizam, Wan Ahmad, Dr. (Universiti Malaysia Perlis (UniMAP), 2012-06-18)
      Brain signals are collected from the human scalp through a set of electrodes placed over the entire scalp. In recent years, the researchers are using higher number of Electroencephalography (EEG) channels to collect the ...