Browsing Sazali Yaacob, Prof. Dr. by Author "Wan Khairunizam, Wan Ahmad, Dr."

Now showing items 1-9 of 9

    • Classification of emotional States from electrocardiogram signals: a non-linear approach based on hurst 

      Selvaraj, Jerritta; Murugappan, M., Dr.; Wan Khairunizam, Wan Ahmad, Dr.; Sazali, Yaacob, Prof. Dr. (BioMed Central, 2013-05)
      Background: Identifying the emotional state is helpful in applications involving patients with autism and other intellectual disabilities; computer-based training, human computer interaction etc. Electrocardiogram (ECG) ...

    • Emotion detection from QRS complex of ECG signals using hurst exponent for different age groups 

      Selvaraj, Jerritta; Murugappan, M., Dr.; Wan Khairunizam, Wan Ahmad, Dr.; Sazali, Yaacob, Prof. Dr. (IEEE Conference Publications, 2013-09)
      Emotion recognition using physiological signals is one of the key research areas in Human Computer Interaction (HCI). In this work, we identify the six basic emotional states (Happiness, sadness, fear, surprise, disgust ...

    • 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 ...

    • Emotion recognition from facial EMG signals using higher order statistics and principal component analysis 

      Selvaraj, Jerritta; Murugappan, Muthusamy, Dr.; Wan Khairunizam, Wan Ahmad, Dr.; Sazali, Yaacob, Prof. Dr. (Taylor & Francis, 2014-04)
      Higher order statistics (HOS) is an efficient feature extraction method used in diverse applications such as bio signal processing, seismic data processing, image processing, sonar, and radar. In this work, we have ...

    • Frequency study of facial electromyography signals with respect to emotion recognition 

      Selvaraj, Jerritta; Murugappan, Muthusamy, Dr.; Wan Khairunizam, Wan Ahmad, Dr.; Sazali, Yaacob, Prof. Dr. (Walter de Gruyter GmbH, 2014-01)
      Emotional intelligence is one of the key research areas in human-computer interaction. This paper reports the development of an emotion recognition system using facial electromyogram (EMG) signals focusing the ambiguity ...

    • In vitro evaluation of finger's hemodynamics for vein graft surveillance using electrical bio-impedance method 

      Lee, Hoi Leong; Shahriman, Abu Bakar, Dr.; Sazali, Yaacob, Prof. Dr.; Zuradzman, Mohamad Razlan, Dr.; Wan Khairunizam, Wan Ahmad, Dr.; Zunaidi I.B; Cheng, Ee Meng, Dr.; Siti Khadijah, Za'aba, Dr.; Shafriza Nisha, Basah, Dr.; Mohd Afendi, Rojan, Dr.; Sharifah Roohi, Syed Waseem Ahmad (American-Eurasian Network for Scientific Information (AENSI), 2014-03)
      Electrical bio-impedance measurement has great potential in many biomedical applications including vein graft surveillance. Studies have shown that thrombosis was the major cause of the vein graft failure. The meticulous ...

    • Infant cry classification to identify asphyxia using time-frequency analysis and radial basis neural networks 

      Muthusamy, Hariharan; Jeyaraman, Saraswathy; Sindhu, Ravindran; Wan Khairunizam, Wan Ahmad, Dr.; Sazali, Yaacob, Prof. Dr. (Elsevier Ltd, 2012-08)
      A cry is the first verbal communication of infants and it is described as a loud, high-pitched sound made by infants in response to certain situations. Infant cry signals can be used to identify physical or psychological ...

    • Infant cry classification: time frequency analysis 

      Saraswathy, Jeyaraman; Hariharan, Muthusamy, Dr.; Wan Khairunizam, Wan Ahmad, Dr.; Sazali, Yaacob, Prof. Dr.; Thiyagar., N (IEEE Conference Publications, 2013-11)
      Acoustic analysis of infant cry has been the subject of a number of researchers since half decades ago. This paper addresses a simple time-frequency analysis based signal processing technique using short-time Fourier ...

    • Performance comparison of daubechies wavelet family in Infant cry classification 

      Saraswathy, J; Hariharan, Muthusamy; Vijean, Vikneswaran; Sazali, Yaacob, Prof. Dr.; Wan Khairunizam, Wan Ahmad, Dr. (IEEE Conference Publications, 2012)
      Infant cry is a non-stationary, loud, high-pitched signal made by infants in response to certain situations. This acoustic signal can be used to identify physical or psychology status of infant. The aim of this work is to ...