Browsing Sazali Yaacob, Prof. Dr. by Subject "EEG"

Now showing items 1-8 of 8

    • 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 ...

    • Automated system for stress evaluation based on EEG signal: A prospective review 

      Saidatul Ardeenawatie, Awang; Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Nashrul Fazli, Mohd Nasir (Institute of Electrical and Electronics Engineers (IEEE), 2011-03-04)
      This paper reviews the issues related to the automated system for stress evaluation based on brain signal. It describes the current status of mental health especially in Malaysia. The anatomy of stress is briefly discussed ...

    • 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 ...

    • 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 ...

    • 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 ...

    • Recognition of motor imagery of hand movements for a BMI using PCA features 

      Hema, Chengalvarayan Radhakrishnamurthy; Paulraj, Murugesapandian; Sazali, Yaacob; Abd Hamid, Adom; Ramachandran, Nagarajan (Institute of Electrical and Electronics Engineering (IEEE), 2008-12-01)
      Motor imagery is the mental simulation of a motor act that includes preparation for movement and mental operations of motor representations implicitly or explicitly. The ability of an individual to control his EEG through ...