Now showing items 1-8 of 8

    • Application-specific multichannel EEG data acquisition system for portable biomedical application 

      Paulraj, Murugesa Pandian, Dr.; Abdul Hamid, Adom, Prof. Dr.; Tung, Kai Xu; Subramaniam, Kamalraj (Malaysian Technical Universities Network (MTUN), 2012-11-20)
      This paper presents the design and construction of a low power application-specific EEG bio-potential multichannel amplifier with high common mode rejection ratio (CMRR) and high input impedance. The bio-potential amplifier ...
    • 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, ...
    • 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 ...
    • Detection of wrist movement using EEG signal for brain machine interface 

      Farid, Ghani, Prof. Dr.; Gaur, Bhoomika; Varshney, Sidhika; Farooq, Omar; Khan, Yusufuzzama (Institute of Electrical and Electronics Engineers (IEEE), 2013-06)
      Brain machine interfaces (BMIs) allow patients suffering from neuromuscular disorders to control the movement of robotic limb or wheelchair under their own guidance. So far only invasive technologies e.g. Electrocorticography ...
    • Driver fatigue and driving performance among drivers in Simulated Prolonged Driving 

      Kee, S.S.; Shamsul Bahri, Mohd Tamrin; Goh Yong, Meng (Universiti Malaysia Perlis (UniMAP), 2009-12-01)
      Motor vehicle accident is a major problem in Malaysia. The statistics for a ten year periods (1997 to 2007) shows an increasing number of accidents. Fatigue and drowsiness among the commercial drivers has been identified ...
    • 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 ...