Browsing Paulraj Murugesa Pandiyan, Assoc. Prof. Dr. by Author "Abdul Hamid, Adom, Prof. Dr."

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    • Adaptive boosting with SVM classifier for moving vehicle classification 

      Norasmadi, Abdul Rahim; Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.; Abdul Hamid, Adom, Prof. Dr. (Malaysian Technical Universities Network (MTUN), 2012-11-20)
      This study examines co-solvent modified supercritical carbon dioxide (SC-CO2) to extract the saturated fatty acids from palm oil. The applied pressure was ranging from 60 to 180 bar and the extraction temperatures were ...

    • 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 ...

    • Brain machine interface for physically retarded people using colour visual tasks 

      Pandiyan, Paulraj Murugesa, Prof. Dr.; Abdul Hamid, Adom, Prof. Dr.; Hema, Chengalvarayan Radhakrishnamurthy; Purushothaman, D. (IEEE Conference Publications, 2010-05)
      A Brain Machine Interface is a communication system which connects the human brain activity to an external device bypassing the peripheral nervous system and muscular system. It provides a communication channel for the ...

    • 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) ...

    • Improving classification of EEG signals for a four-state brain machine interface 

      Hema, Chengalvarayan Radhakrishnamurthy; Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.; Abdul Hamid, Adom, Prof. Dr. (Institute of Electrical and Electronics Engineers (IEEE), 2012)
      Neural network classifiers are one among the popular modes in the design of classifiers for electroencephalograph based brain machine interfaces. This study presents algorithms to improve the classification performance of ...