Browsing Paulraj Murugesa Pandiyan, Assoc. Prof. Dr. by Title

Now showing items 1-20 of 113

    • Active stereo vision based system for estimation of Mobile Robot Orientation using composition matrix 

      Paulraj, Murugesapandian; Fadzilah, Hashim; R. Badlishah, Ahmad; Hema, Chengalvarayan Radhakrishnamurthy; Abdul Hamid, Adom (Universiti Malaysia Perlis, 2009-10-11)
      The computation of a mobile robot position and orientation is a common task in the area of computing vision and image processing. For a successful application, it is important that the position and orientation of a mobile ...

    • 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 ...

    • Analysis of classroom speech intelligibility using fuzzy linear regression model 

      Paulraj, M.P., Dr.; Sazali, Yaacob, Prof. Dr.; Ahmad Nazri, Dr.; Thagirarani, M . (Universiti Malaysia Perlis, 2006)
      Speech is defined as a process of producing sounds confirming to an accepted code by the human vocal apparatus. These sounds are perceived by the ear-brain system with the primary purpose of conveying thoughts. The ...

    • Application of feedforward neural network for the classification of pathological voices 

      Sazali, Yaacob, Prof. Dr.; Murugesa Padiyan, Paulraj, Dr.; Mohd Rizon, Mohammed Juhari, Prof. Dr.; Muthusamy, Hariharan, Dr. (Universiti Teknologi MARA (UiTM), 2007-03-09)
      This paper present the application of feed forward neural network for the classification of pathological voices based on the on the acoustic analysis and EGG features. Acoustic analysis is a non-invasive technique based ...

    • Application of frame energy based DCT moments for the damage diagnosis in steel plates using FLNN 

      Paulraj, Murugesa Pandiyan, Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Mohd Shukry, Abdul Majid, Dr.; Krishnan, Pranesh (IEEE Conference Publications, 2012-12)
      This paper discusses the application of frame energy based Discrete Cosine Transformation (DCT) moment features for the detection of damages in steel plates. A simple experimental model is devised to suspend the steel ...

    • 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 ...

    • Asynchronous brain machine interface-based control of a wheelchair 

      Hema, Chengalvarayan Radhakrishnamurthy; Murugesan Pandiyan, Paulraj, Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Abdul Hamid, Adom, Dr.; Ramachandran, Nagarajan, Prof. Dr. (Springerlink, 2011)
      A brain machine interface (BMI) design for controlling the navigation of a power wheelchair is proposed. Real-time experiments with four able bodied subjects are carried out using the BMI-controlled wheelchair. The BMI is ...

    • 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 ...

    • Automatic detection of voice disorders using self loop architecture in back propagation network 

      Murugesa Pandiyan, Paulraj, Prof. Madya Dr,; Sazali, Yaacob, Prof. Dr.; Sivanandam, S. N.; Muthusamy, Hariharan, Dr. (Anna University, 2008-01-04)
      Acoustic analysis is a non-invasive technique to detect the voice disorders and diagnose the vocal and voice disease. In the recent years, voice disease are increasing dramatically due to unhealthy social habits and voice ...

    • Bimodal Rehabilitation for the Voice and Movement Impaired using Brain Signals 

      Hema, C. R.; Paulraj, M. P., Assoc. Prof. Dr.; Sazali, Yaacob, Prof.; Abdul Hamid, Adom, Assoc. Prof. Dr.; Nagarajan, Prof.; Leong, Shi Wei; Erdy Sulino, Mohd Muslim Tan; Ahmad Zulfadli, Musa; Farid, Affendi (Universiti Malaysia Perlis, 2009-01-07)
      The Bimodal Rehabilitation for the Voice and Movement Impaired using Brain Signals is a device which can help the paralyzed patients to communicate through a digital voice and also to drive a robot chair within their homes ...

    • A Biometric Authentication System Using Brain Signatures 

      Hema, C. R.; Paulraj, M. P., Assoc. Prof. Dr.; Sazali, Yaacob, Prof. Dr.; R., Nagarajan, Prof. Dr.; Abdul Hamid, Adom, Assoc. Prof. Dr.; Adzizul Adzlan, Osman; Leong, Shi Wei; Mohd Ridhwan, Rashid (Universiti Malaysia Perlis, 2010-01-07)
      The Biometric Authentication system comprises of an acquisition unit, a processing unit and a display unit. Signal Processing and Artificial Intelligence is used to process the brain signatures collected through EEG ...

    • BMI using spectral energy entropy for colour visual tasks 

      Divakar, Purushothaman; Paulraj, Murugesa Pandiyan, Prof. Madya Dr.; Abdul Hamid, Adom, Dr.; Hema, Chengalvarayan Radhakrishnamurthy (Universiti Malaysia Perlis (UniMAP)Centre for Graduate Studies, 2010-10-16)
      EEG signals are the electrophysiological measures of brain function and it is used to develop a Brain machine Interface. A Brain machine Interface (BMI) system is used to provide a communication and control technology ...

    • Brain machine interface based wheelchair control with minimal subject training 

      Hema, Chengalvarayan Radhakrishnamurthy; Paulraj, Murugesapandian; Sazali, Yaacob; Abdul Hamid, Adom; Ramachandran, Nagarajan (Universiti Malaysia Perlis, 2009-10-11)
      Wheelchair control using a Brain Machine Interface based on motor imagery requires adequate subject training. In this paper we propose a new algorithm for a brain machine interface design which is implemented in real-time ...

    • 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 ...

    • Brain machine interface: A comparison between fuzzy and neural classifiers 

      Hema, Chengalvarayan Radhakrishnamurthy; Paulraj, Murugesapandian; Ramachandran, Nagarajan; Sazali, Yaacob; Abdul Hamid, Adom (ICIC International, 2009)
      Patients with neurodegenerative disease loose all motor movements including impairment of speech, leaving the patients totally locked-in. One possible option for rehabilitation of such patients is through a brain machine ...

    • Brain machine interface: Analysis of segmented EEG signal classification using short-time PCA and recurrent neural networks 

      Hema, Chengalvarayan Radhakrishnamurthy; Paulraj, Murugesa Pandiyan, Assoc. Prof.; Nagarajan, Ramachandran, Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Abdul Hamid, Adom, Prof. Madya (University of Basrah, 2008)
      Brain machine interface provides a communication channel between the human brain and an external device. Brain interfaces are studied to provide rehabilitation to patients with neurodegenerative diseases; such patients ...

    • Brain machine interface: classification of mental tasks using short-time PCA and recurrent neural networks 

      Hema, Chengalvarayan Radhakrishnamurthy; Paulraj, Murugesapandian; Sazali, Yaacob; Abd Hamid, Adom; Ramachandran, Nagarajan (Institute of Electrical and Electronics Engineering (IEEE), 2007-11-25)
      Brain machine interface provides a communication channel between the human brain and an external device. Brain interfaces are studied to provide rehabilitation to patients with neurodegenerative diseases; such patients ...

    • Brain machine interface: motor imagery recognition with different signal length representations 

      Hema, Chengalvarayan Radhakrishnamurthy; Paulraj, Murugesapandian; Sazali, Yaacob; Abdul Hamid, Adom; Ramachandran, Nagarajan (Institute of Electrical and Electronics Engineering (IEEE), 2009-03-06)
      This work investigates how signal representations affect the performance of a motor imagery recognition system, specifically we investigate on recognition accuracy and computational time of a brain machine interface designed ...

    • Brain signatures: a modality for biometric authentication 

      Hema, Chengalvarayan Radhakrishnamurthy; Paulraj, Murugesapandian; Kaur, Harkirenjit (Institute of Electrical and Electronics Engineering (IEEE), 2008-12-01)
      In this paper we investigate the use of brain signatures as a possible biometric authentication technique. Research on brain EEG signals has shown that individuals exhibit unique brain patterns for similar tasks. In this ...

    • Car cabin interior noise classification using temporal composite features and probabilistic neural network model 

      Paulraj, Murugesa Pandiyan, Prof. Dr.; Allan Melvin, Andrew; Sazali, Yaacob, Prof. Dr. (Trans Tech Publications Inc., 2014)
      Determination of vehicle comfort is important because continuous exposure to the noise and vibration leads to health problems for the driver and passengers. In this paper, a vehicle comfort level classification system has ...