Browsing Ramachandran, Nagarajan, Prof. Dr. by Title

Now showing items 1-20 of 91

    • An adaptive predictive fuzzy logic for the altitude control of a micro-satellite 

      Ramachandran, Nagarajan; Pandiyan, Paulraj Murugesa, Prof. Madya Dr.; Sazali, Yaacob, Prof. Dr.; Zuraidah, Md Zain, Prof. Dr.; Rusli, R. (Association pour la promotion des techniques de modelisation et de simulation dans l'entreprise Press, 2009)
      This paper deals with the attitude control of a micro-satellite in space using fuzzy logic principles. A micro-satellite in space can behave in an un-predictive way due the effect of variations in its system parameters and ...

    • 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, ...

    • Artificial intelligence techniques in IC chip marking 

      Muthukaruppan, Kartigayan; Nagarajan, R.; Sazali, Yaacob; Pandian, Paulraj; Mohamed Rizon, Mohamed Juhari (Kolej Universiti Kejuruteraan Utara Malaysia, 2005)
      In this paper, an industrial machine vision system incorporating Optical Character Recognition (OCR) is employed to inspect the marking on the Integrated Circuit (IC) Chips. This inspection is carried out while the ICs are ...

    • 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 ...

    • 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 ...

    • 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 ...

    • 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: 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 ...

    • Classification of human emotion from eeg using discrete wavelet transform 

      Murugappan, M.; Ramachandran, Nagarajan; Sazali, Yaacob, Prof. Dr. (Scientific Research Publishing Inc, 2010-04)
      In this paper, we summarize the human emotion recognition using different set of electroencephalogram (EEG) channels using discrete wavelet transform. An audio-visual induction based protocol has been designed with more ...

    • Combining spatial filtering and wavelet transform for classifying human emotions using EEG Signals 

      Murugappan; Nagarajan, Ramachandran, Prof. Dr.; Sazali, Yaacob, Prof. Dr. (Biomedical Engineering Society of the R.O.C., 2011)
      In this paper, we present human emotion assessment using electroencephalogram (EEG) signals. The combination of surface Laplacian (SL) filtering, time-frequency analysis of wavelet transform (WT) and linear classifiers are ...

    • 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 ...

    • Comparison of performance using Daubechies Wavelet family for facial expression recognition 

      M., Satiyan; M., Hariharan; Ramachandran, Nagarajan, Prof. Dr. (Institute of Electrical and Electronics Engineers (IEEE), 2010-05-21)
      This paper investigates the performance of a Daubechies Wavelet family in recognizing facial expressions. A set of luminance stickers were fixed on subject's face and the subject is instructed to perform required facial ...

    • Design and development of stereo motion for mobile observation center 

      Muhammad Naufal, Mansor; Sazali, Yaacob; Nagarajan, R.; Hariharan, M. (Universiti Malaysia Perlis, 2009-10-11)
      This paper presents an approach to the condition monitoring patient in ICU. A human-computer interface (HCI) system is designed for the people with severe disabilities. For the last decades, most of the patients’ sleeps ...

    • Detection of facial changes for hospital ICU patients 

      Muhammad Naufal, Mansor; Sazali, Yaacob, Prof. Dr.; Nagarajan, Ramachandran, Prof. Dr.; Hariharan, M. (Institute of Electrical and Electronics Engineers (IEEE), 2010-05-21)
      This paper presents an integrated system for detecting facial changes of patient in a hospital in Intensive Care Unit (ICU). The facial changes are most widely represented by eyes and mouth movements. The proposed system ...

    • Detection of facial changes for hospital ICU patients using neural network 

      Muhammad Naufal, Mansor; Sazali, Yaacob, Prof. Dr.; Ramachandran, Nagarajan, Prof. Dr.; Muthusamy, Hariharan (Institute of Electrical and Electronics Engineers (IEEE), 2010-05-21)
      This paper presents an integrated system for detecting facial changes of patient in a hospital in Intensive Care Unit (ICU). The facial changes are most widely represented by eyes movements. The proposed system uses color ...

    • Detection of facial changes for ICU patients using KNN classifier 

      Muhammad Naufal, Mansor; Sazali, Yaacob, Prof. Dr.; Nagarajan, Ramachandran; Che, Lim Sin; Hariharan, Muthusamy, Dr.; Muhd Ezanuddin, Abdul Aziz (2010-06)
      This paper presents an integrated system for detecting facial changes of patient in a hospital in Intensive Care Unit(ICU).In this research we have considered the facial changes most widely represented by eyes and mouth ...