Browsing Abdul Hamid Adom, Prof. Dr. by Subject "Neural network"

Now showing items 1-5 of 5

    • 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 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 ...

    • Classification of EEG colour imagination tasks based BMI using energy and entropy features 

      Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.; Abdul Hamid, Adom, Assoc. Prof. Dr.; Hema, Chengalvarayan Radhakrishnamurthy; Purushothaman, Divakar (Universiti Malaysia Perlis (UniMAP)School of Mechatronic Engineering, 2012-02-27)
      Electroencephalogram (EEG) signals are the electrophysiological measures of brain function and it is used to develop a brain machine interface. Brain machine interface (BMI) system is used to provide a communication and ...

    • 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) ...

    • Synchronous brain machine interface design using focused time delay networks 

      Hema, Chengalvarayan Radhakrishnamurthy; Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Abdul Hamid, Adom, Assoc. Prof. Dr.; Ramachandran, Nagarajan, Prof. Dr. (Universiti Malaysia Perlis (UniMAP)School of Mechatronic Engineering, 2012-02-27)
      Focused time delay neural network based design for a four-state Brain Machine Interface (BMI) to drive a wheelchair is analyzed. Motor imagery signals recorded noninvasively using two bipolar electrodes are used in the ...