Browsing Sazali Yaacob, Prof. Dr. by Title

Now showing items 25-44 of 251

    • 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 ...

    • 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 ...

    • Classification of emotional States from electrocardiogram signals: a non-linear approach based on hurst 

      Selvaraj, Jerritta; Murugappan, M., Dr.; Wan Khairunizam, Wan Ahmad, Dr.; Sazali, Yaacob, Prof. Dr. (BioMed Central, 2013-05)
      Background: Identifying the emotional state is helpful in applications involving patients with autism and other intellectual disabilities; computer-based training, human computer interaction etc. Electrocardiogram (ECG) ...

    • 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 ...

    • The classification of material mechanical properties using non-destructive vibration technique 

      Intan Maisarah, Abd Rahim; Fauziah, Mat; Sazali, Yaacob, Prof. Dr.; Rakhmad, Arief Siregar (Institute of Electrical and Electronics Engineers (IEEE), 2011-03-04)
      This study is to develop a system of a non-destructive testing on the material to define the mechanical properties of material. The study focused on experimental and testing of the material mechanical properties using ...

    • Classification of speaker accent using hybrid DWT-LPC features and K-nearest neighbors in ethnically diverse Malaysian English 

      Yusnita, Mohd Ali; Pandiyan, Paulraj Murugesa, Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Shahriman, Abu Bakar, Dr. (IEEE Conference Publications, 2012-12)
      Accent is a major cause of variability in automatic speaker-independent speech recognition systems. Under certain circumstances, this event introduces unsatisfactory performance of the systems. In order to circumvent this ...

    • Classification of speech dysfluencies using LPC based parameterization techniques 

      Hariharan, Muthusamy; Lim, Sin Chee; Ooi, Chia Ai; Sazali, Yaacob, Prof. Dr. (Springer Science+Business Media, LLC., 2011-01-20)
      The goal of this paper is to discuss and compare three feature extraction methods: Linear Predictive Coefficients (LPC), Linear Prediction Cepstral Coefficients (LPCC) and Weighted Linear Prediction Cepstral Coefficients ...

    • Classification of speech dysfluencies with MFCC and LPCC features 

      Ooi, Chia Ai; Muthusamy, Hariharan, Dr.; Sazali, Yaacob, Prof. Dr.; Lim, Sin Chee (Elsevier Ltd., 2012-02)
      The goal of this paper is to discuss comparison of speech parameterization methods: Mel-Frequency Cepstrum Coefficients (MFCC) and Linear Prediction Cepstrum Coefficients (LPCC) for recognizing the stuttered events. Speech ...

    • Classification of vehicle noise comfort level using feedforward neural network 

      Paulraj, Murugesa Pandiyan, Assoc. Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Siti Marhainis; Andrew, Allan Melvin (Universiti Malaysia Perlis (UniMAP)School of Mechatronic Engineering, 2012-02-27)

    • Classification of vowel sounds using MFCC and feed forward neural network 

      Paulraj, Murugesa Pandiyan, Prof. Madya; Sazali, Yaacob, Prof. Dr.; Nazri, A.; Kumar, S. (Institute of Electrical and Elctronics Engineering (IEEE), 2009-03-06)
      The English language as spoken by Malaysians varies from place to place and differs from one ethnic community and its sub-group to another. Hence, it is necessary to develop an exclusive Speech to text translation system ...

    • Classifying material type and mechanical properties using artificial neural network 

      Intan Maisarah, Abd Rahim; Fauziah, Mat; Sazali, Yaacob, Prof. Dr.; Rakhmad Arief, Siregar (Institute of Electrical and Electronics Engineers (IEEE), 2011-03-04)
      This paper focused on experimental data and study for the testing of the material mechanical properties using vibration technique. By applying vibration analysis and testing on the material, we could determine the natural ...

    • Classroom speech intelligibility prediction using backpropagation Neural Network 

      Paularaj, M. P.; Sazali, Yaacob; Ahmad Nazri; Thagirarani, M. (Coimbatore Institute of Technology, 2007-08-27)
      In terms of individual communication, speech is the most important and efficient means, even in today's multi-media society. Thus, classrooms are mainly used for delivering speech between lecturers and students, it is ...

    • Classroom speech intelligibility prediction using Elman neural network 

      Paulraj, Murugesa Pandiyan, Prof. Madya; Sazali, Yaacob, Prof. Dr.; Ahmad Nazri, Abdullah; M., Thagirarani; M. Ridhwan, Tamjis (Institute of Electrical and Electronics Engineers (IEEE), 2010-05-21)
      A study was conducted to develop a simple system for classrooms speech intelligibility prediction. In this study, several classrooms properties such as size, signal-to-noise ratio (SNR) and Speech Transmission Index ...

    • 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 ...