Now showing items 101-120 of 250

    • Improved back propagation neural network for the diagnosis of pathological voices 

      Paulraj, M.P.; Sazali, Yaacob, Prof. Dr.; Sivanandam, S. N.; Hariharan, Muthusamy (Association for Advancedment of Modelling and Simulation Techniques in Entreprises (A.M.S.E), 2008)
      Most of vocal and voice diseases cause changes in the voice. ENT clinicians use acoustic voice analysis to characterize the pathological voices. Nowadays, voice diseases are increasing dramatically due to unhealthy social ...
    • Identification of vocal and voice disorders 

      Murugesa Pandiyan, Paulraj, Prof. Madya Dr.; Sazali, Yaacob, Prof. Dr.; Mohd Rizon, Mohammed Juhari, Prof. Dr.; Sivanandam, S. N.; Muthusamy, Hariharan, Dr. (Universiti Malaysia Perlis (UniMAP), 2007-10-25)
      The discrimination of normal and pathological voices using noninvasive acoustic analysis helps to perform accurate identification of voice disorders and diagnoses of vocal and voice disease. Acoustic analysis is a non- ...
    • Neural network based detection of voice disorders using energy spectrum and equal-loudness contours 

      Murugesa Pandian, Paulraj, Prof. Madya Dr.; Sazali, Yaacob, Prof. Dr.; Sivanandam, S. N.; Muthusamy, Hariharan, Dr. (Universiti Teknologi MARA (UiTM)Faculti of Electrical Engineering, 2008-03-07)
      Impairment of vocal function can have a major impact on the quality of life, severely limiting communication at work and affecting all social aspect of daily life. In the recent years, voice disease are increasing dramatically ...
    • Diagnosis of voice disorders using band energy spectrum in wavelet domain 

      Murugesa Pandiyan, Paulraj, Prof. Madya Dr,; Sazali, Yaacob, Prof. Dr.; Muthusamy, Hariharan, Dr. (Universiti Malaysia Perlis (UniMAP), 2008-03-08)
      In the evolution of quality of speech, acoustic analyses of normal and pathological voices have become increasingly interesting to researchers in laryngology and speech pathologies. Vocal signal information plays an important ...
    • A preliminary study of inhaled pharmaceutical aerosol flow characteristics in metered dose inhaler spacer 

      Ahmad Faizal, Salleh; Muhammad Izham, Ismail; Md Tasyrif, Abdul Rahman; Sazali, Yaacob, Prof. Dr.; Khaled, Helmy, Dr. (Springerlink, 2008-06-25)
      Metered Dose Inhalers (MDI) is used to prevent and relieve the symptoms and progression of certain diseases (asthma, chronic obstructive pulmonary disease, cystic fibrosis and bronchiectosis) by delivering the inhaled ...
    • 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 ...
    • A review on stress inducement stimuli for assessing human stress using physiological signals 

      P., Karthikeyan; Murugappan, M., Dr.; Sazali, Yaacob, Prof. Dr. (Institute of Electrical and Electronics Engineers (IEEE), 2011-03-04)
      Assessing human stress in real-time is more difficult and challenging today. The present review deals about the measurement of stress in laboratory environment using different stress inducement stimuli by the help of ...
    • 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 ...
    • 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 ...
    • Supervised neural network classifier for voice pathology 

      Murugesa Pandiyan, Paulraj, Prof. Madya Dr,; Sazali, Yaacob, Prof. Dr.; Sivanandam, S. N.; Hariharan, Muthusamy (Kongu Engineering College, 2008-01-03)
      The classification of normal and pathological voices using noninvasive acoustical analysis features helps speech specialist to perform accurate diagnoses of vocal and voice disease. Acoustic analysis is a non-invasive ...
    • 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 ...
    • 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 ...
    • Performance comparisons of new excitation coil design aspects in Magnetic Induction Tomography (MIT) applications 

      Zulkarnay, Zakaria; Muhamad Hafiz, Hussin; Ruzairi, Abdul Rahim; Nur Farahiyah, Mohammad; Azian Azamimi, Abdullah; Sazali, Yaacob, Prof. Dr.; Syed Mustafa Kamal, Syed Aman (Institute of Electrical and Electronics Engineers (IEEE), 2011-01-24)
      Magnetic Induction Tomography (MIT) is a contactless method interested in conductivity properties of the object. In MIT system, excitation coil plays an important role since it generate primary field which then will propagate ...
    • Feature extraction based on mel-scaled wavelet packet transform for the diagnosis of voice disorders 

      Murugesa Pandian, Paulraj, Prof. Madya Dr,; Sazali, Yaacob, Prof. Dr.; Muthusamy, Hariharan, Dr. (SpringerLink, 2008-06-25)
      Feature extraction from the vocal signal plays very important role in the area of automatic detection of voice disorders. Many feature extraction algorithms have been developed in the last three decades based on acoustic ...
    • 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 ...
    • Phoneme-based or isolated-word modeling speech recognition system? An overview 

      Yusnita, M. A.; Murugesa Pandiyan, Paulraj, Assoc. Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Shahriman, Abu Bakar; Saidatul Ardeenaawatie, Awang; Ahmad Nazri, Abdullah (Institute of Electrical and Electronics Engineers (IEEE), 2011-03-04)
      In this paper speech theories and some methodological concerns about feature extraction and classification techniques widely used in speech recognition system are surveyed and discussed. The shortage of isolated word speech ...
    • Pathological infant cry analysis using wavelet packet transform and probabilistic neural network 

      Muthusamy, Hariharan; Sazali, Yaacob, Prof. Dr.; Saidatul Ardeenaawatie, Awang (Elsevier Ltd., 2011-11)
      A new approach has been presented based on the wavelet packet transform and probabilistic neural network (PNN) for the analysis of infant cry signals. Feature extraction and development of classification algorithms play ...
    • 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 ...
    • Diagnosis of voices disorders using MEL scaled WPT and functional link neural network 

      Paulraj, Muregesa Pandiyan, Prof. Madya Dr.; Sazali, Yaacob, Prof. Dr.; Hariharan, Muthusamy (Biomedical Fuzzy Systems Association (BMFSA), 2008-03-31)
      Nowadays voice disorders are increasing dramatically due to the modern way of life. Most of the voice disorders cause changes in the voice signal. Acoustic analysis on the speech signal could be a useful tool for ...
    • Patients tremble analysis under different camera placement in critical care 

      Muhammad Naufal, Mansor; Sazali, Yaacob, Prof. Dr.; R. Nagarajan, Prof. Dr.; Muthusamy, Hariharan, Dr. (Science Academy, 2011-03)
      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 ...