Now showing items 13-32 of 78

    • 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 ...
    • A comparative study of wavelet families for classification of wrist motions 

      Muthusamy, Hariharan; Chong, Yen Fook; Sindhu, Ravindran; Bukhari, Ilias; Sazali, Yaacob, Prof. Dr. (Elsevier Ltd., 2012-11)
      The selection of most suitable mother wavelet function is still an open research problem in various signal and image processing applications. This paper presents a comparative study of different wavelet families (Daubechies, ...
    • Comparison of LPCC and MFCC for isolated Malay speech recognition 

      Chong x, Chong Yen Fook; Muthusamy, Hariharan, Dr.; Sazali, Yaacob, Prof. Dr.; Abdul Hamid, Adom, Prof. Dr. (Universiti Malaysia Perlis (UniMAP), 2012-06-18)
      Automatic speech recognition (ASR) is an area of research which deals with the recognition of speech by machine in several conditions. ASR performs well under restricted conditions (quiet environment), but performance ...
    • 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 ...
    • Comparison of speech parameterization techniques for the classification of speech disfluencies 

      Chong, Yen Fook; Hariharan, Muthusamy, Dr.; Lim, Sin Chee; Sazali, Yaacob, Prof. Dr.; Abdul Hamid, Adom, Prof. Dr. (Scientific and Technical Research Council of Turkey, 2013-12)
      Stuttering assessment through the manual classification of speech disfluencies is subjective, inconsistent, time-consuming, and prone to error. The aim of this paper is to compare the effectiveness of the 3 speech feature ...
    • 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 ...
    • Detection of vocal fold paralysis and edema using time-domain features and probabilistic neural network 

      Hariharan, Muthusamy; Paulraj, Murugesa Pandiyan, Assoc. Prof.; Sazali, Yaacob, Prof. Dr. (Inderscience Publisher, 2011)
      This paper proposes a feature extraction method based on time-domain energy variation for the detection of vocal fold pathology. In this work, two different vocal fold problems (vocal fold paralysis and edema) are taken ...
    • Development of attitude control system on RCM3400 microcontroller 

      Yaakop, M.; Sazali, Yaacob, Prof. Dr.; Abdul Rahman, Mohd Saad, Prof Madya; Zain, M.; Paulraj, Murugesa Pandiyan, Prof. Dr.; Hariharan, M.; Nagarajan, R., Prof. Dr.; Kay, W. S.; Arshad, A. S. (Institute of Electrical and Electronic Engineers (IEEE), 2009-02-17)
      This paper describes the development of a nanosatellite altitude control system (ACS) which employ a filter base controller with comparison with a simple adaptive predictive fuzzy logic controller (APFLC) for a 1, 2 and 3 ...
    • Diagnosis of vocal fold pathology using time-domain features and systole activated neural network 

      Paulraj, Murugesa Pandiyan, Prof. Madya; Sazali, Yaacob, Prof. Dr.; Hariharan, M. (Institute of Electrical and Elctronics Engineering (IEEE), 2009-03-06)
      Due to the nature of job, unhealthy social habits and voice abuse, the people are subjected to the risk of voice problems. It is well known that most of vocal fold pathologies cause changes in the acoustic voice signal. ...
    • 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 ...
    • 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 ...
    • Discrete wavelet transform in recognition human emotional movement through knocking 

      Shafriza Nisha, Basah, Dr.; Sazali, Yaacob, Prof. Dr.; Muthusamy, Hariharan, Dr.; Nurnadia, M. Khair (IEEE Conference Publications, 2013)
      Developing tools for identifying emotional states in human action is seen more challenging area of research and has attracted many researchers recently. In this paper, a new feature extraction method was proposed in ...
    • Discrimination of vision impairments using single trial VEPs 

      Vijean, Vikneswaran; Hariharan, Muthusamy, Dr.; Sazali, Yaacob, Prof. Dr. (IEEE Conference Publications, 2011-11)
      Analysis of Visually evoked potential (VEP) in the investigation of ocular diseases is gaining interests from researchers all over the world. VEP is an electrical signal generated by the brain (Occipital Cortex) in response ...
    • Effect of normalization method on classification of speech dysfluencies using LPC, LPCC and WLPCC 

      Lim, Sin Chee; Sazali, Yaacob, Prof. Madya Dr.; Muthusamy, Hariharan (Universiti Malaysia Perlis (UniMAP)Centre for Graduate Studies, 2010-10-16)
      The main aim of this paper is to discuss the enhancement of the classification performance on the speech dysfluencies, namely, prolongations and repetitions after employ statistical normalization (SN) on signal and ...
    • 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 ...
    • Feature extraction for biometric recognition with photoplethysmography signals 

      Resit Kavsaoglu, A.; Polat, Kemal; Recep Bozkure, M.; Hariharan, Muthusamy, Dr. (IEEE Conference Publications, 2013-04)
      Photoplethysmography (PPG) signals stand out due to features such as readily accessible, high reliability and confidentiality, the ease of use etc. among bio-signals. The feasibility studies carried out on the PPG signals ...