Browsing Researchers by Author "Muthusamy, Hariharan, Dr."

Now showing items 1-19 of 19

    • 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 ...

    • Assimilate the auditory scale with wavelet packet filters for multistyle classification of speech under stress 

      Nurul Aida Amira, Johari; Muthusamy, Hariharan, Dr.; Saidatul Ardeenawatie, Awang; Sazali, Yaacob, Prof. Dr. (Institute of Electrical and Electronics Engineers (IEEE), 2012-02-27)
      Nowadays, people are having high stress level due to highworkload stress, emergency phone call and multitasking. Emotional/stress of a person affects his/her performance in daily life and speech production. The research ...

    • Automatic classification of infant cry: A review 

      Saraswathy, J.; Muthusamy, Hariharan, Dr.; Sazali, Yaacob, Prof. Dr.; Wan Khairunizam, Wan Ahmad, Dr, (Institute of Electrical and Electronics Engineers (IEEE), 2012-02-27)
      This paper reviews the some of significant works on infant cry signal analysis proposed in the past two decades and reviews the recent progress in this field. The cry of baby cannot be predicted accurately where it is very ...

    • 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 ...

    • Automatic infant anxiety character with SVM 

      Sazali, Yaacob, Prof. Dr.; Muthusamy, Hariharan, Dr.; Shafriza Nisha, Basah, Dr.; Mohd Lutfi, Mohd Khidir; Ku Mohd Yusri, Ku Ibrahim; Syahrull Hi-Fi Syam, Ahmad Jamil; Ahmad Kadri, Junoh; Muhammad Nazri, Rejab; Muhammad Naufal, Mansor (Elsevier Ltd., 2012)
      Notable complications of sedation practices have been identified and efforts to modify these practices in ICUs have begun. While sedation-scoring tools have been introduced into clinical practice in intensive care few have ...

    • Automatically infant cues recognition based on LDA and SVM classifier 

      Sazali, Yaacob, Prof. Dr.; Muhammad Nazri, Rejab; Ahmad Kadri, Junoh; Syahrull Hi-Fi Syam, Ahmad Jamil; Shafriza Nisha, Basah, Dr.; Muthusamy, Hariharan, Dr.; J, Ahmad; Mohd Lutfi, Mohd Khidir; Ku Mohd Yusri, Ku Ibrahim; Muhammad Naufal, Mansor (Springer Berlin Heidelberg, 2013)
      This paper presents the management of sedation in critically ill infants is a complex issue for Intensive Care Units (ICU) worldwide. Notable complications of sedation practices have been identified and efforts to modify ...

    • 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 ...

    • 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 ...

    • 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 ...

    • 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 ...

    • 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 ...

    • 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 ...

    • Objective analysis of vision impairments using single trial VEPs 

      Muthusamy, Hariharan, Dr.; Vikneswaran, Vijean; Sazali, Yaacob, Prof. Dr. (Institute of Electrical and Electronics Engineers (IEEE), 2012-02-27)
      Visually evoked potential (VEP) is an electrical signal generated by the brain (Occipital Cortex) in response to a visual stimuli. These VEP are recorded non-invasively by placing the surface electrodes at the scalp, and ...

    • Optimal selection of long time acoustic features using GA for the assessment of vocal fold disorders 

      Sindhu, Ravindran; Neoh, Siew Chin, Dr.; Muthusamy, Hariharan, Dr. (Trans Tech Publications, 2013)
      In recent times, vocal fold problems have been increasing dramatically due to unhealthy social habits and voice abuse. Non-invasive methods like acoustic analysis of voice signals can be used to investigate such problems. ...

    • 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 ...

    • A review: Malay speech recognition and audio visual speech recognition 

      C., Y. Fook; Muthusamy, Hariharan, Dr.; Sazali, Yaacob, Prof. Dr.; Abdul Hamid, Adom, Prof. Madya. Dr. (Institute of Electrical and Electronics Engineers (IEEE), 2012-02-27)
      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 ...

    • Speech stuttering assessment using sample entropy and Least Square Support Vector Machine 

      Muthusamy, Hariharan, Dr.; Vijean, Vikneswaran; Chong, Yen Fook; Sazali, Yaacob, Prof. Dr. (Institute of Electrical and Electronics Engineers (IEEE), 2012-03)
      This work is intended to discuss the performance of sample entropy feature for the recognition of stuttered events. The data for the analysis is taken from the UCLASS database. Manual segmentation is performed to identify ...

    • A study of human emotional: Review 

      Nurnadia, M. Khair; Sazali, Yaacob, Prof. Dr.; Muthusamy, Hariharan, Dr.; Shafriza Nisha, Basah, Dr. (Institute of Electrical and Electronics Engineers (IEEE), 2012-02-27)
      Modeling human activities such as human robotic, and human behavior is an active research involving multidisciplinary field including biomedical engineering, biomechanics, mathematics etc. Thus is due to the fact that a ...