Browsing Sazali Yaacob, Prof. Dr. by Title

Now showing items 12-31 of 251

    • Arthroscopy Knee Reconstruction Using Virtual Reality Assisted Medical Robots 

      Sundaraj, Kenneth, Assoc. Prof. Dr.; Sazali, Yaacob, Prof. Dr. (Malaysian Invention & Design Society (MINDS), 2006)
      Located in the center of the knee the anterior cruciate ligament (ACL) is the primary stabilizer of the knee joint which is frequently injured by a twisting or pivoting movement.

    • Artificial intelligence techniques in IC chip marking 

      Muthukaruppan, Kartigayan; Nagarajan, R.; Sazali, Yaacob; Pandian, Paulraj; Mohamed Rizon, Mohamed Juhari (Kolej Universiti Kejuruteraan Utara Malaysia, 2005)
      In this paper, an industrial machine vision system incorporating Optical Character Recognition (OCR) is employed to inspect the marking on the Integrated Circuit (IC) Chips. This inspection is carried out while the ICs are ...

    • 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 ...

    • Asymmetric ratio and FCM based salient channel selection for human emotion detection using EEG 

      Mohamad Rizon, Mohamed Juhari; Murugappan, M.; Ramachandran, Nagarajan; Sazali, Yaacob (World Scientific abd Engineering Academy and Scoiety (WSEAS), 2008)
      Electroencephalogram (EEG) is one of the most reliable physiological signals used for detecting the emotional states of human brain. We propose Asymmetric Ratio (AR) based channel selection for human emotion recognition ...

    • 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 ...

    • Auditory wavelet packet filters for multistyle classification of speech under stress 

      Nurul Aida Amira, Johari; Hariharan, Muthusamy, Dr.; Sazali, Yaacob, Prof. Dr.; Vijean, Vikneswaran (IEEE Conference Publications, 2011-11)
      Nowadays, people are having high stress level due to high workload stress, emergency phone call and multitasking. Emotional/stress of a person affect his/her performance in daily life and speech production. The research ...

    • 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 ...

    • 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 prolongations and repetitions using LPCC 

      Chee, L. S.; Ooi, Chia Ai; Hariharan, M.; Sazali, Yaacob, Prof. Dr. (Institute of Electrical and Elctronics Engineering (IEEE), 2009-12-14)
      Stuttering is a speech disorder in which the normal flow of speech is disrupted by occurrences of dysfluencies, such as repetitions, interjection and so on. There are high proportion of repetitions and prolongations in ...

    • 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 ...

    • Automatic Stuttering Recognition Tool 

      Ooi, Chia Ai; Muthusamy, Hariharan; Lim, Sim Chee; Sazali, Yaacob, Prof. Dr. (Universiti Malaysia Perlis, 2010-01-07)
      An automatic stuttering recognition system is developed to count and classy the two types of dysfuencies (repetition and prolongation) automatically.

    • 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 ...

    • 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 ...