Browsing M. Murugappan, Dr. by Title

Now showing items 9-28 of 67

    • Descriptive analysis of skin temperature variability of sympathetic nervous system activity in stress 

      Karthikeyan, Palanisamy; Murugappan, M., Dr.; Sazali, Yaacob, Prof. Dr. (Society of Physical Therapy Science, 2012-12)
      [Purpose] Stress is a common factor of several diseases. Stress can be reduced through appropriate stress management and relaxation methods. In this study, variation in skin temperature (ST) was investigated as a primary ...

    • Detecting driver drowsiness based on sensors-a review 

      Sahayadhas, Arun; Sundaraj, Kenneth, Prof. Dr.; Murugappan, M (Multidisciplinary Digital Publishing Institute (MDPI), 2012)
      In recent years, driver drowsiness has been one of the major causes of road accidents and can lead to severe physical injuries, deaths and significant economic losses. Statistics indicate the need of a reliable driver ...

    • Detection of human stress using short-term ECG and HRV signals 

      Karthikeyan, Palanisamy; Murugappan, Muthusamy, Dr.; Sazali, Yaacob, Prof. Dr. (World Scientific Publishing Company, 2013-04)
      This paper introduces a method for resolving the problem of human stress detection through short-term (less than 5 min) electrocardiogram (ECG) and heart rate variability (HRV) signals. The explored methodology helps to ...

    • Development of cost effective ECG data acquisition system for clinical applications using LabVIEW 

      Murugappan, M., Dr.; Thirumani, Reena; Mohammad Iqbal, Omar@Ye Htut, Assoc. Prof. Dr.; Murugappan, Subbulakshmi (IEEE Conference Publications, 2014-03)
      The main objective of this work is to develop a portable and cost effective data acquisition (DAQ) system for clinical applications. This DAQ consists of several modules such as power supply, analog to digital converter ...

    • Development of Discrete Wavelet Transform (DWT) toolbox for signal processing applications 

      Mousa K., Wali; Murugappan, M., Dr.; R. Badlishah, Ahmad, Assoc. Prof. Dr.; Bong, Siao Zheng (Institute of Electrical and Electronics Engineers (IEEE), 2012-02-27)
      Discrete Wavelet Transform (DWT) plays a significant role in several image and signal processing applications. Most of the researchers are using different wavelet toolboxes for their application and research investigation. ...

    • Development of EEG data acquisition device by using single board computer 

      Wali, Mousa Kadhim; Murugappan, M., Dr.; R. Badlishah, Ahmad, Prof. Dr. (Inderscience Enterprises Ltd., 2013)
      Electroencephalogram (EEG) plays a vital role in several medical diagnosis (brain tumour detection, Alzheimer disease, epilepsy, etc.), engineering applications (emotion detection, drowsiness detection, stress assessment, ...

    • Development of EEG data acquisition device by using TS7800 Single Board Computer (SBC) 

      Mousa K. Wali; Murugappan, M., Dr.; R. Badlishah, Ahmad, Assoc. Prof. Dr. (Universiti Malaysia Perlis (UniMAP)School of Mechatronic Engineering, 2012-02-27)
      Electroencephalogram (EEG) plays a vital role in several medical diagnosis (brain tumor detection, Alzheimer disease, epilepsy, etc), engineering applications (emotion detection, drowsiness detection, stress assessment, ...

    • Driver inattention detection methods: a review 

      Sahayadhas, Arun; Sundaraj, Kenneth, Prof. Dr.; Murugappan, M (IEEE Conference Publications, 2012)
      In recent years, driver inattention or distraction is one of the major causes for road accidents. If the distracted driver is alerted on time, most of the physical injuries, deaths, and economic losses can be avoided. To ...

    • Drowsiness detection during different times of day using multiple features 

      Sahayadhas, Arun; Sundaraj, Kenneth, Prof. Dr.; Murugappan, M (Springer Netherlands, 2013)
      Driver drowsiness has been one of the major causes of road accidents that lead to severe trauma, such as physical injury, death, and economic loss, which highlights the need to develop a system that can alert drivers of ...

    • DWT and MFCC based human emotional speech classification using LDA 

      Murugappan, Muthusamy, Dr.; Nurul Qasturi Idayu, Baharuddin; Jeritta, S (Institute of Electrical and Electronics Engineers (IEEE), 2012-02-27)
      Recent years, identification of gender based on emotional speech is one of the active research areas in developing intelligent human machine interactive (HMI) systems and biometric system. This work aims to identify the ...

    • Early predictionof cardiovascular diseases using ECG signal: A review 

      Nurul Hikmah, Kamaruddin; Murugappan, Muthusamy, Dr.; Mohd Iqbal, Omar, Assoc. Prof. Dr. (Universiti Malaysia Perlis (UniMAP), 2012-06-18)
      Electrocardiography is considered a representative signal of cardiac physiology. ECG signal analysis can provide lots of information about heart condition whether it is normal and abnormal. Cardiovascular Disease (CVD) is ...

    • ECG signals based mental stress assessment using wavelet transform 

      Karthikeyan, Palanisamy; Murugappan, M., Dr.; Sazali, Yaacob, Prof. Dr. (IEEE Conference Publications, 2011-11)
      This paper describes the mental stress assessment using Electrocardiography (ECG) signal. Stress reflects the changes in heart rates under stressful situation. In this work, Heart Rate Variability (HRV) from ECG signal is ...

    • EEG dynamics in neurological disorders: Parkinson's disease and stroke 

      Yuvaraj, Rajamanickam; Murugappan, M; Sundaraj, Kenneth, Prof. Dr. (IEEE Conference Publications, 2012)
      The electroencephalogram (EEG) signals provide oscillatory dynamics and valuable information about brain function. In fact, this permits the detection of changes in neurological state which are especially useful in the ...

    • Electromyogram signal based human emotion classification using KNN and LDA 

      Murugappan, M., Dr. (IEEE Conference Publications, 2011-06)
      In this paper, we presents Electromyogram (EMG) signal based human emotion classification using K Nearest Neighbor (KNN) and Linear Discriminant Analysis (LDA). Five most dominating emotions such as: happy, disgust, fear, ...

    • EMG signal based human stress level classification using wavelet packet transform 

      Karthikeyan, Palanisamy; Murugappan, M., Dr.; Sazali, Yaacob, Prof. Dr. (Springer-Verlag, 2012)
      Recent days, Electromyogram (EMG) signal acquired from muscles can be useful to measure the human stress levels. The aim of this present work to investigate the relationship between the changes in human stress levels to ...

    • Emotion classification in Parkinson's disease by higher-order spectra and power spectrum features using EEG signals: a comparative study 

      Yuvaraj, Rajamanickam; Murugappan, M., Dr.; Norlinah, Mohamed Ibrahim; Mohammad Iqbal, Omar@Ye Htut, Assoc. Prof. Dr.; Sundaraj, Kenneth, Prof. Dr.; Khairiyah, Mohamad; Palaniappan, Ramaswamy; Satiyan, Marimuthu (World Scientific Publishing Co. Pte Ltd, 2014-03)
      Deficits in the ability to process emotions characterize several neuropsychiatric disorders and are traits of Parkinson's disease (PD), and there is need for a method of quantifying emotion, which is currently performed ...

    • Emotion detection from QRS complex of ECG signals using hurst exponent for different age groups 

      Selvaraj, Jerritta; Murugappan, M., Dr.; Wan Khairunizam, Wan Ahmad, Dr.; Sazali, Yaacob, Prof. Dr. (IEEE Conference Publications, 2013-09)
      Emotion recognition using physiological signals is one of the key research areas in Human Computer Interaction (HCI). In this work, we identify the six basic emotional states (Happiness, sadness, fear, surprise, disgust ...

    • Emotion processing in Parkinson's disease: an EEG spectral power study 

      Yuvaraj, Rajamanickam; Murugappan, M; Mohd Iqbal, Omar@Ye Htut, Assoc. Prof. Dr.; Norlinah, Mohamed Ibrahim; Sundaraj, Kenneth, Prof. Dr.; Khairiyah, Mohamad; Satiyan, M (Informa Healthcare, 2013)
      Objective: Although an emotional deficit is a common finding in Parkinson's disease (PD), its neurobiological mechanism on emotion recognition is still unknown. This study examined the emotion processing deficits in PD ...

    • Emotion recognition from electrocardiogram signals using Hilbert Huang Transform 

      Selvaraj, Jerritta; Murugappan, M., Dr.; Wan Khairunizam, Wan Ahmad, Dr.; Sazali, Yaacob, Prof. Dr. (IEEE Conference Publications, 2012-10)
      Equipping robots and computers with emotional intelligence is becoming important in Human-Computer Interaction (HCI). Bio-signal based methods are found to be reliable and accurate than conventional methods as they directly ...

    • Emotion recognition from facial EMG signals using higher order statistics and principal component analysis 

      Selvaraj, Jerritta; Murugappan, Muthusamy, Dr.; Wan Khairunizam, Wan Ahmad, Dr.; Sazali, Yaacob, Prof. Dr. (Taylor & Francis, 2014-04)
      Higher order statistics (HOS) is an efficient feature extraction method used in diverse applications such as bio signal processing, seismic data processing, image processing, sonar, and radar. In this work, we have ...