Browsing Sazali Yaacob, Prof. Dr. by Author "murugappan@unimap.edu.my"

Now showing items 1-14 of 14

    • Classification of emotional States from electrocardiogram signals: a non-linear approach based on hurst 

      Selvaraj, Jerritta; Murugappan, M., Dr.; Wan Khairunizam, Wan Ahmad, Dr.; Sazali, Yaacob, Prof. Dr. (BioMed Central, 2013-05)
      Background: Identifying the emotional state is helpful in applications involving patients with autism and other intellectual disabilities; computer-based training, human computer interaction etc. Electrocardiogram (ECG) ...

    • Combining spatial filtering and wavelet transform for classifying human emotions using EEG Signals 

      Murugappan; Nagarajan, Ramachandran, Prof. Dr.; Sazali, Yaacob, Prof. Dr. (Biomedical Engineering Society of the R.O.C., 2011)
      In this paper, we present human emotion assessment using electroencephalogram (EEG) signals. The combination of surface Laplacian (SL) filtering, time-frequency analysis of wavelet transform (WT) and linear classifiers are ...

    • 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 ...

    • 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 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 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 ...

    • FCM clustering of emotional stress using ECG features 

      Zheng, Bong Siao; Murugappan, M., Dr.; Sazali, Yaacob, Prof. Dr. (IEEE Conference Publications, 2013-04)
      Emotional stress refers to the inducement of stress due to the consequence of a continuous experience of negative emotions (sad, anger, fear and disgust). This work aims to investigate the effect of negative emotions in ...

    • Frequency study of facial electromyography signals with respect to emotion recognition 

      Selvaraj, Jerritta; Murugappan, Muthusamy, Dr.; Wan Khairunizam, Wan Ahmad, Dr.; Sazali, Yaacob, Prof. Dr. (Walter de Gruyter GmbH, 2014-01)
      Emotional intelligence is one of the key research areas in human-computer interaction. This paper reports the development of an emotion recognition system using facial electromyogram (EMG) signals focusing the ambiguity ...

    • Human emotional stress assessment through Heart Rate Detection in a customized protocol experiment 

      Zheng, Bong Siao; Murugappan, M., Dr.; Sazali, Yaacob, Prof. Dr. (IEEE Conference Publications, 2012-09)
      Continuous existence of negative emotions (disgust, anger, fear and sad) over a longer period of time induces emotional stress. This emotional stress can be analyzed through physiological signal characteristics such as ...

    • Lifting scheme for human emotion recognition using EEG 

      Murugappan, M., Dr.; Mohd Rizon, Mohamed Juhari; Nagarajan, Ramachandran, Prof. Dr.; Sazali, Yaacob, Prof. Dr.; Ibrahim, Zunaidi; Hazry, Desa, Assoc. Prof. Dr. (IEEE Conference Publications, 2008-08)
      In recent years, the need and importance of automatically recognizing emotions from EEG signals has grown with increasing role of brain computer interface applications. The detection of fine grained changes in functional ...

    • Mathematical modeling of human body for lifting task 

      Ku Nor Syamimi, Ku Ismail; Shafriza Nisha, Basah, Dr.; Nur Hidayah, Omar; Sazali, Yaacob, Prof. Dr.; Murugappan, Muthusamy, Dr. (IEEE Conference Publications, 2012)
      Physical lifting tasks commonly involve to types of body postures, namely, squat lifting and stoop lifting. Studies shows improper body posture during lifting task has detrimental effect to human lower-back region over ...

    • Methods and approaches on inferring human emotional stress changes through physiological signals: A review 

      Bong, Siao Zheng; Murugappan, Muthusamy, Dr.; Sazali, Yaacob, Prof. Dr. (Inderscience Enterprises Ltd, 2013)
      Emotional stress is kind of stressful state which is developed due to the continuous occurrence of negative emotions such as sad, disgust, angry and fear over a long period of time. In this work, a detailed investigation ...

    • Multiple physiological signal-based human stress identification using non-linear classifiers 

      Karthikeyan, Palanisamy; Murugappan, Muthusamy, Dr.; Sazali, Yaacob, Prof. Dr. (2013)
      This paper describes the human stress identification using multiple physiological signals. The Electrocardiogram (ECG), Electromyogram (EMG), Heart Rate Variability (HRV), Galvanic Skin Response (GSR), and Skin Temperature ...