List of Publication by tag - National Autism Resource Centre (NARC)

List of Publications

There are numbers of autism related research can be found in Malaysia that generally focus on the ASD, learning disorder, communication aids, therapy and many more. The list of publications is provided below:

How to search Publication using Text Search

Click this to search using keyword determined by the user.
It will lead to a new web page with a text search box.
Type your keyword in the search box

How to Search Publication using Keyword

Click on Keyword to search for any publication. Bigger words indicate the most used tags and smaller words indicate the least used.
Click on dropdown buttons to choose any years, types of publications or authors of your choice.
Click on underlined words in the publication detail to view more information.

Adolescent Adult Animals Anthropomorphic Robots Anxiety Article Assistive Technology Attention Attention Deficit Disorder Autism Autism Spectrum Disorders Autistic Children Biomedical Engineering Brain Caregiver Case Report Child Development Disorders Children Children with Autism Classification (of information) Clinical Article Cognition Communication Communication Skills Computer Aided Instruction Controlled Study Cross-Sectional Study Developmental Disorders Diagnosis Disease Severity Diseases Down Syndrome E-learning Early Intervention Education Electroencephalogram Electroencephalography Emotion Epilepsy Facial Expression Family Feature Extraction Female Gait Analysis Gene Genetics Health Care Human Human Computer Interaction Human Robot Interaction Humanoid Robot Humanoid Robot NAO Infant Intellectual Impairment Intelligent Control Learning Learning Disorder Major Clinical Study Malaysia Male Manufacture Mental Disorders Mental Health Middle Aged Mobile Applications Nonhuman Parents Pathophysiology Patient Rehabilitation Phenotype Physiology Preschool Preschool Child Priority Journal Procedures Psychology Quality of Life Questionnaires Research Review Robotics Robots Schizophrenia School Child Serious Games Signal Processing Smart Sensors Social Behaviour Social Communications Social Interactions Social Skills Special Education Statistics Students Surveys Teaching Unclassified Drug User Interfaces Visual Perception Young Adult

Show all

2013

Selvaraj, J; Murugappan, M; Wan, K; Yaacob, S

Classification of emotional states from electrocardiogram signals: A non-linear approach based on hurst Journal Article

BioMedical Engineering Online, 12 (1), 2013, ISSN: 1475925X, (cited By 42).

Abstract | Links | BibTeX | Tags: Adolescent, Adult, Aged, Article, Audio-Visual Stimulus, Autonomous Nervous Systems, Children, Classification Accuracy, Computer Based Training, Computer-Assisted, Electrocardiogram Signal, Electrocardiography, Emotion, Female, Fuzzy K-nearest Neighbor, Higher-Order Statistic (HOS), Human, Intellectual Disability, Interactive Computer Systems, Methodology, Middle Aged, Nonlinear Dynamics, Nonlinear System, Procedures, Real Time Systems, Signal Processing, Statistics, Young Adult

@article{Selvaraj2013,
title = {Classification of emotional states from electrocardiogram signals: A non-linear approach based on hurst},
author = {J Selvaraj and M Murugappan and K Wan and S Yaacob},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84879017985&doi=10.1186%2f1475-925X-12-44&partnerID=40&md5=18c5309ac9f3017f455480f1ff732a30},
doi = {10.1186/1475-925X-12-44},
issn = {1475925X},
year = {2013},
date = {2013-01-01},
journal = {BioMedical Engineering Online},
volume = {12},
number = {1},
publisher = {BioMed Central Ltd.},
abstract = {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) signals, being an activity of the autonomous nervous system (ANS), reflect the underlying true emotional state of a person. However, the performance of various methods developed so far lacks accuracy, and more robust methods need to be developed to identify the emotional pattern associated with ECG signals.Methods: Emotional ECG data was obtained from sixty participants by inducing the six basic emotional states (happiness, sadness, fear, disgust, surprise and neutral) using audio-visual stimuli. The non-linear feature 'Hurst' was computed using Rescaled Range Statistics (RRS) and Finite Variance Scaling (FVS) methods. New Hurst features were proposed by combining the existing RRS and FVS methods with Higher Order Statistics (HOS). The features were then classified using four classifiers - Bayesian Classifier, Regression Tree, K- nearest neighbor and Fuzzy K-nearest neighbor. Seventy percent of the features were used for training and thirty percent for testing the algorithm.Results: Analysis of Variance (ANOVA) conveyed that Hurst and the proposed features were statistically significant (p < 0.001). Hurst computed using RRS and FVS methods showed similar classification accuracy. The features obtained by combining FVS and HOS performed better with a maximum accuracy of 92.87% and 76.45% for classifying the six emotional states using random and subject independent validation respectively.Conclusions: The results indicate that the combination of non-linear analysis and HOS tend to capture the finer emotional changes that can be seen in healthy ECG data. This work can be further fine tuned to develop a real time system. © 2013 Selvaraj et al.; licensee BioMed Central Ltd.},
note = {cited By 42},
keywords = {Adolescent, Adult, Aged, Article, Audio-Visual Stimulus, Autonomous Nervous Systems, Children, Classification Accuracy, Computer Based Training, Computer-Assisted, Electrocardiogram Signal, Electrocardiography, Emotion, Female, Fuzzy K-nearest Neighbor, Higher-Order Statistic (HOS), Human, Intellectual Disability, Interactive Computer Systems, Methodology, Middle Aged, Nonlinear Dynamics, Nonlinear System, Procedures, Real Time Systems, Signal Processing, Statistics, Young Adult},
pubstate = {published},
tppubtype = {article}
}