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:

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

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2015

Isa, N R M; Yusoff, M; Khalid, N E; Tahir, N; Nikmat, Binti A W

Autism severity level detection using fuzzy expert system Conference

Institute of Electrical and Electronics Engineers Inc., 2015, ISBN: 9781479957651, (cited By 2).

Abstract | Links | BibTeX | Tags: Autism, Autism Severity Level, Autistic Children, Children with Autism, Data Acquisition, Developmental Disorders, Diseases, Education, Expert Systems, Fuzzy Expert Systems, Level Detections, Manufacture, Robotics, Social Communications, Surveys, System Architectures, Teaching

@conference{Isa2015218,
title = {Autism severity level detection using fuzzy expert system},
author = {N R M Isa and M Yusoff and N E Khalid and N Tahir and A W Binti Nikmat},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84959503922&doi=10.1109%2fROMA.2014.7295891&partnerID=40&md5=63e742d59b785d14f87d98dac7dd71ee},
doi = {10.1109/ROMA.2014.7295891},
isbn = {9781479957651},
year = {2015},
date = {2015-01-01},
journal = {2014 IEEE International Symposium on Robotics and Manufacturing Automation, IEEE-ROMA2014},
pages = {218-223},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {Autism is a neuro developmental disorder that is recently well known among Malaysian. Many researches on autism detection have been conducted worldwide. However, there is lack of research conducted in detecting autism severity level. Therefore, this paper focuses on autism severity level detection using fuzzy expert system. Two main autistic behavioral criteria are selected which are social communication impairment and restricted repetitive behavior. Data acquisition was based on interview sessions with clinical psychologist and distribution of 36 questionnaires to teachers and parents that have autistic children. It was then analyzed and the cut off points for each severity level; level 1 (mild), level 2 (moderate), and level 3 (severe) is determined. The fuzzy expert system processes are employed to detect the severity levels. The processes involve Fuzzy system architecture, fuzzification, rules evaluation, rules evaluation and defuzzification. The finding demonstrates that the system is able to detect autism severity level with a good accuracy. This system also accommodates with suitable recommendation based on the generated result whether the suggestion is to go for speech therapy or behavior therapy. © 2014 IEEE.},
note = {cited By 2},
keywords = {Autism, Autism Severity Level, Autistic Children, Children with Autism, Data Acquisition, Developmental Disorders, Diseases, Education, Expert Systems, Fuzzy Expert Systems, Level Detections, Manufacture, Robotics, Social Communications, Surveys, System Architectures, Teaching},
pubstate = {published},
tppubtype = {conference}
}

2009

Yusoff, Mohd N; Wahab, Abdul M H; Aziz, M A; AshaÁri, Jalil F

ESSE: Learning disability classification system for autism and dyslexia Journal Article

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5614 LNCS (PART 1), pp. 395-402, 2009, ISSN: 03029743, (cited By 2).

Abstract | Links | BibTeX | Tags: Autism, Centralized Decision Making, Classification System, Decision Making, Errors, Expert Systems, Human Computer Interaction, Human Errors, Knowledge Engineering, Knowledge Management, Knowledge-Based Classification, Learning Disorder, Malaysia, Special Education, Teaching

@article{MohdYusoff2009395,
title = {ESSE: Learning disability classification system for autism and dyslexia},
author = {N Mohd Yusoff and M H Abdul Wahab and M A Aziz and F Jalil AshaÁri},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-76249116153&doi=10.1007%2f978-3-642-02707-9_45&partnerID=40&md5=f51c6dd35a86b7eef7ee117d1daa41dd},
doi = {10.1007/978-3-642-02707-9_45},
issn = {03029743},
year = {2009},
date = {2009-01-01},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
volume = {5614 LNCS},
number = {PART 1},
pages = {395-402},
abstract = {This paper presents an Expert System for Special Education (ESSE) based on scenario in Malaysia. This system is developed through the process of knowledge-gaining which is gathered from various expertise in chosen domain. Realizing the limitation of traditional classification system that teachers adopted, we developed ESSE to automate a centralized decision making system. ESSE is also able to provide consistent answers for repetitive decisions, processes and tasks. Besides, teachers using this system hold and maintain significant level of information pertaining both learning disabilities, thus reduce amount of human errors. ESSE knowledge-based resulted from the knowledge engineering called Qualifiers and Choice. Both are gathered from the analysis of symptoms that are experienced by Autism and Dyslexia patients. Every type of disability is divided to several categories and sub-category to facilitate question's arrangement. This paper presents a review of Expert System for Special Education (ESSE), problems arises and the knowledge-based classification systems. © 2009 Springer Berlin Heidelberg.},
note = {cited By 2},
keywords = {Autism, Centralized Decision Making, Classification System, Decision Making, Errors, Expert Systems, Human Computer Interaction, Human Errors, Knowledge Engineering, Knowledge Management, Knowledge-Based Classification, Learning Disorder, Malaysia, Special Education, Teaching},
pubstate = {published},
tppubtype = {article}
}