@article{ISI:000444996500092,
title = {A Review on Using Assistive Technology to Enhance Social Skills Competence Among Children with Autism Spectrum Disorder (ASD)},
author = {Zuraida Ibrahim and Maizam Alias},
doi = {10.1166/asl.2018.11582},
issn = {1936-6612},
year = {2018},
date = {2018-06-01},
journal = {ADVANCED SCIENCE LETTERS},
volume = {24},
number = {6},
pages = {4250-4254},
publisher = {AMER SCIENTIFIC PUBLISHERS},
address = {26650 THE OLD RD, STE 208, VALENCIA, CA 91381-0751 USA},
organization = {Univ Teknologi Malaysia, Int Student Soc; Int Students Ctr; Univ Teknologi Malaysia, Inst Sultan Iskandar},
abstract = {This paper is intended to explore published reports, journals and
articles concerning the implementation of Special Education in Malaysia.
The literature review targets the Malaysian education system, focusing
on students with special education need (SEN); in particular students
with Autism Spectrum Disorder (ASD) in an attempt to describe the
current state of understanding on current issues and gaps that lies
within them. Specifically, the objectives of this review are to (a)
identify effective intervention for ASD children, (b) identify
appropriate domains for social skills competence, and (c) to make
suggestions for future research. A narrative review was conducted on
available literature to provide the explanations on existing knowledge
related to the Malaysian education system, special education, ASD,
teaching and learning approach for ASD children and effective
intervention for ASD children. The findings from the narrative review
indicate that inadequate social interaction is the main factor
contributing to social skills deficit in ASD children in special
education. The skills deficit consequently leads to problems with
educators, peers, incompetence for independent living and lack of
acceptance by society. The majority of literature makes recommendations
on the implementation of assistive technology for skills enhancement.
Furthermore, social interaction, social communication, social emotional
and social behaviour were identified as domains for social skills
competence in ASD children. Overall, the finding from the narrative
review provides some support for conducting future research on the
implementation of assistive technology in early intervention to enhance
the teaching and learning process of social skills competence among ASD
children.},
note = {International Conference on Science, Engineering, Management and Social
Sciences (ICSEMSS), Univ Teknologi Malaysia, Johor Bahru, MALAYSIA, OCT
06-08, 2016},
keywords = {Assistive Technology, Autism Spectrum Disorders, Early Intervention, Social Skills Competence},
pubstate = {published},
tppubtype = {article}
}

@article{Hashim2013567,
title = {Robot-assisted to elicit behaviors for autism screening},
author = {H Hashim and H Yussof and F A Hanapiah and S Shamsuddin and L Ismail and N A Malik},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84886257860&doi=10.4028%2fwww.scientific.net%2fAMM.393.567&partnerID=40&md5=9ef0b91be1f79ae1771901b04e271636},
doi = {10.4028/www.scientific.net/AMM.393.567},
issn = {16609336},
year = {2013},
date = {2013-01-01},
journal = {Applied Mechanics and Materials},
volume = {393},
pages = {567-572},
abstract = {Early screening and diagnosis of Autism spectrums is essential to determine the best means of early intervention program. Since there is no sign in biological for autism, screening and assessment must focus on the behavioral deficits. Somehow screening is not a diagnosis, but a filter that picks out children for subsequent assessment. The aim of this paper is to propose and to ignite discussion concerning robotic assisted in autism screening process to enable early diagnosis and intervention. This process combines (a) selection of an autism screening tool (b) refinement of screening subscales and (c) integration of subscales with robot action. We use Gilliam Autism Rating Scale-2 (GARS-2) inversely integrated with humanoid robot Nao to produce a counter action to elicit individual behaviours for screening and diagnosis purposes. In extracting of GARS-2, we had considered the limitation and sensitivity when a robot tries to assist in the process of screening and diagnosis. Integrating robotics into innovative treatments however highlighted the need for additional rigorous empirical studies with quantitative measurement. © (2013) Trans Tech Publications, Switzerland.},
note = {cited By 2},
keywords = {Anthropomorphic Robots, Autism Spectrum Disorders, Diseases, Early Intervention, Humanoid Robot, Humanoid Robot NAO, Individual Behaviour, Intervention, Mechanical Engineering, Program Diagnostics, Quantitative Measurement, Robotics, Screening Process},
pubstate = {published},
tppubtype = {article}
}

@article{Shams2012372,
title = {Fuzzy model for detection and estimation of the degree of autism spectrum disorder},
author = {W K Shams and A Wahab and U A Qidwai},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84869038189&doi=10.1007%2f978-3-642-34478-7_46&partnerID=40&md5=98929aba468010a02f652994b0da2a54},
doi = {10.1007/978-3-642-34478-7_46},
issn = {03029743},
year = {2012},
date = {2012-01-01},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
volume = {7666 LNCS},
number = {PART 4},
pages = {372-379},
abstract = {Early detection of autism spectrum disorder (ASD) is of great significance for early intervention. Besides, knowing the degree of severity in ASD and how it changes with the intervention is imperative for the treatment process. This study proposes Takagi- Sugeno-Kang (TSK) fuzzy modeling approach that is based on subtractive clustering to classify autism spectrum disorder and to estimate the degree of prognosis. The study has been carried out using Electroencephalography (EEG) signal on two groups of control and ASD children age-matched between seven to nine years old. EEG signals are quantized to temporal-time domain using Short Time Frequency Transformation (STFT). Spectrum energy is extracted as features for alpha band. The proposed system is modeled to estimate the degree in which subject is autistic, normal or uncertain. The results show accuracy in range (70-97) % when using fuzzy model .Also this system is modeled to generate crisp decision; the results show accuracy in the range (80-100) %. The proposed model can be adapted to help psychiatrist for diagnosis and intervention process. © 2012 Springer-Verlag.},
note = {cited By 2},
keywords = {Autism Spectrum Disorders, Classification (of information), Data Processing, Detection and Estimation, Diseases, Early Intervention, EEG Signals, Electrophysiology, Fuzzy Approach, Fuzzy Modeling, Spectrum Energy, Subtractive Clustering, Time-Frequency Transformation, Treatment Process},
pubstate = {published},
tppubtype = {article}
}

@article{Kuan20101022,
title = {Development of an effective assessment and training support system for cognitive ability for special children},
author = {T M Kuan and E Supriyanto and Y K Jiar and Y E Han},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-77958107712&partnerID=40&md5=2ec5c3ecbb54c2ebde0e55834dd2ae56},
issn = {11092750},
year = {2010},
date = {2010-01-01},
journal = {WSEAS Transactions on Computers},
volume = {9},
number = {9},
pages = {1022-1031},
abstract = {In definition, special children include children who are having Down syndrome, autism, global delay, epilepsy, slow learner and others. In this study, the special children are focused on children with Down syndrome. Down syndrome occurs due to an extra copy of chromosome 21 in the children's chromosome. Early intervention Program (EIP) is a systematic program with therapy, exercises, and activities which designed to help children especially special children. Cognitive development is the construction of thought processes, which is one of the most important skills that have to be developed for Down syndrome children in order to lead a normal life. This support system is focused mainly to help them improving their logical thinking and memory skills. This cognitive assessment and training support system utilizes the radio frequency identification (RFID) technology implemented in C Sharp programming language. The completed system was then tested and feedback was obtained from parents or trainers of Down syndrome children. The results show that the system can generate results in graphical form stably and training for improving the cognitive ability of the children is reliable based on global recognized curriculum. In conclusion, the system can be used in order to help trainers or parents to improve the cognitive ability of children with Down syndrome.},
note = {cited By 0},
keywords = {Assessment and Training, Chromosomes, Cognitive Ability, Curricula, Early Intervention, Radio Frequency Identification (RFID), RFID, Special Children, Support System},
pubstate = {published},
tppubtype = {article}
}