@conference{Jamil2015342,
title = {Gait-Based Emotion Detection of Children with Autism Spectrum Disorders: A Preliminary Investigation},
author = {N Jamil and N H M Khir and M Ismail and F H A Razak},
editor = {Miskon M F Yussof H.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84962833568&doi=10.1016%2fj.procs.2015.12.305&partnerID=40&md5=6893678f1ed83b87147ff9183b94428b},
doi = {10.1016/j.procs.2015.12.305},
issn = {18770509},
year = {2015},
date = {2015-01-01},
journal = {Procedia Computer Science},
volume = {76},
pages = {342-348},
publisher = {Elsevier B.V.},
abstract = {With the disturbing increase of children with Autism Spectrum Disorder (ASD) in Malaysia, a lot of efforts and studies are put forward towards understanding and managing matters related to ASD. One way is to find means of easing the social communications among these children and their caretakers, particularly during intervention. If the caretaker is able to comprehend the children emotional state of mind prior to therapy, some sort of trust and attachment will be developed. However, regulating emotions is a challenge to these children. Nonverbal communication such as facial expression is difficult for ASD children. Therefore, we proposed the use of walking patterns (i.e. gait) to detect the type of emotions of ASD children. Even though using gait for emotion recognition is common among normal individuals, none can be found done on children with ASD. Thus, the aim of this paper is to conduct a preliminary review on the possibilities of carrying out gait-based emotion detection among ASD children with regards to the emotional types, gait parameters and methods of gait data acquisition. © 2015 The Authors.},
note = {cited By 4},
keywords = {Autism Spectrum Disorders, Children with Autism, Data Acquisition, Diseases, Emotion, Emotion Detection, Emotion Recognition, Emotional State, Facial Expression, Gait Analysis, Intelligent Control, Nonverbal Communication, Pattern Recognition, Robotics, Smart Sensors, Social Communications, Speech Recognition},
pubstate = {published},
tppubtype = {conference}
}

@conference{Othman2010315,
title = {Understanding autistic children perception through EEG},
author = {M Othman and A Wahab},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84883660524&partnerID=40&md5=df9dac75053fbfa693b4823d5a0a77ad},
isbn = {9781617820267},
year = {2010},
date = {2010-01-01},
journal = {23rd International Conference on Computer Applications in Industry and Engineering 2010, CAINE 2010 - Including SNA 2010 Workshop},
pages = {315-320},
abstract = {Autistic children are known as having difficulties understanding human's facial expressions, making them incapable of interpreting the emotional states of others. This paper seeks to understand autistic children perception by analyzing brain signals using MFCC and MLP. An empirical study was conducted on 6 autistic and 6 typically developing children. Subjects' brainwaves were monitored while watching calm, happy and sad faces. Experimental results show that it is possible to discriminate the emotions of autistic children against control subjects with the accuracy of 76.61%. Brainwaves of autistic children also showed the trend of reversed emotions compared to normal children while watching happy and sad faces.},
note = {cited By 0},
keywords = {Autism Spectrum Disorders, Autistic Children, Behavioral Research, Children with Autism, Computer Applications, Control Subject, Electroencephalography, Emotion, Emotional State, Empirical Studies, Facial Expression, Mel Frequency Cepstral Coefficients, Multilayer-Percheptron (MLP), Speech Recognition},
pubstate = {published},
tppubtype = {conference}
}