@conference{Rusli2016274,
title = {Hottest pixel segmentation based thermal image analysis for children},
author = {N Rusli and H M Yusof and S N Sidek and M H Latif},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015712176&doi=10.1109%2fIECBES.2016.7843457&partnerID=40&md5=847e69c597caab24e0cd0f4e2cf558c6},
doi = {10.1109/IECBES.2016.7843457},
isbn = {9781467377911},
year = {2016},
date = {2016-01-01},
journal = {IECBES 2016 - IEEE-EMBS Conference on Biomedical Engineering and Sciences},
pages = {274-279},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {In this paper, the first order statistics for gray level intensity defined from thermal image is implemented to govern the significant and distinguishable characteristic pattern in thermal image of affective states. The impact of thresholding mechanism is studied to differentiate between positive affective states (happy) and negative affective states (sad) analysis in response to the stimuli adopted from International Affective Pictures System (IAPS) database. The hottest pixel segmentation technique is applied where it identifies the threshold level in a way to classify the hottest pixel area. The region of interest is narrowed to a forehead region with result of separation analysis made to left and right area. Two experiments have been conducted by using different set of stimuli and the results depicts of asymmetry and differed in culmination pattern for these two affective states. This conclusive result from this study suggests that this feature can be used as one of the important feature to give information of affective states on individuals with autism spectrum disorder (ASD) with least of facial expressions and perhaps would-be use in non-verbal means. © 2016 IEEE.},
note = {cited By 0},
keywords = {Affective State, Autism Spectrum Disorders, Biomedical Engineering, Diseases, Feature Extraction, First-Order Statistics, Forehead Region, Gray Level Intensity, Image Analysis, Image Segmentation, Pixels, Segmentation Techniques, Thermal Image Analysis, Thermal Images},
pubstate = {published},
tppubtype = {conference}
}

@conference{Rusli2016226,
title = {Non-invasive assessment of affective states on individual with autism spectrum disorder: A review},
author = {N B Rusli and S N Sidek and H Md Yusof and M H Abd Latif},
editor = {Ahmad Usman M Y J Ibrahim F. Mohktar M.S.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84952767451&doi=10.1007%2f978-981-10-0266-3_47&partnerID=40&md5=f4aafb2216ef5c9d03ae7a1db352e4bd},
doi = {10.1007/978-981-10-0266-3_47},
issn = {16800737},
year = {2016},
date = {2016-01-01},
journal = {IFMBE Proceedings},
volume = {56},
pages = {226-230},
publisher = {Springer Verlag},
abstract = {Individuals with Autism Spectrum Disorder (ASD) are identified as a group of people who have social interaction and communication impairment. They have difficulty in producing speech and explaining what they meant. They also suffer from emotional or cognitive states requirement that stance challenges to their interest in communicating and socializing. Hence, it is vital to know their emotion to help them develop better skills in social interaction. Emotion can be derived from affective states and can be detected through physical reaction and physiological signals. There are numerous known modalities available to detect the affective states either through invasive and non-invasive methods. In order to evaluate the affective states of individuals with ASD, amongst the methods used are through electrodermal activity (EDA), electromyographic (EMG) activity, and cardiovascular activity (ECG) and blood flow analyses. Though considered non invasive, these methods require sensor to be patched on to the skin causing discomfort to the subjects and might distract their true emotion. We propose non-invasive methods which is also contactless to address the problem to detect emotion of individual with ASD that is through thermal imaging. Through the impact of cutaneous temperature in blood flow, thermal imprint is radiated and can be detected in this method. To date, no research has been reported of the use of thermal imaging analysis of facial skin temperature on the individuals with ASD. In this paper we will justify the method and also discuss the merits and demerits of other methods. © International Federation for Medical and Biological Engineering 2016.},
note = {cited By 1},
keywords = {Affective State, Autism, Biomedical Engineering, Blood, Diseases, Emotion, Facial Expression, Hemodynamics, Infrared Imaging, Noninvasive Medical Procedures, Physiological Signals, Physiology, Signal Detection, Skin, Social Sciences},
pubstate = {published},
tppubtype = {conference}
}