MIT-World Peace University (MIT-WPU) is a top educational institute located in Pune, India. It is recognized within&nbsp;UGC under Government of Maharashtra Act No. XXXV 2017.&nbsp;

It is part of the MIT group of institutions (established in 1983) which covers 10+ campuses across India and has more than 50,000+ students enrolled across various disciplines at a given point of time. The institute houses 15 schools ranging from Engineering &amp; Technology, Design, Pharmacy, Commerce, Governance among others. It offers undergraduate, postgraduate and PhD programs among different disciplines.&nbsp;

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MIT World Peace University

The Autism Spectrum Disorder (ASD) is known to be characterized by decreased social interactions to stimuli, difficulties in communication, repetitive behaviours and physical movements, unusual or severely limited interests. Since it affects different individuals differently and to different extents, it is very challenging to diagnose and differentiate from other neurodevelopmental disorders. The earlier it is diagnosed, the better it is for the individual, as an intervention protocol can be charted at the earliest. Research shows that early intervention can be very beneficial in the long term as the affected individuals' symptoms can be reduced to a great extent and in some cases they may not show up on the spectrum at all, but the lack of awareness and objective diagnostic tools makes it difficult to diagnose at an early age. The objective nature of the automated approaches to the screening of Autism Spectrum Disorder would be considered as a viable option for a second opinion and by an extension also an efficient screening process after which the patients would be referred to a therapist. Tests like eye tracking, detection of physical attributes via wearable and static IoT devices, classification on MRI scans and voice prosody detection techniques are easily reproducible and more time efficient than a one on one interview session with a therapist. In this paper we explore the various innovations made in automating the screening process. This paper lists the demerits of the subjective existing diagnosis systems and also surveys and complies the various eye gazing, voice prosody, wearable IoT modules, their contributions and their impacts in making the diagnosis process of Autism Spectral Disorder more objective and efficient. © 2020 IEEE.

School of Computer Engineering & Technology

Engineering and Technology

2020 IEEE 15th International Conference on Industrial and Information Systems, ICIIS 2020 - Proceedings

A Survey: Strategies for detection of Autism Syndrome Disorder

The texture which is in motion is known as Dynamic texture. As the texture can change in shape and direction over time, Segmentation of Dynamic Texture is a challenging task. Furthermore, features of Dynamic texture like spatial (i.e., appearance) and temporal (i.e., motion) may differ from each other. However, studies are mostly limited to characterization of single dynamic textures in the current literature. In this paper, the segmentation problem of image sequences consisting of cluttered dynamic textures is addressed. For the segmentation of dynamic texture, two local texture descriptor based techniques and Lucas-Kanade optical flow technique are combined together to achieve accurate segmentation. Two texture descriptor based techniques are Local binary pattern and Weber local descriptor. These descriptors are used in spatial as well as in temporal domain and it helps to segment a frame of video into distinct regions based on the histogram of the region. Lucas-Kanade based optical flow technique is used in temporal domain, which determines direction of motion of dynamic texture in a sequence. These three features are computed for every section of individual frame and equivalent histograms are obtained. These histograms are concatenated and compared with suitable threshold to obtain segmentation of dynamic texture. © Springer International Publishing Switzerland 2015.