While the number of children with diagnosed autism spectrum disorder (ASD) continues to rise from year to year, there is still no universal approach to autism diagnosis and treatment. A great variety of different tools and approaches for the on-site diagnostic are available right now, however, a big percent of parents have no access to them and they tend to search for the available tools and correction programs on the Internet. Lack of money, absence of qualified specialists, and low level of trust to the correction methods are the main issues that affect the in-time diagnoses of ASD and which need to be solved to get the early treatment for the little patients. Understanding the importance of this issue our team decided to investigate new methods of the online autism diagnoses and develop the algorithm that will be able to predict the chances of ASD according to the information from the gaze activity of the child. The results that we got during the experiments show supported our idea that eye-tracking technology is one of the most promising tools for the early detection of the eye-movement features that can be markers of the ASD. Moreover, we have conducted a series of experiments to ensure that our approach has a reliable result on the cheap webcam systems. Thus, this approach can be used as an additional first screening tool for the home monitoring of the early child development and ASD connected disorders monitoring. The further development of eye-tracking based autism diagnosis has a big potential of usage and can be further implemented in the daily practice for practical specialists and parents.
Universidad Peruana Cayetano Heredia（秘鲁卡耶塔诺·埃雷迪亚大学）；Johns Hopkins University（约翰斯·霍普金斯大学）
Autism is a developmental disorder that affects social interaction and communication of children. The gold standard diagnostic tools are very difficult to use and time consuming. However, diagnostic could be deduced from child gaze preferences by looking a video with social and abstract scenes. In this work, we propose an algorithm based on convolutional neural networks to predict gaze direction for a fast and effective autism diagnosis. Early results show that our algorithm achieves real-time response and robust high accuracy for prediction of gaze direction.
Exploring Image Transforms derived from Eye Gaze Variables for Progressive Autism Diagnosis
College of Engineering and Information Technology, University of Dubai, UAE（工程与信息技术学院，迪拜大学）；School of Electrical, Computer, and Telecommunications Engineering, University of Wollongong, Australia（电气、计算机与电信工程学院，沃尔longong大学）；College of Medicine and Health Sciences, Mohammed Bin Rashid University Dubai, UAE（医学与健康科学学院，迪拜穆罕默德·本·拉希德大学）
This research addressed whether interactions with social robots could facilitate joint attention of the autism spectrum disorder (ASD). Two conditions of initiators, namely 'Human' vs. 'Robot' were measured with 15 children with ASD and 15 age-matched typically developing (TD) children. Apart from fixation and gaze transition, a new longest common subsequence (LCS) approach was proposed to analyze eye-movement traces. Results revealed that children with ASD showed deficits of joint attention. Compared to the human agent, robot facilitate less fixations towards the targets, but it attracted mor…
Introducing CALMED: Multimodal Annotated Dataset for Emotion Detection in Children with Autism
University of Galway（戈尔韦大学）；LORIA CNRS/INRIA/Université de Lorraine（洛林大学国家科学研究中心/法国国家信息与自动化研究所洛林计算机科学及其应用实验室）；Université Sorbonne Paris Nord（巴黎索邦北大学）；ASK - All Special Kids（ASK-所有特殊儿童）
A good teaching method is incomprehensible for an autistic child. The autism spectrum disorder is a very diverse phenomenon. It is said that no two autistic children are the same. So, something that works for one child may not be fit for another. The same case is true for their education. Different children need to be approached with different teaching methods. But it is quite hard to identify the appropriate teaching method. As the term itself explains, the autism spectrum disorder is like a spectrum. There are multiple factors to determine the type of autism of a child. A child might even be…
Development of Immersive Virtual and Augmented Reality-Based Joint Attention Training Platform for Children with Autism
Indian Institute of Technology Delhi（印度德里理工学院）；Indian Institute of Technology Jodhpur（印度焦浦尔理工学院）；All India Institute of Medical Sciences Delhi（印度医学科学院德里分院）
The 3D4Amb project aims at developing a system based on the stereoscopic 3D techonlogy, like the NVIDIA 3D Vision, for the diagnosis and treatment of amblyopia in young children. It exploits the active shutter technology to provide binocular vision, i.e. to show different images to the amblyotic (or lazy) and the normal eye. It would allow easy diagnosis of amblyopia and its treatment by means of interactive games or other entertainment activities. It should not suffer from the compliance problems of the classical treatment, it is suitable to domestic use, and it could at least partially subst…
ADHD is being recognized as a diagnosis which persists into adulthood impacting economic, occupational, and educational outcomes. There is an increased need to accurately diagnose and recommend interventions for this population. One consideration is the development and implementation of reliable and valid outcome measures which reflect core diagnostic criteria. For example, adults with ADHD have reduced working memory capacity when compared to their peers (Michalek et al., 2014). A reduction in working memory capacity indicates attentional control deficits which align with many symptoms outlin…
Dermatologist-like explainable AI enhances melanoma diagnosis accuracy: eye-tracking study
German Cancer Research Center (DKFZ)（德国癌症研究中心）；Medical University of Vienna（维也纳医科大学）；Uniklinikum Erlangen（埃尔朗根大学医院）；Friedrich-Alexander-Universität Erlangen-Nürnberg（弗里德里希-亚历山大-埃尔朗根-纽伦堡大学）；Bavarian Cancer Research Center (BZFK)（巴伐利亚癌症研究中心）；University Medical Center Mannheim（曼海姆大学医学中心）；Ruprecht-Karl University of Heidelberg（海德堡鲁普雷希特-卡尔大学（海德堡大学））；DKFZ Hector Cancer Institute at the University Medical Center Mannheim（曼海姆大学医学中心DKFZ赫克托癌症研究所）；University Hospital Frankfurt（法兰克福大学医院）；Goethe-University Frankfurt（法兰克福歌德大学）；Pontificia Universidad Católica de Chile（智利天主教大学）；University Hospital Würzburg（维尔茨堡大学医院）；National Center for Tumor Diseases (NCT)（国家肿瘤疾病中心）；TUD Dresden University of Technology（德累斯顿工业大学）；University Hospital Aachen（亚琛大学医院）；RWTH University of Aachen（亚琛工业大学）
Deep Learning in Mild Cognitive Impairment Diagnosis using Eye Movements and Image Content in Visual Memory Tasks
Institute for Systems and Robotics（系统与机器人研究所）；Laboratory for Robotics and Engineering Systems（机器人与工程系统实验室）；Instituto Superior Técnico（技术高等学院）；Universidade de Lisboa（里斯本大学）；Department of Psychology（心理学系）；University of Chicago（芝加哥大学）；Institute for Mind and Biology（心灵与生物学研究所）；Sapienza Università di Roma（罗马萨皮恩扎大学）
University of Washington（华盛顿大学）；Seattle Children’s Research Institute（西雅图儿童研究所）；Binghamton University（宾汉姆顿大学）；University of Virginia（弗吉尼亚大学）；University of Colorado（科罗拉多大学）；Xi’an Institute of Optics and Precision Mechanics, CAS（中国科学院西安光学精密机械研究所）；Yale University（耶鲁大学）
Identifying oculomotor behaviors relevant for eye-tracking applications is a critical but often challenging task. Aiming to automatically learn and extract knowledge from existing eye-tracking data, we develop a novel method that creates rich representations of oculomotor scanpaths to facilitate the learning of downstream tasks. The proposed stimulus-agnostic Oculomotor Behavior Framework (OBF) model learns human oculomotor behaviors from unsupervised and semi-supervised tasks, including reconstruction, predictive coding, fixation identification, and contrastive learning tasks. The resultant p…
Internal State Estimation in Groups via Active Information Gathering
The University of Hong Kong（香港大学）；Tencent America（腾讯美国）；Centre for Transformative Garment Production（转型服装生产中心）；Tsinghua University（清华大学）；University of Jinan（济南大学）；Shandong University（山东大学）
