scholarly journals EYE-C: Eye-Contact Robust Detection and Analysis during Unconstrained Child-Therapist Interactions in the Clinical Setting of Autism Spectrum Disorders

2021 ◽  
Vol 11 (12) ◽  
pp. 1555
Author(s):  
Gianpaolo Alvari ◽  
Luca Coviello ◽  
Cesare Furlanello
Keyword(s):  
Clinical Sample ◽  
Eye Contact ◽  
Video Camera ◽  
Autism Spectrum ◽  
Individual Characteristics ◽  
Video Data ◽  
Contact Dynamics ◽  
Treatment Programs ◽  
Robust Detection ◽  
High Level

The high level of heterogeneity in Autism Spectrum Disorder (ASD) and the lack of systematic measurements complicate predicting outcomes of early intervention and the identification of better-tailored treatment programs. Computational phenotyping may assist therapists in monitoring child behavior through quantitative measures and personalizing the intervention based on individual characteristics; still, real-world behavioral analysis is an ongoing challenge. For this purpose, we designed EYE-C, a system based on OpenPose and Gaze360 for fine-grained analysis of eye-contact episodes in unconstrained therapist-child interactions via a single video camera. The model was validated on video data varying in resolution and setting, achieving promising performance. We further tested EYE-C on a clinical sample of 62 preschoolers with ASD for spectrum stratification based on eye-contact features and age. By unsupervised clustering, three distinct sub-groups were identified, differentiated by eye-contact dynamics and a specific clinical phenotype. Overall, this study highlights the potential of Artificial Intelligence in categorizing atypical behavior and providing translational solutions that might assist clinical practice.

The Influence of Language Context on Repetitive Speech Use in Children With Autism Spectrum Disorder

2020 ◽  
Vol 29 (1) ◽  
pp. 327-334 ◽  
Author(s):  
Allison Gladfelter ◽  
Cassidy VanZuiden
Keyword(s):  
Autism Spectrum Disorder ◽  
Autism Spectrum ◽  
Individual Characteristics ◽  
Receptive Vocabulary ◽  
Spectrum Disorder ◽  
School Age Children ◽  
Social Responsiveness ◽  
Contributing Factors ◽  
Children With Asd ◽  
Language Context

Purpose Although repetitive speech is a hallmark characteristic of autism spectrum disorder (ASD), the contributing factors that influence repetitive speech use remain unknown. The purpose of this exploratory study was to determine if the language context impacts the amount and type of repetitive speech produced by children with ASD. Method As part of a broader word-learning study, 11 school-age children with ASD participated in two different language contexts: storytelling and play. Previously collected language samples were transcribed and coded for four types of repetitive speech: immediate echolalia, delayed echolalia, verbal stereotypy, and vocal stereotypy. The rates and proportions of repetitive speech were compared across the two language contexts using Wilcoxon signed-ranks tests. Individual characteristics were further explored using Spearman correlations. Results The children produced lower rates of repetitive speech during the storytelling context than the play-based context. Only immediate echolalia differed between the two contexts based on rate and approached significance based on proportion, with more immediate echolalia produced in the play-based context than in the storytelling context. There were no significant correlations between repetitive speech and measures of social responsiveness, expressive or receptive vocabulary, or nonverbal intelligence. Conclusions The children with ASD produced less immediate echolalia in the storytelling context than in the play-based context. Immediate echolalia use was not related to social skills, vocabulary, or nonverbal IQ scores. These findings offer valuable insights into better understanding repetitive speech use in children with ASD.

scholarly journals Natural Language Description of Videos for Smart Surveillance

2021 ◽  
Vol 11 (9) ◽  
pp. 3730
Author(s):  
Aniqa Dilawari ◽  
Muhammad Usman Ghani Khan ◽  
Yasser D. Al-Otaibi ◽  
Zahoor-ur Rehman ◽  
Atta-ur Rahman ◽  
...  
Keyword(s):  
Natural Language ◽  
Feature Recognition ◽  
Scene Recognition ◽  
Video Data ◽  
Surveillance Video ◽  
Video Footage ◽  
Parallel Pipeline ◽  
September 11 Attacks ◽  
Description Framework ◽  
High Level

After the September 11 attacks, security and surveillance measures have changed across the globe. Now, surveillance cameras are installed almost everywhere to monitor video footage. Though quite handy, these cameras produce videos in a massive size and volume. The major challenge faced by security agencies is the effort of analyzing the surveillance video data collected and generated daily. Problems related to these videos are twofold: (1) understanding the contents of video streams, and (2) conversion of the video contents to condensed formats, such as textual interpretations and summaries, to save storage space. In this paper, we have proposed a video description framework on a surveillance dataset. This framework is based on the multitask learning of high-level features (HLFs) using a convolutional neural network (CNN) and natural language generation (NLG) through bidirectional recurrent networks. For each specific task, a parallel pipeline is derived from the base visual geometry group (VGG)-16 model. Tasks include scene recognition, action recognition, object recognition and human face specific feature recognition. Experimental results on the TRECViD, UET Video Surveillance (UETVS) and AGRIINTRUSION datasets depict that the model outperforms state-of-the-art methods by a METEOR (Metric for Evaluation of Translation with Explicit ORdering) score of 33.9%, 34.3%, and 31.2%, respectively. Our results show that our framework has distinct advantages over traditional rule-based models for the recognition and generation of natural language descriptions.

scholarly journals Mealtime Behaviors and Food Preferences of Students with Autism Spectrum Disorder

Foods ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 49
Author(s):  
Hae Jin Park ◽  
Su Jin Choi ◽  
Yuri Kim ◽  
Mi Sook Cho ◽  
Yu-Ri Kim ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Nutrition Education ◽  
Neurodevelopmental Disorder ◽  
Food Preferences ◽  
Autism Spectrum ◽  
Repetitive Behaviors ◽  
Spectrum Disorder ◽  
Online Questionnaire ◽  
Mealtime Behavior ◽  
High Level

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by a lack of social communication and restrictive, repetitive behaviors or interests. This study aimed to examine the mealtime behaviors and food preferences of students with ASD. An online questionnaire on mealtime behavior and food preferences of ASD students was conducted by caregivers including parents, and the average age of ASD students was 14.1 ± 6.1. The analysis of mealtime behavior resulted in classification into three clusters: cluster 1, the “low-level problematic mealtime behavior group”; cluster 2, the “mid-level problematic mealtime behavior group”; and cluster 3, the “high-level problematic mealtime behavior group”. Cluster 1 included older students than other clusters and their own specific dietary rituals. Meanwhile, cluster 3 included younger students than other clusters, high-level problematic mealtime behavior, and a low preference for food. In particular, there were significant differences in age and food preference for each subdivided ASD group according to their eating behaviors. Therefore, the content and method of nutrition education for ASD students’ needs a detailed approach according to the characteristics of each group.

scholarly journals Parental evaluation of a revised autism spectrum disorder diagnostic process for children under 36 months of age

2021 ◽  
Author(s):  
Jean-François Lemay ◽  
Shauna Langenberger ◽  
Scott McLeod
Keyword(s):  
Autism Spectrum Disorder ◽  
Early Intervention ◽  
Parent Education ◽  
Positive Impact ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Diagnostic Process ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
High Level

Abstract Background The Alberta Children’s Hospital-Autism Spectrum Disorder Diagnostic Clinic (ACH-ASDC) was restructured due to long wait times and unsustainable clinic workflow. Major changes included the initiation of pre- and post-ASD parent education sessions and distinct ASD screening appointments before the ASD diagnostic appointment. Methods We conducted a parental program evaluation in summer 2018 of the ACH-ASDC. We used a cross-sectional survey to evaluate key outcomes including parental satisfaction, and the percentage of families obtaining access to government supports and early intervention programs. Results For the 101 eligible patients diagnosed with ASD under 36 months of age 70 (69.3%) parents agreed to participate. The mean diagnostic age of the children diagnosed with ASD was 30.6 months (SD=4.1 months). There were no statistically significant age differences between biological sexes. Ninety-three per cent of parents felt that ASD educational sessions were useful, and 92% of parents were satisfied to very satisfied with the overall ASD diagnostic process. Ninety per cent of parents had access to at least one of the key resources available for ASD early intervention in our province following diagnosis. Parents reported a positive impact on intervention provided to their child in the areas of communication, social interaction, and behaviour. Conclusion Parents of children diagnosed with ASD expressed a high level of satisfaction with the restructured ACH-ASDC process. Implementing parent education sessions was well received and met parents’ needs. Parents were able to access intervention services following diagnosis and reported positive impacts for their child. Re-envisioning program approaches to incorporate novel strategies to support families should be encouraged.

scholarly journals Deep-Framework: A Distributed, Scalable, and Edge-Oriented Framework for Real-Time Analysis of Video Streams

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4045
Author(s):  
Alessandro Sassu ◽  
Jose Francisco Saenz-Cogollo ◽  
Maurizio Agelli
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Video Data ◽  
Video Analytics ◽  
Web Based ◽  
Real Time Analysis ◽  
Open Source Framework ◽  
Cluster Configuration ◽  
Time Requirements ◽  
High Level

Edge computing is the best approach for meeting the exponential demand and the real-time requirements of many video analytics applications. Since most of the recent advances regarding the extraction of information from images and video rely on computation heavy deep learning algorithms, there is a growing need for solutions that allow the deployment and use of new models on scalable and flexible edge architectures. In this work, we present Deep-Framework, a novel open source framework for developing edge-oriented real-time video analytics applications based on deep learning. Deep-Framework has a scalable multi-stream architecture based on Docker and abstracts away from the user the complexity of cluster configuration, orchestration of services, and GPU resources allocation. It provides Python interfaces for integrating deep learning models developed with the most popular frameworks and also provides high-level APIs based on standard HTTP and WebRTC interfaces for consuming the extracted video data on clients running on browsers or any other web-based platform.

Brief Report: Does Eye Contact Induce Contagious Yawning in Children with Autism Spectrum Disorder?

2009 ◽  
Vol 39 (11) ◽  
pp. 1598-1602 ◽  
Author(s):  
Atsushi Senju ◽  
Yukiko Kikuchi ◽  
Hironori Akechi ◽  
Toshikazu Hasegawa ◽  
Yoshikuni Tojo ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Eye Contact ◽  
Children With Autism ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Contagious Yawning

Conspicuous consumption of luxury experiences: an experimental investigation of status perceptions on social media

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Carolin Siepmann ◽  
Lisa Carola Holthoff ◽  
Pascal Kowalczuk
Keyword(s):  
Social Media ◽  
Personal Characteristics ◽  
Conspicuous Consumption ◽  
Individual Characteristics ◽  
Luxury Goods ◽  
Content Type ◽  
The Status ◽  
Self Actualization ◽  
The Individual ◽  
High Level

Purpose As luxury goods are losing their importance for demonstrating status, wealth or power to others, individuals are searching for alternative status symbols. Recently, individuals have increasingly used conspicuous consumption and displays of experiences on social media to obtain affirmation. This study aims to analyze the effects of luxury and nonluxury experiences, as well as traditional luxury goods on status- and nonstatus-related dimensions. Design/methodology/approach After presenting the theoretical foundation, the authors conduct a study with 599 participants to compare status perceptions elicited by the conspicuous consumption of luxury goods, luxury experiences and nonluxury experiences. The authors investigate whether experiences that are visibly consumed on Instagram are replacing traditional luxury goods as the most important status symbols. Furthermore, the authors examine the effects of the content shown on nonstatus-related dimensions and analyze whether status perceptions differ between female and male social media communicators. Finally, the authors analyze how personal characteristics (self-esteem, self-actualization and materialism) influence the status perceptions of others on social media. Findings The results show that luxury goods are still the most important means of displaying status. However, especially for women, luxury experiences are also associated with a high level of social status. Thus, the results imply important gender differences in the perceptions of status- and nonstatus-related dimensions. Furthermore, the findings indicate that, in particular, the individual characteristics of self-actualization and materialism affect status perceptions depending on the posted content. Originality/value While the research has already considered some alternative forms of conspicuous consumption, little attention has been given to experiences as status symbols. However, with their growing importance as substitutes for luxury goods and the rise of social media, the desire to conspicuously consume experiences is increasing. The authors address this gap in the literature by focusing on the conspicuous display of luxury and nonluxury experiences on social media.

scholarly journals Altered interpersonal distance regulation in autism spectrum disorder

2021 ◽  
Author(s):  
Kinga Farkas ◽  
Orsolya Pesthy ◽  
Anna Guttengeber ◽  
Anna Szonja Weigl ◽  
Andras Veres ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Experimental Design ◽  
Real Life ◽  
Essential Element ◽  
Eye Contact ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Interpersonal Distance ◽  
Incidental Condition ◽  
Distance Regulation

Interpersonal distance regulation is an essential element of social communication. Its impairment in autism spectrum disorder (ASD) is widely acknowledged among practitioners, but only a handful of studies reported empirical research in real-life settings focusing only on children. However, these studies did not measure the alterations of vegetative functions related to interpersonal distance. Here, we introduced a new experimental design to systematically measure interpersonal distance along with heart rate variability (HRV) in adults with ASD and tested the modulatory effect of intentionality, eye contact, moving activity, and attribution. Twenty-two adults diagnosed with ASD and 21 matched neurotypical controls participated in our study from 2019 October to 2020 February. Our new experimental design combined the modified version of the stop distance paradigm with HRV measurement controlling for eye contact between the experimenter and the participant to measure interpersonal distance in incidental and intentional conditions. Our results showed greater preferred distance in ASD in the intentional but not in the incidental condition. These results were altered with eye contact and the participant's role (active vs. passive) in the stop distance task. Moreover, we found lower baseline HRV and reduced HRV reactivity in ASD; however, these vegetative measurements could not predict preferred interpersonal distance. Our study highlights the importance of interpersonal space regulation in ASD and the need for sophisticated experimental designs to grasp the complexity and underlying factors of distance regulation in typical and atypical populations.

Sign in / Sign up

Export Citation Format

Share Document