Literature DB >> 29466819

Feasibility Testing of a Wearable Behavioral Aid for Social Learning in Children with Autism.

Jena Daniels, Nick Haber, Catalin Voss, Jessey Schwartz, Serena Tamura, Azar Fazel, Aaron Kline, Peter Washington, Jennifer Phillips, Terry Winograd, Carl Feinstein, Dennis P Wall.   

Abstract

BACKGROUND: Recent advances in computer vision and wearable technology have created an opportunity to introduce mobile therapy systems for autism spectrum disorders (ASD) that can respond to the increasing demand for therapeutic interventions; however, feasibility questions must be answered first.
OBJECTIVE: We studied the feasibility of a prototype therapeutic tool for children with ASD using Google Glass, examining whether children with ASD would wear such a device, if providing the emotion classification will improve emotion recognition, and how emotion recognition differs between ASD participants and neurotypical controls (NC).
METHODS: We ran a controlled laboratory experiment with 43 children: 23 with ASD and 20 NC. Children identified static facial images on a computer screen with one of 7 emotions in 3 successive batches: the first with no information about emotion provided to the child, the second with the correct classification from the Glass labeling the emotion, and the third again without emotion information. We then trained a logistic regression classifier on the emotion confusion matrices generated by the two information-free batches to predict ASD versus NC.
RESULTS: All 43 children were comfortable wearing the Glass. ASD and NC participants who completed the computer task with Glass providing audible emotion labeling (n = 33) showed increased accuracies in emotion labeling, and the logistic regression classifier achieved an accuracy of 72.7%. Further analysis suggests that the ability to recognize surprise, fear, and neutrality may distinguish ASD cases from NC.
CONCLUSION: This feasibility study supports the utility of a wearable device for social affective learning in ASD children and demonstrates subtle differences in how ASD and NC children perform on an emotion recognition task. Schattauer GmbH Stuttgart.

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Year:  2018        PMID: 29466819      PMCID: PMC5821509          DOI: 10.1055/s-0038-1626727

Source DB:  PubMed          Journal:  Appl Clin Inform        ISSN: 1869-0327            Impact factor:   2.342


  54 in total

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5.  Avatar assistant: improving social skills in students with an ASD through a computer-based intervention.

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Journal:  J Autism Dev Disord       Date:  2011-11

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  16 in total

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2.  Understanding the experiences of self-injurious behavior in autism spectrum disorder: Implications for monitoring technology design.

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Journal:  Appl Clin Inform       Date:  2021-01-06       Impact factor: 2.342

4.  Classifying Autism From Crowdsourced Semistructured Speech Recordings: Machine Learning Model Comparison Study.

Authors:  Nathan A Chi; Peter Washington; Aaron Kline; Arman Husic; Cathy Hou; Chloe He; Kaitlyn Dunlap; Dennis P Wall
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5.  Toward Continuous Social Phenotyping: Analyzing Gaze Patterns in an Emotion Recognition Task for Children With Autism Through Wearable Smart Glasses.

Authors:  Nick Haber; Anish Nag; Catalin Voss; Serena Tamura; Jena Daniels; Jeffrey Ma; Bryan Chiang; Shasta Ramachandran; Jessey Schwartz; Terry Winograd; Carl Feinstein; Dennis P Wall
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6.  Validity of Online Screening for Autism: Crowdsourcing Study Comparing Paid and Unpaid Diagnostic Tasks.

Authors:  Peter Washington; Haik Kalantarian; Qandeel Tariq; Jessey Schwartz; Kaitlyn Dunlap; Brianna Chrisman; Maya Varma; Michael Ning; Aaron Kline; Nathaniel Stockham; Kelley Paskov; Catalin Voss; Nick Haber; Dennis Paul Wall
Journal:  J Med Internet Res       Date:  2019-05-23       Impact factor: 5.428

7.  The use of wearable technology to measure and support abilities, disabilities and functional skills in autistic youth: a scoping review.

Authors:  Melissa H Black; Benjamin Milbourn; Nigel T M Chen; Sarah McGarry; Fatema Wali; Armilda S V Ho; Mika Lee; Sven Bölte; Torbjorn Falkmer; Sonya Girdler
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8.  The Performance of Emotion Classifiers for Children With Parent-Reported Autism: Quantitative Feasibility Study.

Authors:  Haik Kalantarian; Khaled Jedoui; Kaitlyn Dunlap; Jessey Schwartz; Peter Washington; Arman Husic; Qandeel Tariq; Michael Ning; Aaron Kline; Dennis Paul Wall
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9.  Feature Selection and Dimension Reduction of Social Autism Data.

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Review 10.  Computer vision in autism spectrum disorder research: a systematic review of published studies from 2009 to 2019.

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