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      Feasibility of an Autism-Focused Augmented Reality Smartglasses System for Social Communication and Behavioral Coaching

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          Abstract

          Background

          Autism spectrum disorder (ASD) is a childhood-onset neurodevelopmental disorder with a rapidly rising prevalence, currently affecting 1 in 68 children, and over 3.5 million people in the United States. Current ASD interventions are primarily based on in-person behavioral therapies that are both costly and difficult to access. These interventions aim to address some of the fundamental deficits that clinically characterize ASD, including deficits in social communication, and the presence of stereotypies, and other autism-related behaviors. Current diagnostic and therapeutic approaches seldom rely on quantitative data measures of symptomatology, severity, or condition trajectory.

          Methods

          Given the current situation, we report on the Brain Power System (BPS), a digital behavioral aid with quantitative data gathering and reporting features. The BPS includes customized smartglasses, providing targeted personalized coaching experiences through a family of gamified augmented-reality applications utilizing artificial intelligence. These applications provide children and adults with coaching for emotion recognition, face directed gaze, eye contact, and behavioral self-regulation. This preliminary case report, part of a larger set of upcoming research reports, explores the feasibility of the BPS to provide coaching in two boys with clinically diagnosed ASD, aged 8 and 9 years.

          Results

          The coaching intervention was found to be well tolerated and rated as being both engaging and fun. Both males could easily use the system, and no technical problems were noted. During the intervention, caregivers reported improved non-verbal communication, eye contact, and social engagement during the intervention. Both boys demonstrated decreased symptoms of ASD, as measured by the aberrant behavior checklist at 24-h post-intervention. Specifically, both cases demonstrated improvements in irritability, lethargy, stereotypy, hyperactivity/non-compliance, and inappropriate speech.

          Conclusion

          Smartglasses using augmented reality may have an important future role in helping address the therapeutic needs of children with ASD. Quantitative data gathering from such sensor-rich systems may allow for digital phenotyping and the refinement of social communication constructs of the research domain criteria. This report provides evidence for the feasibility, usability, and tolerability of one such specialized smartglasses system.

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          Most cited references32

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          Visual Fixation Patterns During Viewing of Naturalistic Social Situations as Predictors of Social Competence in Individuals With Autism

          Manifestations of core social deficits in autism are more pronounced in everyday settings than in explicit experimental tasks. To bring experimental measures in line with clinical observation, we report a novel method of quantifying atypical strategies of social monitoring in a setting that simulates the demands of daily experience. Enhanced ecological validity was intended to maximize between-group effect sizes and assess the predictive utility of experimental variables relative to outcome measures of social competence.
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            The aberrant behavior checklist: a behavior rating scale for the assessment of treatment effects.

            The development of a scale to assess drug and other treatment effects on severely mentally retarded individuals was described. In the first stage of the project, an initial scale encompassing a large number of behavior problems was used to rate 418 residents. The scale was then reduced to an intermediate version, and in the second stage, 509 moderately to profoundly retarded individuals were rated. Separate factor analyses of the data from the two samples resulted in a five-factor scale comprising 58 items. The factors of the Aberrant Behavior Checklist have been labeled as follows: (I) Irritability, Agitation, Crying; (II) Lethargy, Social Withdrawal; (III) Stereotypic Behavior; (IV) Hyperactivity, Noncompliance; and (V) Inappropriate Speech. Average subscale scores were presented for the instrument, and the results were compared with empirically derived rating scales of childhood psychopathology and with factor analytic work in the field of mental retardation.
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              Prevalence of autism spectrum disorder among children aged 8 years - autism and developmental disabilities monitoring network, 11 sites, United States, 2010.

              (2014)
              Autism spectrum disorder (ASD). 2010. The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance system in the United States that provides estimates of the prevalence of ASD and other characteristics among children aged 8 years whose parents or guardians live in 11 ADDM sites in the United States. ADDM surveillance is conducted in two phases. The first phase consists of screening and abstracting comprehensive evaluations performed by professional providers in the community. Multiple data sources for these evaluations include general pediatric health clinics and specialized programs for children with developmental disabilities. In addition, most ADDM Network sites also review and abstract records of children receiving special education services in public schools. The second phase involves review of all abstracted evaluations by trained clinicians to determine ASD surveillance case status. A child meets the surveillance case definition for ASD if a comprehensive evaluation of that child completed by a qualified professional describes behaviors consistent with the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) diagnostic criteria for any of the following conditions: autistic disorder, pervasive developmental disorder-not otherwise specified (including atypical autism), or Asperger disorder. This report provides updated prevalence estimates for ASD from the 2010 surveillance year. In addition to prevalence estimates, characteristics of the population of children with ASD are described. For 2010, the overall prevalence of ASD among the ADDM sites was 14.7 per 1,000 (one in 68) children aged 8 years. Overall ASD prevalence estimates varied among sites from 5.7 to 21.9 per 1,000 children aged 8 years. ASD prevalence estimates also varied by sex and racial/ethnic group. Approximately one in 42 boys and one in 189 girls living in the ADDM Network communities were identified as having ASD. Non-Hispanic white children were approximately 30% more likely to be identified with ASD than non-Hispanic black children and were almost 50% more likely to be identified with ASD than Hispanic children. Among the seven sites with sufficient data on intellectual ability, 31% of children with ASD were classified as having IQ scores in the range of intellectual disability (IQ ≤70), 23% in the borderline range (IQ = 71-85), and 46% in the average or above average range of intellectual ability (IQ >85). The proportion of children classified in the range of intellectual disability differed by race/ethnicity. Approximately 48% of non-Hispanic black children with ASD were classified in the range of intellectual disability compared with 38% of Hispanic children and 25% of non-Hispanic white children. The median age of earliest known ASD diagnosis was 53 months and did not differ significantly by sex or race/ethnicity. These findings from CDC's ADDM Network, which are based on 2010 data reported from 11 sites, provide updated population-based estimates of the prevalence of ASD in multiple communities in the United States. Because the ADDM Network sites do not provide a representative sample of the entire United States, the combined prevalence estimates presented in this report cannot be generalized to all children aged 8 years in the United States population. Consistent with previous reports from the ADDM Network, findings from the 2010 surveillance year were marked by significant variations in ASD prevalence by geographic area, sex, race/ethnicity, and level of intellectual ability. The extent to which this variation might be attributable to diagnostic practices, underrecognition of ASD symptoms in some racial/ethnic groups, socioeconomic disparities in access to services, and regional differences in clinical or school-based practices that might influence the findings in this report is unclear. ADDM Network investigators will continue to monitor the prevalence of ASD in select communities, with a focus on exploring changes within these communities that might affect both the observed prevalence of ASD and population-based characteristics of children identified with ASD. Although ASD is sometimes diagnosed by 2 years of age, the median age of the first ASD diagnosis remains older than age 4 years in the ADDM Network communities. Recommendations from the ADDM Network include enhancing strategies to address the need for 1) standardized, widely adopted measures to document ASD severity and functional limitations associated with ASD diagnosis; 2) improved recognition and documentation of symptoms of ASD, particularly among both boys and girls, children without intellectual disability, and children in all racial/ethnic groups; and 3) decreasing the age when children receive their first evaluation for and a diagnosis of ASD and are enrolled in community-based support systems.
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                Author and article information

                Contributors
                Journal
                Front Pediatr
                Front Pediatr
                Front. Pediatr.
                Frontiers in Pediatrics
                Frontiers Media S.A.
                2296-2360
                26 June 2017
                2017
                : 5
                : 145
                Affiliations
                [1] 1Brain Power , Cambridge, MA, United States
                [2] 2Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology , Cambridge, MA, United States
                [3] 3Department of Psychiatry, Harvard Medical School , Boston, MA, United States
                [4] 4Department of Psychology, Harvard University , Cambridge, MA, United States
                Author notes

                Edited by: Kerim M. Munir, Boston Children’s Hospital, United States

                Reviewed by: Alka Anand Subramanyam, Topiwala National Medical College & BYL Nair Charitable Hospital, India; Kürşat Altınbaş, Selçuk University, Turkey

                *Correspondence: Ned T. Sahin, ned@ 123456brain-power.com

                Specialty section: This article was submitted to Child and Adolescent Psychiatry, a section of the journal Frontiers in Pediatrics

                Article
                10.3389/fped.2017.00145
                5483849
                28695116
                9277e9f3-5923-4ffd-87bd-0690ca9edb40
                Copyright © 2017 Liu, Salisbury, Vahabzadeh and Sahin.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 26 February 2017
                : 08 June 2017
                Page count
                Figures: 3, Tables: 5, Equations: 0, References: 42, Pages: 8, Words: 5318
                Categories
                Pediatrics
                Technology Report

                augmented reality,virtual reality,feasibility,tolerability,smartglasses,autism spectrum disorder,education,stimulant

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