Developing Social Communication Skills Using Dual First-Person Video Recording Glasses: A Novel Intervention for Adolescents with Autism

Hurwitz, Sarah; Ryan, Tybytha; Kennedy, Daniel P.

doi:10.1007/s10803-019-04312-6

Cited by 3 publications

(2 citation statements)

References 26 publications

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“…We implemented a method to deliver more reliable and quantifiable measurements of a behavioral feature that is very important in clinical ASD. Previously developed solutions were based on a heavy structuring of interaction, which often limited the value of subsequent analysis and application aspects [ 11 , 32 , 35 , 36 , 37 , 38 , 39 , 40 , 41 ]. Considering the importance of integrating eye contact into intervention programs [ 21 ], our method offers a solution with the potential to support the real clinical context of ASD.…”

Section: Discussionmentioning

confidence: 99%

“…Notably, computational approaches introduce the possibility of collecting quantitative and fine-grained measures with high temporal sensitivity. Most of these approaches were designed upon employing advanced eye-tracking technologies through wearable devices (i.e., smart-glasses) [ 34 , 35 , 36 ], frontal cameras [ 32 , 37 , 38 , 39 , 40 , 41 ] or strong interaction structuring [ 11 , 37 ]. The major drawback of implementing these techniques remains the constraint of operating in not-so-naturalistic environments [ 17 , 18 ].…”

Section: Introductionmentioning

confidence: 99%

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

2021

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

2021

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Operationalizing Social Communication in Autism and Related Neurodevelopmental Research: a Scoping Review Over 20 Years

Tajik-Parvinchi

Hidecker

Selvakumaran

et al. 2021

Curr Dev Disord Rep

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Wearable technology for monitoring behavioral and physiological responses in children with autism spectrum disorder: A literature review

Ahuja

Sarkar

Chandra

et al. 2022

TAD

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BACKGROUND: Autism Spectrum Disorder (ASD) is characterized by difficulties in social communication, social interactions, and repetitive behaviors. The earlier the diagnosis, the sooner the intervention therapy can begin, thus, making early diagnosis an important research goal. Technological innovations have tremendous potential to assist with early diagnosis and improve intervention programs. There is a limited understanding of the Wearable Technologies (WTs) currently available for autistic individuals, and how they measure functioning in this population. OBJECTIVE: The aim of this review is to identify advancement in wearable technologies used to monitor behavioral and physiological responses in the intervention of children with ASD. METHODS: A literature search was performed for English language articles and conference papers indexed in Science direct, PubMed, Web of science, Google scholar, ERIC, ProQuest and Cochrane in last five years (2017–2021), resulting in eighteen studies being reviewed. RESULTS: Wearable technology present a potential solution that can support and complement existing interventions. WTs measured a range of physiological and behavioural functions to objectively measure stereotypical motor movements, social function, communication, and emotion regulation in autistic youth in the context of a range of environments and activities. CONCLUSIONS: Advancement in technology that include behavioral and physiological response monitoring with wearable sensors provide the opportunity to acquire new understanding of the internal components of observable behavior of children with ASD. This could lead to better individualization of treatment and greater treatment effectiveness.

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Developing Social Communication Skills Using Dual First-Person Video Recording Glasses: A Novel Intervention for Adolescents with Autism

Cited by 3 publications

References 26 publications

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

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

Operationalizing Social Communication in Autism and Related Neurodevelopmental Research: a Scoping Review Over 20 Years

Wearable technology for monitoring behavioral and physiological responses in children with autism spectrum disorder: A literature review

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