Integrating Image and Textual Information in Human–Robot Interactions for Children With Autism Spectrum Disorder

Yang, Xue; Shyu, Mei‐Ling; Yu, Hanqi; Sun, Shiming; Yin, Nian-Sheng; Chen, Wei

doi:10.1109/tmm.2018.2865828

Cited by 26 publications

(11 citation statements)

References 38 publications

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“…[ [49][50][51][52][53][54][55][56][57][58] Pepper Android Humanoid (height = 1.21 m and width = 0.48 m). It has almost the same articulations than a human, except for its mobile base and the impossibility of moving every finger independently.…”

Section: Appearance Type Description Publicationsmentioning

confidence: 99%

“…In the case of social robotics, speech recognition is an important feature, as we need an intuitive, organic, and more natural method of communication than the old-fashioned peripherals. In [58], the researchers propose the use of the Nao robot to maintain conversations with children with autism and automatically extract crucial information on their interests to recommend them picture books. In [57], the authors propose a conversational therapy using a Nao robot that encourages the child to talk about their experiences and help them to recognize objects and imitate facial expressions.…”

Section: Appearance Type Description Publicationsmentioning

confidence: 99%

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Socially Assistive Robots for Older Adults and People with Autism: An Overview

2020

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Over one billion people in the world suffer from some form of disability. Nevertheless, according to the World Health Organization, people with disabilities are particularly vulnerable to deficiencies in services, such as health care, rehabilitation, support, and assistance. In this sense, recent technological developments can mitigate these deficiencies, offering less-expensive assistive systems to meet users’ needs. This paper reviews and summarizes the research efforts toward the development of these kinds of systems, focusing on two social groups: older adults and children with autism.

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Section: Appearance Type Description Publicationsmentioning

confidence: 99%

Section: Appearance Type Description Publicationsmentioning

confidence: 99%

Socially Assistive Robots for Older Adults and People with Autism: An Overview

2020

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“…However, most works focus on only recognizing certain targets involved in driving rather than providing driving suggestions. Image captioning originates from Machine Translating [60] and Natural Language Processing(NPL) [43], and mainly applied in human-robot interactions [61], early childhood education [62], information retrieval [63], and visually impaired assistance [64]. In this paper, we attempt to introduce the image captioning method, the new emerging technology in artificial intelligence, to ITS so as to generate high-level semantic information for driving suggestions or strategies.…”

Section: Discussionmentioning

confidence: 99%

The Traffic Scene Understanding and Prediction Based on Image Captioning

Song

et al. 2021

IEEE Access

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“…Studies (Kumazaki, Muramatsu, Yoshikawa, Yoshimura, et al, 2019) reported that the ADOS results comparing children with ASD and TD could not be confirmed. In addition, Yang et al (2018) mentioned that the outcomes were not validated with the ASD population. As a result, there was doubt regarding the study's validity and the data's reliability in the absence of examination of gold-standard evaluations and experiment groups.…”

Section: Limitationsmentioning

confidence: 99%

Robot facilitated rehabilitation of children with autism spectrum disorder: A 10 year scoping review

2022

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Background: A severe shortage of skilled clinicians and infrastructure limits the delivery of early intervention programmes for autism spectrum disorder (ASD) children that are labour and duration intensive and most advantageous in the first 3 years. Aim: Assess the role of robot mediated intervention (RMI) role in the rehabilitation of ASD individuals by responding to five research questions in the area of (1) Technology maturity; (2) Skill improvement areas; (3) Research design including participant's demographics, datasets, intervention details, and evaluation tools; (4) Data gathering, analysis, and technology contribution, and (5) Role of Robots in intervention and its effectiveness. Methods: Scoping review included RMI studies for ASD individuals published in PUBMED, SCOPUS, and IEEE-Xplore databases between January 1, 2011, and December 31, 2020. The publications were evaluated utilizing the PRISMA scoping review criteria (PRISMA-ScR) checklist and the Critical Appraisal Skills Program (CASP). Results: The 59 selected publications demonstrated that RMI improved skills for ASD individuals in 12 areas. During RMI, extensive joint attention stimuli were given to ASD individuals, and the therapy promoted ASD children's eye contact, imitation, socio-communication, and academic skills. However, various ethical, privacy, and safety concerns were reported in the review. Conclusion: RMI can improve access, quality, and affordability in ASD intervention. The acceptance and use of technology can be fast-tracked by (1) incorporating statistically valid study designs; (2) carrying out field trials including diverse participant groups; (3) standardizing datasets with quality parameters; (4) recruiting statistically appropriate participant groups from ASD, Neuro Typical (NT) and diverse developmental disorder population; and (5) and addressing ethical, privacy, safety, trust, and other stakeholder concerns.

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Integrating Image and Textual Information in Human–Robot Interactions for Children With Autism Spectrum Disorder

Cited by 26 publications

References 38 publications

Socially Assistive Robots for Older Adults and People with Autism: An Overview

Socially Assistive Robots for Older Adults and People with Autism: An Overview

The Traffic Scene Understanding and Prediction Based on Image Captioning

Robot facilitated rehabilitation of children with autism spectrum disorder: A 10 year scoping review

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