Development and Evaluation of Emotional Robots for Children with Autism Spectrum Disorders

Jeon, Myounghoon; Zhang, Ruimin; Lehman, William; Fakhrhosseini, Seyedeh Maryam; Barnes, Jaclyn; Park, Chung Hyuk

doi:10.1007/978-3-319-21380-4_63

Cited by 8 publications

(4 citation statements)

References 12 publications

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“…(ii) The primary recognition technique used is artificial intelligence. Along with the above, the most used classifier by some authors is the SVM [28,[38][39][40], reaching a recognition rate of 98.54% [28].…”

Section: Discussionmentioning

confidence: 99%

Emo-mirror: a proposal to support emotion recognition in children with autism spectrum disorders

Pavez

Diaz

Arango‐López

et al. 2021

Neural Comput & Applic

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Autism spectrum disorder (ASD) is a neurodevelopmental disorder defined as persistent difficulty in maturing the socialization process. Health professionals have used traditional methods in the therapies performed on patients with the aim of improving the expression of emotions by patients. However, they have not been sufficient to detect the different emotions expressed in the face of people according to different sensations. Therefore, different artificial intelligence techniques have been applied to improve the results obtained in these therapies. In this article, we propose the construction of an intelligent mirror to recognize five basic emotions: angry, scared, sad, happy and neutral. This mirror uses convolutional neural networks to analyze the images that are captured by a camera and compare it with the one that the patient should perform, thus supporting the therapies performed by health professionals in children with ASD. The proposal presents the platform and computer architecture, as well as the evaluation by specialists under the technology acceptance model.

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Section: Discussionmentioning

confidence: 99%

Emo-mirror: a proposal to support emotion recognition in children with autism spectrum disorders

Pavez

Diaz

Arango‐López

et al. 2021

Neural Comput & Applic

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“…Previous research has explored education (Caro et al, 2017; Hatfield et al, 2018, Van Laarhoven et al, 2018), social interaction training (Jeon et al, 2015; Millen et al, 2010), social media (Bahiss et al, 2010), serious games (Barry et al, 2008; Caro et al, 2017, Caro et al, 2017), music therapy (Cibrian et al, 2017), university student portal (Fabri et al, 2016; MacLeod, 2010), and communication aids (Checkley et al, 2010; Cheng et al, 2010). These technologies influence every area of life.…”

Section: How Was the Value Of Usability Framed?mentioning

confidence: 99%

Usability: Adoption, Measurement, Value

et al. 2020

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Objective We searched for the application of usability in the literature with a focus on adoption, measurements employed, and demonstrated value. Five human factors domains served as a platform for our reflection, which included the last 20 years. Background As usability studies continue to accumulate, there has been only a little past reflection on usability and contributions across a variety of applications. Our research provides a background for general usability, and we target specific usability research subareas within transportation, aging populations, autistic populations, telehealth, and cybersecurity. Method “Usability” research was explored across five different domains within human factors. The goal was not to perform an exhaustive review but, rather, sample usability practices within several specific subareas. We focused on answering three questions: How was usability adopted? How was it measured? How was it framed in terms of value? Conclusion We found that usability is very domain specific. Usability benchmarking studies and empirical standards are rare. The value associated with improving usability ranged widely—from monetary benefits to saving lives. Thus, researchers are motivated to further improve usability practices. A number of data collection and interpretation challenges still call for solutions. Application Findings offer insight into the development of usability, as applied across a variety of subdomains. Our reflection ought to inform future theory development efforts. We are concerned about the lack of established benchmarks, which can help ground data interpretation. Future research should address this gap in the literature. We note that our findings can be used to develop better training materials for future usability researchers.

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“…In addition to conventional therapy methods, technologically enhanced intervention methods have also been widely adopted in ASD therapy due to the inherent interest in technology that is commonly reported in children with ASD [20][21][22][23][24][25]. The range of solutions is diverse, including video-based instruction, computer-aided instruction, mobile applications, virtual reality, and socially assistive robots [13] [26][27]. However, such methods mostly target the core impairments that characterize ASD, with applications that focus on improving educational performances, emotional recognition and expression, social behaviors, and/or language and communication skills [28][29][30].…”

Section: Introductionmentioning

confidence: 99%

A Robotic Framework to Facilitate Sensory Experiences for Children with Autism Spectrum Disorder

Javed

Burns

Jeon

et al. 2019

J. Hum.-Robot Interact.

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The diagnosis of Autism Spectrum Disorder (ASD) in children is commonly accompanied by a diagnosis of sensory processing disorders as well. Abnormalities are usually reported in multiple sensory processing domains, showing a higher prevalence of unusual responses, particularly to tactile, auditory and visual stimuli. This paper discusses a novel robot-based framework designed to target sensory difficulties faced by children with ASD in a controlled setting. The setup consists of a number of sensory stations, together with robotic agents that navigate the stations and interact with the stimuli as they are presented. These stimuli are designed to resemble real world scenarios that form a common part of one's everyday experiences. Given the strong interest of children with ASD in technology in general and robots in particular, we attempt to utilize our robotic platform to demonstrate socially acceptable responses to the stimuli in an interactive, pedagogical setting that encourages the child's social, motor and vocal skills, while providing a diverse sensory experience. A preliminary user study was conducted to evaluate the efficacy of the proposed framework, with a total of 18 participants (5 with ASD and 13 typically developing) between the ages of 4 and 12 years. We describe our methods of data collection, coding of video data and the analysis of the results obtained from the study. We also discuss the limitations of the current work and detail our plans for the future work to improve the validity of the obtained results.

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Development and Evaluation of Emotional Robots for Children with Autism Spectrum Disorders

Cited by 8 publications

References 12 publications

Emo-mirror: a proposal to support emotion recognition in children with autism spectrum disorders

Emo-mirror: a proposal to support emotion recognition in children with autism spectrum disorders

Usability: Adoption, Measurement, Value

A Robotic Framework to Facilitate Sensory Experiences for Children with Autism Spectrum Disorder

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