Design of a robotic agent that measures smile and facing behavior of children with Autism Spectrum Disorder

Hirokawa, Masakazu; Funahashi, Akira; Pan, Yadong; Itoh, Yasushi; Suzuki, Kenji

doi:10.1109/roman.2016.7745217

Cited by 11 publications

(8 citation statements)

References 25 publications

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“…Compared to other physiological sensors, such as electroencephalography and functional MRI, facial EMG can be attached directly to the facial muscles involved in smiling (Maria et al, 2019). Also, it can be used in both laboratory and therapy settings (Hirokawa et al, 2016). Furthermore, the performance evaluation of the Smile Reader has been investigated with adults in a laboratory and children with ASD in therapy; the device has proven reliability for accuracy in smile detection (Funahashi et al, 2014;Gruebler and Suzuki, 2014;Hirokawa et al, 2018).…”

Section: Apparatusmentioning

confidence: 99%

Smiles as a Signal of Prosocial Behaviors Toward the Robot in the Therapeutic Setting for Children With Autism Spectrum Disorder

et al. 2021

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We explored how robot-assisted therapy based on smile analysis may facilitate the prosocial behaviors of children with autism spectrum disorder. Prosocial behaviors, which are actions for the benefit of others, are required to belong to society and increase the quality of life. As smiling is a candidate for predicting prosocial behaviors in robot-assisted therapy, we measured smiles by annotating behaviors that were recorded with video cameras and by classifying facial muscle activities recorded with a wearable device. While interacting with a robot, the participants experienced two situations where participants' prosocial behaviors are expected, which were supporting the robot to walk and helping the robot from falling. We first explored the overall smiles at specific timings and prosocial behaviors. Then, we explored the smiles triggered by a robot and behavior changes before engaging in prosocial behaviors. The results show that the specific timing of smiles and prosocial behaviors increased in the second session of children with autism spectrum disorder. Additionally, a smile was followed by a series of behaviors before prosocial behavior. With a proposed Bayesian model, smiling, or heading predicted prosocial behaviors with higher accuracy compared to other variables. Particularly, voluntary prosocial behaviors were observed after smiling. The findings of this exploratory study imply that smiles might be a signal of prosocial behaviors. We also suggest a probabilistic model for predicting prosocial behaviors based on smile analysis, which could be applied to personalized robot-assisted therapy by controlling a robot's movements to arouse smiles and increase the probability that a child with autism spectrum disorder will engage in prosocial behaviors.

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Section: Apparatusmentioning

confidence: 99%

Smiles as a Signal of Prosocial Behaviors Toward the Robot in the Therapeutic Setting for Children With Autism Spectrum Disorder

et al. 2021

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“…There is still a long way to go to support unscripted conversations between a robot and a participant. There is also work on using cameras to track facial expressions [87,88] and gestures made by a participant to understand the emotion of the participant and to allow the participant to give commands to the robots for increased degree of interaction between robots and participants [11].…”

Section: Social Robotsmentioning

confidence: 99%

Technology-Facilitated Diagnosis and Treatment of Individuals with Autism Spectrum Disorder: An Engineering Perspective

Liu

Zhao

et al. 2017

Applied Sciences

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Abstract:The rapid development of computer and robotic technologies in the last decade is giving hope to perform earlier and more accurate diagnoses of the Autism Spectrum Disorder (ASD), and more effective, consistent, and cost-conscious treatment. Besides the reduced cost, the main benefit of using technology to facilitate treatment is that stimuli produced during each session of the treatment can be controlled, which not only guarantees consistency across different sessions, but also makes it possible to focus on a single phenomenon, which is difficult even for a trained professional to perform, and deliver the stimuli according to the treatment plan. In this article, we provide a comprehensive review of research on recent technology-facilitated diagnosis and treat of children and adults with ASD. Different from existing reviews on this topic, which predominantly concern clinical issues, we focus on the engineering perspective of autism studies. All technology facilitated systems used for autism studies can be modeled as human machine interactive systems where one or more participants would constitute as the human component, and a computer-based or a robotic-based system would be the machine component. Based on this model, we organize our review with the following questions: (1) What are presented to the participants in the studies and how are the content and delivery methods enabled by technologies? (2) How are the reactions/inputs collected from the participants in response to the stimuli in the studies? (3) Are the experimental procedure and programs presented to participants dynamically adjustable based on the responses from the participants, and if so, how? and (4) How are the programs assessed?

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“…WTs may also be particularly suited to intervention to support and facilitate functioning. As demonstrated by a number of studies included in this review, WTs were capable of providing therapists, researchers and parents with real-time data on a child's response to intervention and treatment (43,47,(54)(55)(56), providing an objective and more relevant means of exploring intervention effects. Through individually measuring a child's response during the course of therapy, an intervention can be modified to address their unique needs and challenges using a precision medicine approach (62).…”

Section: Discussionmentioning

confidence: 99%

“…Accelerometers to detect stereotypical movement or self-injurious behavior was observed to be generally accurate (48)(49)(50)(51)(52), however, significant variability in individual behavior was proposed to negatively influence classification performance, with individualized and adaptive classification of stereotypical movement and self-injurious behavior still required (53). Electromyography (EMG) sensors placed on the face were discussed as a means to measure smile behavior in autistic children in two studies (54,55). One study found that the use of facial EMG sensors during animal-assisted therapy were effective in quantifying children's emotional experiences to the therapy (54).…”

Section: Types Of Wearable Technologiesmentioning

confidence: 99%

“…One study found that the use of facial EMG sensors during animal-assisted therapy were effective in quantifying children's emotional experiences to the therapy (54). In a later study (55), it was shown that EMG sensors placed on the face were capable of reliably detecting smile behavior in autistic children during play with a robot.…”

Section: Types Of Wearable Technologiesmentioning

confidence: 99%

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

Black

Milbourn

Chen

et al. 2020

Scandinavian Journal of Child and Adolescent Psychiatry and Psychology

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Background: Wearable technology (WT) to measure and support social and non-social functioning in Autism Spectrum Disorder (ASD) has been a growing interest of researchers over the past decade. There is however limited understanding of the WTs currently available for autistic individuals, and how they measure functioning in this population. Objective: This scoping review explored the use of WTs for measuring and supporting abilities, disabilities and functional skills in autistic youth. Method: Four electronic databases were searched to identify literature investigating the use of WT in autistic youth, resulting in a total of 33 studies being reviewed. Descriptive and content analysis was conducted, with studies subsequently mapped to the ASD International Classification of Functioning, Disability and Health Core-sets and the ICF Child and Youth Version (ICF-CY). Results: Studies were predominately pilot studies for novel devices. 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: While this review raises promising prospects for the use of WTs for autistic youth, the current evidence is limited and requires further investigation.

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Design of a robotic agent that measures smile and facing behavior of children with Autism Spectrum Disorder

Cited by 11 publications

References 25 publications

Smiles as a Signal of Prosocial Behaviors Toward the Robot in the Therapeutic Setting for Children With Autism Spectrum Disorder

Smiles as a Signal of Prosocial Behaviors Toward the Robot in the Therapeutic Setting for Children With Autism Spectrum Disorder

Technology-Facilitated Diagnosis and Treatment of Individuals with Autism Spectrum Disorder: An Engineering Perspective

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

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