Robot-Based Motor Rehabilitation in Autism: A Systematic Review

Jouaiti, Mélanie; Hénaff, Patrick

doi:10.1007/s12369-019-00598-9

Cited by 31 publications

(13 citation statements)

References 114 publications

(85 reference statements)

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“…Consequently, the trust toward the robot arm might be larger than toward humans. This would be in line with the aforementioned studies (Giullian et al, 2010 ; Ricks and Colton, 2010 ; Jouaiti and Hénaff, 2019 ; Reardon et al, 2019 ) about autistic children and students becoming socialized and educated more easily with robots than with humans. Also, the single finding that one participant abandoned his tic lends weight to this hypothesis.…”

Section: Discussionsupporting

confidence: 86%

“…Moreover, robot-based autism therapy, especially for children, is a rapidly growing research area. The interaction is intended to increase their social skills, along with an associated rehabilitation of motor skills (Giullian et al, 2010 ; Ricks and Colton, 2010 ; Jouaiti and Hénaff, 2019 ). An initial study on teaching students with intellectual disabilities different tasks using a social robot also showed promising results, probably because the students felt less pressure when asking a robot to repeat the explanation than they did with a judgmental human equivalent (Reardon et al, 2019 ).…”

Section: Related Workmentioning

confidence: 99%

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Acceptance of Industrial Collaborative Robots by People With Disabilities in Sheltered Workshops

et al. 2021

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The integration of people with disabilities into the working world is an important, yet challenging field of research. While different inclusion efforts exist, people with disabilities are still under-represented in the open labor market. This paper investigates the approach of using a collaborative robot arm to support people with disabilities with their reintegration into the workplace. However, there is currently little literature about the acceptance of an industrial robot by people with disabilities and in cases where a robot leads to stress, fear, or any other form of discomfort, this approach is not feasible. For this reason, a first user study was performed in a sheltered workshop to investigate the acceptance of a robot arm by workers with disabilities. As a first step in this underdeveloped field, two main aspects were covered. Firstly, the reaction and familiarization to the robot arm within a study situation was closely examined in order to separate any effects that were not caused by the moving robot. Secondly, the reaction toward the robot arm during collaboration was investigated. In doing so, five different distances between the robot arm and the participants were considered to make collaboration in the workplace as pleasant as possible. The results revealed that it took the participants about 20 min to get used to the situation, while the robot was immediately accepted very well and did not cause fear or discomfort at any time. Surprisingly, in some cases, short distances were accepted even better than the larger distances. For these reasons, the presented approach showed to promise for future investigations.

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Section: Discussionsupporting

confidence: 86%

Section: Related Workmentioning

confidence: 99%

Acceptance of Industrial Collaborative Robots by People With Disabilities in Sheltered Workshops

et al. 2021

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“…This is one social robot application that has received much attention [32,[66][67][68][69][70][71][72][73][74][75][76]. For example, families coping with a relative with autism often struggle with social and emotional communication.…”

Section: Assistance To the Elderly And Handicappedmentioning

confidence: 99%

The Social Robot in Rehabilitation and Assistance: What Is the Future?

Giansanti

2021

Healthcare

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This commentary aims to address the field of social robots both in terms of the global situation and research perspectives. It has four polarities. First, it revisits the evolutions in robotics, which, starting from collaborative robotics, has led to the diffusion of social robots. Second, it illustrates the main fields in the employment of social robots in rehabilitation and assistance in the elderly and handicapped and in further emerging sectors. Third, it takes a look at the future directions of the research development both in terms of clinical and technological aspects. Fourth, it discusses the opportunities and limits, starting from the development and clinical use of social robots during the COVID-19 pandemic to the increase of ethical discussion on their use.

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“…The cause of ASD is extremely complex, involving genetic and environmental factors [ 2 , 3 ]. In recent years, the number of children diagnosed with ASD has been increasing [ 4 , 5 ]. It is estimated that one in 160 children have autism [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

Application of Skeleton Data and Long Short-Term Memory in Action Recognition of Children with Autism Spectrum Disorder

Zhang

Tian

et al. 2021

Sensors

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The recognition of stereotyped action is one of the core diagnostic criteria of Autism Spectrum Disorder (ASD). However, it mainly relies on parent interviews and clinical observations, which lead to a long diagnosis cycle and prevents the ASD children from timely treatment. To speed up the recognition process of stereotyped actions, a method based on skeleton data and Long Short-Term Memory (LSTM) is proposed in this paper. In the first stage of our method, the OpenPose algorithm is used to obtain the initial skeleton data from the video of ASD children. Furthermore, four denoising methods are proposed to eliminate the noise of the initial skeleton data. In the second stage, we track multiple ASD children in the same scene by matching distance between current skeletons and previous skeletons. In the last stage, the neural network based on LSTM is proposed to classify the ASD children’s actions. The performed experiments show that our proposed method is effective for ASD children’s action recognition. Compared to the previous traditional schemes, our scheme has higher accuracy and is almost non-invasive for ASD children.

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Robot-Based Motor Rehabilitation in Autism: A Systematic Review

Cited by 31 publications

References 114 publications

Acceptance of Industrial Collaborative Robots by People With Disabilities in Sheltered Workshops

Acceptance of Industrial Collaborative Robots by People With Disabilities in Sheltered Workshops

The Social Robot in Rehabilitation and Assistance: What Is the Future?

Application of Skeleton Data and Long Short-Term Memory in Action Recognition of Children with Autism Spectrum Disorder

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