Quantitative Results of Robot-Assisted Therapy for Children with Autism, ADHD and Delayed Speech Development

Zhanatkyzy, Aida; Telisheva, Zhansaule; Turarova, Aizada; Zhexenova, Zhanel; Sandygulova, Anara

doi:10.1145/3371382.3378254

Cited by 7 publications

(10 citation statements)

References 4 publications

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“…Most of the 94 included studies used robotics as the type of AI intervention to target participation among children and youth with disabilities or other diagnosed health conditions (72/94, 77%) [ 35 - 106 ], followed by HMI (51/94, 54%) [ 35 , 37 - 44 , 47 , 50 - 55 , 58 , 65 , 66 , 69 , 71 , 72 , 75 , 78 , 80 , 82 , 85 - 89 , 91 - 98 , 100 , 101 , 103 - 111 ], visualization and VR (19/94, 20%) [ 53 , 54 , 72 , 79 , 107 , 108 , 112 - 124 ], NLP (18/94, 19%) [ 36 , 47 , 52 , 64 , 71 , 78 , 79 , 82 , 91 , 101 , 103 - 105 , 120 , 125 - 128 ], ML (11/94, 12%), computer vision (10/94, 11%) [ 40 , 41 , 64 , 67 , 69 , 107 , 110 , 120 , 125 , 126 , 128 ], and constraint satisfaction and optimization (1/94, 1%; Table 1 ) [ 110 ]. Of the 72 studies on robotics, 63 (88%) studies...…”

Section: Resultsmentioning

confidence: 99%

“…Explicit + categorical: 35 [ 37 , 39 - 42 , 47 , 51 , 53 , 54 , 58 , 59 , 61 - 63 , 67 - 69 , 71 - 73 , 78 , 80 , 85 , 86 , 88 , 92 - 96 , 98 - 100 , 102 , 103 ]…”

Section: Resultsunclassified

“…In-person: 44 [ 35 , 37 - 44 , 47 , 50 , 52 - 55 , 57 , 58 , 65 , 66 , 69 , 71 , 72 , 75 , 78 , 80 , 82 , 86 - 89 , 91 , 93 , 94 , 96 - 98 , 101 , 103 - 107 , 109 , 111 ]…”

Section: Resultsunclassified

“…Most of the included studies described interventions using multiple applications of AI (60/94, 64%), such as robotics with HMI [ 35 - 44 , 47 , 50 - 55 , 57 , 58 , 63 - 67 , 69 , 71 , 72 , 75 , 78 - 80 , 82 , 85 - 89 , 91 - 98 , 100 , 101 , 103 - 108 , 112 , 120 , 125 - 128 ], or ML with NLP and constraint satisfaction and optimization [ 110 ]. Across these studies, robotics was most often integrated into interventions that employed multiple applications of AI.…”

Section: Resultsmentioning

confidence: 99%

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Artificial Intelligence in Rehabilitation Targeting the Participation of Children and Youth With Disabilities: Scoping Review

Kaelin¹,

Valizadeh²,

Salgado³

et al. 2021

J Med Internet Res

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Background In the last decade, there has been a rapid increase in research on the use of artificial intelligence (AI) to improve child and youth participation in daily life activities, which is a key rehabilitation outcome. However, existing reviews place variable focus on participation, are narrow in scope, and are restricted to select diagnoses, hindering interpretability regarding the existing scope of AI applications that target the participation of children and youth in a pediatric rehabilitation setting. Objective The aim of this scoping review is to examine how AI is integrated into pediatric rehabilitation interventions targeting the participation of children and youth with disabilities or other diagnosed health conditions in valued activities. Methods We conducted a comprehensive literature search using established Applied Health Sciences and Computer Science databases. Two independent researchers screened and selected the studies based on a systematic procedure. Inclusion criteria were as follows: participation was an explicit study aim or outcome or the targeted focus of the AI application; AI was applied as part of the provided and tested intervention; children or youth with a disability or other diagnosed health conditions were the focus of either the study or AI application or both; and the study was published in English. Data were mapped according to the types of AI, the mode of delivery, the type of personalization, and whether the intervention addressed individual goal-setting. Results The literature search identified 3029 documents, of which 94 met the inclusion criteria. Most of the included studies used multiple applications of AI with the highest prevalence of robotics (72/94, 77%) and human-machine interaction (51/94, 54%). Regarding mode of delivery, most of the included studies described an intervention delivered in-person (84/94, 89%), and only 11% (10/94) were delivered remotely. Most interventions were tailored to groups of individuals (93/94, 99%). Only 1% (1/94) of interventions was tailored to patients’ individually reported participation needs, and only one intervention (1/94, 1%) described individual goal-setting as part of their therapy process or intervention planning. Conclusions There is an increasing amount of research on interventions using AI to target the participation of children and youth with disabilities or other diagnosed health conditions, supporting the potential of using AI in pediatric rehabilitation. On the basis of our results, 3 major gaps for further research and development were identified: a lack of remotely delivered participation-focused interventions using AI; a lack of individual goal-setting integrated in interventions; and a lack of interventions tailored to individually reported participation needs of children, youth, or families.

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Section: Resultsmentioning

confidence: 99%

“…Explicit + categorical: 35 [ 37 , 39 - 42 , 47 , 51 , 53 , 54 , 58 , 59 , 61 - 63 , 67 - 69 , 71 - 73 , 78 , 80 , 85 , 86 , 88 , 92 - 96 , 98 - 100 , 102 , 103 ]…”

Section: Resultsunclassified

“…In-person: 44 [ 35 , 37 - 44 , 47 , 50 , 52 - 55 , 57 , 58 , 65 , 66 , 69 , 71 , 72 , 75 , 78 , 80 , 82 , 86 - 89 , 91 , 93 , 94 , 96 - 98 , 101 , 103 - 107 , 109 , 111 ]…”

Section: Resultsunclassified

Section: Resultsmentioning

confidence: 99%

See 2 more Smart Citations

Artificial Intelligence in Rehabilitation Targeting the Participation of Children and Youth With Disabilities: Scoping Review

Kaelin¹,

Valizadeh²,

Salgado³

et al. 2021

J Med Internet Res

View full text Add to dashboard Cite

show abstract

“…As for mode of delivery, most of the included studies described an intervention delivered in-person (84/94, 89%) [35][36][37][38][39][40][41][42][43][44][45][46][47][48][49][50][86][87][88][89][90][91]93,94,[96][97][98][99][101][102][103][104][105][106][107]109,[111][112][113][114][115][116][117][118][119][120][121][122][123][124]127], mainly using a one-on-one approach. A total of 11% (10/94)...…”

Section: Types Of Ai Intervention Mode Of Intervention Delivery and Type Of Personalizationmentioning

confidence: 99%

Artificial Intelligence in Rehabilitation Targeting the Participation of Children and Youth With Disabilities: Scoping Review (Preprint)

Kaelin¹,

Valizadeh²,

Salgado³

et al. 2020

Preprint

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BACKGROUND In the last decade, there has been a rapid increase in research on the use of artificial intelligence (AI) to improve child and youth participation in daily life activities, which is a key rehabilitation outcome. However, existing reviews place variable focus on participation, are narrow in scope, and are restricted to select diagnoses, hindering interpretability regarding the existing scope of AI applications that target the participation of children and youth in a pediatric rehabilitation setting. OBJECTIVE The aim of this scoping review is to examine how AI is integrated into pediatric rehabilitation interventions targeting the participation of children and youth with disabilities or other diagnosed health conditions in valued activities. METHODS We conducted a comprehensive literature search using established Applied Health Sciences and Computer Science databases. Two independent researchers screened and selected the studies based on a systematic procedure. Inclusion criteria were as follows: participation was an explicit study aim or outcome or the targeted focus of the AI application; AI was applied as part of the provided and tested intervention; children or youth with a disability or other diagnosed health conditions were the focus of either the study or AI application or both; and the study was published in English. Data were mapped according to the types of AI, the mode of delivery, the type of personalization, and whether the intervention addressed individual goal-setting. RESULTS The literature search identified 3029 documents, of which 94 met the inclusion criteria. Most of the included studies used multiple applications of AI with the highest prevalence of robotics (72/94, 77%) and human-machine interaction (51/94, 54%). Regarding mode of delivery, most of the included studies described an intervention delivered in-person (84/94, 89%), and only 11% (10/94) were delivered remotely. Most interventions were tailored to groups of individuals (93/94, 99%). Only 1% (1/94) of interventions was tailored to patients’ individually reported participation needs, and only one intervention (1/94, 1%) described individual goal-setting as part of their therapy process or intervention planning. CONCLUSIONS There is an increasing amount of research on interventions using AI to target the participation of children and youth with disabilities or other diagnosed health conditions, supporting the potential of using AI in pediatric rehabilitation. On the basis of our results, 3 major gaps for further research and development were identified: a lack of remotely delivered participation-focused interventions using AI; a lack of individual goal-setting integrated in interventions; and a lack of interventions tailored to individually reported participation needs of children, youth, or families.

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Robotic Technologies in ADHD Care: Literature Review

et al. 2022

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Robotics has made it possible to change and improve many support processes for vulnerable people in different settings. In recent years, its use has been oriented toward supporting therapeutic interventions of neurodevelopmental disorders (NDD), including attention deficit hyperactivity disorder (ADHD). This review of the literature highlights how advances in robotics have evolved in different scenarios of ADHD treatment, its collaboration with other emerging technologies, its results, its limitations, and the research challenges for the future development of robotics in the field of supporting children with ADHD. The authors conducted a literature review based on the location of keywords 'robotics' and several NNDs such as 'ADHD', 'Autism Spectrum Disorder (ASD)', 'cerebral palsy', and 'dementia' in titles, abstracts, and introduction of scientific articles in the Scopus and Web of Science (WoS) database. The reviewed literature was classified according to the type of therapy supported by the robots, the type of robot and the associated technologies. From this analysis, we can solve the research question: Which types of robots have the potential for specific applications in ADHD treatment? Furthermore, this article shows that despite favorable technical results, robotic technologies that support ADHD therapies require significant improvements in terms of scalability, human-machine interaction, and treatment and processing of acquired information to be applied effectively in real-world therapies. The most significant research challenges are proposed to drive research efforts to develop new approaches to enable robotic assistants to participate in ADHD therapies.

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Quantitative Results of Robot-Assisted Therapy for Children with Autism, ADHD and Delayed Speech Development

Cited by 7 publications

References 4 publications

Artificial Intelligence in Rehabilitation Targeting the Participation of Children and Youth With Disabilities: Scoping Review

Artificial Intelligence in Rehabilitation Targeting the Participation of Children and Youth With Disabilities: Scoping Review

Artificial Intelligence in Rehabilitation Targeting the Participation of Children and Youth With Disabilities: Scoping Review (Preprint)

Robotic Technologies in ADHD Care: Literature Review

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