A scalable and customizable multimedia framework for behavioral intervention

Trevisan, Diogo Fernando; Araujo, Fernanda A. B. de; Benitez, Priscila; Góis, João Paulo

doi:10.1007/s40692-020-00181-6

Cited by 1 publication

(2 citation statements)

References 24 publications

(15 reference statements)

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“…The third category of tools is for the treatment or monitoring of children with autism. In the study by Trevisan et al [13] which focuses on developing a framework for educational activities to support professionals during cognitive therapy for children with autism. The tool, created using modular and dynamic templates, can also be used for normal children by other education professionals.. Other studies consist of using interactive robots to interact with autistic children in therapy sessions as summarised in the work of Ramirez et al [24], such as irobiQ and Caro [25],…”

Section: Related Workmentioning

confidence: 99%

“…The second aspect focused on capturing emotions based on facial expres- 3) Therapists General Feedback: Professionals were invited to evaluate the framework in different aspects and give feedback for future improvements. Their feedback was collected through a questionnaire inspired from the study of [13] and divided into two parts as displayed in figure 11. For the numerical part of the questionnaire, the scores given are considered to be favourable to the framework as shown in Figure 12.…”

Section: ) Children Related Observationsmentioning

confidence: 99%

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Friendy: A Deep Learning based Framework for Assisting in Young Autistic Children Psychotherapy Interventions

Hadri¹,

Bouramoul²

2023

JCOMSS

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The management of children with autism is a complex and challenging task due to the symptoms related to the disorder that affect their cognitive and behavioral functioning. This makes it difficult for them to process information and adapt to new situations, leading to non-cooperative tendencies during therapy sessions, which can slow down their progress. To support professionals and enhance the therapy experience for these children, a deep learning and contextual chatbot technology based framework, named "Friendy," has been proposed and implemented. The results of its performance testing show a high accuracy rate of 80.5% and the experimentation with independent professionals demonstrate its promising potential for scalability and integration into future therapy processes. The framework provides a valuable solution to the difficulties encountered in the management of children with autism, offering an innovative and effective approach to their care.

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Section: Related Workmentioning

confidence: 99%

Section: ) Children Related Observationsmentioning

confidence: 99%