Early Diagnosis in ASD and personalized Training to PREVENT (ETAP)
Early Diagnosis in ASD and personalized Training to PREVENT (ETAP)
ERA-NET: Permed
Disciplines
Other Social Sciences (50%); Computer Sciences (50%)
Keywords
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Hci,
Autism Spectrum Disorder,
Games Research
An increasing number of children are affected by Autism Spectrum Disorders (ASD). Statistics show that one in every 44 children is affected by ASD, with boys being four times more likely to be affected than girls. ASD is accompanied by various severe cognitive issues, particularly the inability to recognize the emotions of others. Current therapy approaches include individual or small-group therapies, which are often expensive, inaccessible, and limited in availability. This poses a risk, given the rising number of autism diagnoses, that an entire generation may not be able to reach their full potential due to the lack of therapy options. Our project aims to provide individuals with ASD a broad, affordable, and accessible approach to emotional recognition training and therapy. We want to achieve this by combining cutting-edge technologies and the expertise of an interdisciplinary research team to create an individualized and virtual therapy environment. Our goal is to expand therapy possibilities for individuals with ASD and help them unlock their full potential. How does it work? Our solution is based on three key elements: 1. Hyperrealistic avatars capable of displaying detailed emotions: These avatars provide a lifelike representation of individuals, allowing those affected to engage with the emotions of others. The availability, scalability, and reproducibility of this system are essential in making therapy accessible to a larger population. 2. Emotional state assessment: Using various sensing methods and image recognition technology, we aim to analyze the emotional state of individuals. This includes measuring reaction rates during therapy tasks, stress levels (measured through skin conductance and heart rate), executive functions (such as inhibition control and attention), and behavioral patterns. Based on this personalized information, the system can provide targeted feedback. 3. Adaptive digital therapy methods that adjust to individual responses: We employ adaptive and gamified approaches to challenge and respond to the measured reactions of individuals. This allows for tailored, individualized, and effective therapy. The goal is to create a scalable platform that enables innovative and personalized therapy approaches while providing a broad and cost-effective access to emotional recognition training and therapy. Our aim is to ensure that more people can benefit from the advantages of emotional recognition training and unlock their full potential.
- Technische Universität Graz - 100%
- Lucas Paletta, Joanneum Research , national collaboration partner
Research Output
- 11 Citations
- 2 Publications
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2025
Title Large language models for autism: evaluating theory of mind tasks in a gamified environment DOI 10.1038/s41598-025-18608-4 Type Journal Article Author Poglitsch C Journal Scientific Reports Pages 34763 Link Publication -
2024
Title XR technologies to enhance the emotional skills of people with autism spectrum disorder: A systematic review DOI 10.1016/j.cag.2024.103942 Type Journal Article Author Poglitsch C Journal Computers & Graphics Pages 103942 Link Publication