Practice track: a learning tracker using digital biomarkers for autistic preschoolers
Loading...
Author (Corporation)
Publication date
2022
Typ of student thesis
Course of study
Collections
Type
04B - Conference paper
Editors
Editor (Corporation)
Supervisor
Parent work
Proceedings of the Society 5.0 Conference 2022 - Integrating digital world and real world to resolve challenges in business and society
Special issue
DOI of the original publication
Link
Series
EPiC Series in Computing
Series number
84
Volume
Issue / Number
Pages / Duration
219-230
Patent number
Publisher / Publishing institution
Place of publication / Event location
Brugg-Windisch
Edition
Version
Programming language
Assignee
Practice partner / Client
Abstract
Preschool children, when diagnosed with Autism Spectrum Disorder (ASD), often ex- perience a long and painful journey on their way to self-advocacy. Access to standard of care is poor, with long waiting times and the feeling of stigmatization in many social set- tings. Early interventions in ASD have been found to deliver promising results, but have a high cost for all stakeholders. Some recent studies have suggested that digital biomarkers (e.g., eye gaze), tracked using affordable wearable devices such as smartphones or tablets, could play a role in identifying children with special needs. In this paper, we discuss the possibility of supporting neurodiverse children with technologies based on digital biomark- ers which can help to a) monitor the performance of children diagnosed with ASD and b) predict those who would benefit most from early interventions. We describe an ongoing feasibility study that uses the “DREAM dataset”, stemming from a clinical study with 61 pre-school children diagnosed with ASD, to identify digital biomarkers informative for the child’s progression on tasks such as imitation of gestures. We describe our vision of a tool that will use these prediction models and that ASD pre-schoolers could use to train certain social skills at home. Our discussion includes the settings in which this usage could be embedded.
Keywords
Subject (DDC)
Event
2nd Society 5.0 Conference 2022
Exhibition start date
Exhibition end date
Conference start date
20.06.2022
Conference end date
22.06.2022
Date of the last check
ISBN
ISSN
Language
English
Created during FHNW affiliation
Yes
Strategic action fields FHNW
Publication status
Published
Review
Peer review of the complete publication
Open access category
Gold
License
Citation
Sandhu, G., Kilburg, A., Martin, A., Pande, C., Witschel, H. F., Laurenzi, E., & Billing, E. (2022). Practice track: a learning tracker using digital biomarkers for autistic preschoolers. In K. Hinkelmann & A. Gerber (Eds.), Proceedings of the Society 5.0 Conference 2022 - Integrating digital world and real world to resolve challenges in business and society (pp. 219–230). https://doi.org/10.29007/m2jx