Practice track: a learning tracker using digital biomarkers for autistic preschoolers

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Vorschaubild
Autor:innen
Autor:in (Körperschaft)
Publikationsdatum
2022
Typ der Arbeit
Studiengang
Typ
04B - Beitrag Konferenzschrift
Herausgeber:innen
Gerber, Aurona
Herausgeber:in (Körperschaft)
Betreuer:in
Übergeordnetes Werk
Proceedings of the Society 5.0 Conference 2022 - Integrating digital world and real world to resolve challenges in business and society
Themenheft
DOI der Originalpublikation
Link
Reihe / Serie
EPiC Series in Computing
Reihennummer
84
Jahrgang / Band
Ausgabe / Nummer
Seiten / Dauer
219-230
Patentnummer
Verlag / Herausgebende Institution
Verlagsort / Veranstaltungsort
Brugg-Windisch
Auflage
Version
Programmiersprache
Abtretungsempfänger:in
Praxispartner:in/Auftraggeber:in
Zusammenfassung
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.
Schlagwörter
Fachgebiet (DDC)
330 - Wirtschaft
Projekt
Veranstaltung
2nd Society 5.0 Conference 2022
Startdatum der Ausstellung
Enddatum der Ausstellung
Startdatum der Konferenz
20.06.2022
Enddatum der Konferenz
22.06.2022
Datum der letzten Prüfung
ISBN
ISSN
Sprache
Englisch
Während FHNW Zugehörigkeit erstellt
Ja
Zukunftsfelder FHNW
Publikationsstatus
Veröffentlicht
Begutachtung
Peer-Review der ganzen Publikation
Open Access-Status
Gold
Lizenz
'https://creativecommons.org/licenses/by/4.0/'
Zitation
SANDHU, Gurmit, Anne KILBURG, Andreas MARTIN, Charuta PANDE, Hans Friedrich WITSCHEL, Emanuele LAURENZI und Erik BILLING, 2022. Practice track: a learning tracker using digital biomarkers for autistic preschoolers. In: Knut HINKELMANN und Aurona GERBER (Hrsg.), Proceedings of the Society 5.0 Conference 2022 - Integrating digital world and real world to resolve challenges in business and society. Brugg-Windisch. 2022. S. 219–230. EPiC Series in Computing, 84. Verfügbar unter: https://doi.org/10.26041/fhnw-7293