The IDEAS research project. Identifying autism spectrum disorder via automated analysis of speech and facial expression recognition.

Autor/inn/en	Kachel, Ulrike; Ritterfeld, Ute; Buschermöhle, Michael; Kugelmann, Klaus; Tuschen, Laura; Neitzel, Isabel; Pliska, Larissa; Blank, Stephanie; Dotzer, Maria; White, Lars O.; Radeloff, Daniel
Titel	The IDEAS research project. Identifying autism spectrum disorder via automated analysis of speech and facial expression recognition. Gefälligkeitsübersetzung: Vorstellung des Forschungsprojekts IDEAS. Identifikation von Menschen mit Autismus-Spektrum-Störung durch automatisierte Sprach- und Mimikerkennung.
Quelle	In: Kindheit und Entwicklung, 34 (2025) 2, S. 69-80Infoseite zur Zeitschrift PDF als Volltext Link als defekt meldenVerfügbarkeit
Sprache	englisch
Dokumenttyp	online; gedruckt; Zeitschriftenaufsatz
ISSN	0942-5403; 2190-6246
DOI	10.1026/0942-5403/a000485
Schlagwörter	Autismus; Gebärde; Psychodiagnostik; Screening-Verfahren; Augenbewegung; Natürliche Sprache; Sprachverarbeitung; App (Programm)
Abstract	Autism spectrum disorder (ASD) is a neurological developmental disorder that requires lifelong supportive measures. Receiving the diagnosis as early as possible can save valuable time before treatment, thereby reducing the severity of the condition and its attendant symptoms. The diagnostic process for ASD is a standardized clinical procedure that takes several hours and includes behavioral and cognitive assessments as well as interviews with patients and their relatives. It is associated with high costs in terms of the healthcare budget, including clinical resources such as highly qualified personnel, time, and other expenses. The shortage of qualified specialists creates a bottleneck that leads to long waiting lists and delays for patients before they can commence the diagnostic process. The IDEAS research project addresses this problem by developing and evaluating a digital ASD screening tool that enables the effective use of limited clinical resources. IDEAS addresses the relevant symptoms via automated analysis of speech, facial expressions, gestures, and eye-tracking. The screening tool will be implemented as an app for tablets and is closely aligned with the established clinical diagnostic process. This article presents considerations for the development of a digital screening tool, addressing challenges arising from the broad spectrum of symptoms associated with ASD and the unique characteristics of pediatric patients, including development tasks, methodological challenges, and general framework conditions within the clinical context. (ZPID).
Erfasst von	Leibniz-Institut für Psychologie, Trier
Update	2026/3