Tourette Syndrome (TS) is a neuropsychiatric disorder characterized by motor and vocal tics that can significantly impair quality of life. Traditionally, diagnosis and treatment rely on clinical assessments as well as pharmacological and behavioural interventions. In recent years, the advent of digital technologies and machine learning methodologies has opened new possibilities to improve diagnosis, monitoring, and personalized care for patients with TS. This mini-review provides an overview of the main developments in the field, including remote monitoring systems with wearable devices, machine learning predictive models for tic pattern identification, integrated management through eHealth platforms, and digital interventions such as evidence-based online therapy. Current limitations, ethical challenges, and future opportunities are discussed, with particular attention to the multidisciplinary integration of neuroscience, psychiatry, psychology, and digital health. This overview aims to offer an up-to-date foundation to foster the development of innovative and patient-centred strategies in TS management.
Di Vincenzo, C., Pontillo, M., Antonietti, A., Cancer, A., Demaria, F., Di Luzio, M., Menghini, D., Vicari, S., Digital health and Tourette Syndrome: new technological frontiers in diagnosis and management, 2026 [Altro]. 10.3389/fpsyt.2026.1765768 [https://hdl.handle.net/10807/337965]
Digital health and Tourette Syndrome: new technological frontiers in diagnosis and management
Di Vincenzo, CristinaPrimo
;Pontillo, Maria
;Antonietti, Alessandro;Cancer, Alice;Di Luzio, Michelangelo;Menghini, Deny;Vicari, Stefano
2026
Abstract
Tourette Syndrome (TS) is a neuropsychiatric disorder characterized by motor and vocal tics that can significantly impair quality of life. Traditionally, diagnosis and treatment rely on clinical assessments as well as pharmacological and behavioural interventions. In recent years, the advent of digital technologies and machine learning methodologies has opened new possibilities to improve diagnosis, monitoring, and personalized care for patients with TS. This mini-review provides an overview of the main developments in the field, including remote monitoring systems with wearable devices, machine learning predictive models for tic pattern identification, integrated management through eHealth platforms, and digital interventions such as evidence-based online therapy. Current limitations, ethical challenges, and future opportunities are discussed, with particular attention to the multidisciplinary integration of neuroscience, psychiatry, psychology, and digital health. This overview aims to offer an up-to-date foundation to foster the development of innovative and patient-centred strategies in TS management.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.



