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Develops digital biomarkers for tracking symptoms in Parkinson’s disease, suggesting better monitoring tools.
Executive summary AI-PROGNOSIS aims to develop a system of digital biomarkers for Parkinson’s disease (PD) monitoring and for informing predictive models of disease risk and prognosis. Deliverable D3.3 “Final report on digital biomarkers for PD” reports on the development of the final version of digital biomarkers (dBMs) for tracking PD symptoms and risk factors, including also results from the dBM-DEV study (NCT06444789) of the project. The focus is placed on motor and non-motor symptoms, including rest tremor, slowness of movement (bradykinesia), dyskinesias, REM Behaviour Disorder (RBD), daytime somnolence, overall physical activity, gross motor function, and cognitive function, using data from wearables, smartphone interaction, and digital active tests.
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Christos Chatzichristos (2026) studied this question.
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