Longitudinal monitoring of motor symptoms in Parkinson’s disease using smartwatch and smartphone app digital biomarkers

As part of a case–control study investigating Parkinson’s disease (PD) progression through clinical imaging and wet biomarker techniques, we utilised smartwatch and smartphone technology to identify potential markers of PD and evaluate their validity in terms of sensitivity to symptom severity and progression. Digital outcome measures were passively (smartwatch) and actively (task assessments) recorded and processed with cross-sectional, longitudinal (up to 24 months), and bivariate analyses. 26 patients with idiopathic PD on dopamine-replacement therapy and 18 healthy controls (HC) participated. 18 passive and 21 active measures could significantly distinguish PD from HC. Measures associated with tremor, daily walking, active motion tasks, and voice-related tasks were the most sensitive. Free living during early morning and OFF-medication assessment measures were able to effectively track symptom deteriorations. Overall, these findings show that smartwatch/smartphone technology can be used to surface candidate digital measures that characterize PD, and that voice changes, as well as motion measures, may be suitable for assessing longitudinal, symptom-related change in individuals with idiopathic PD on dopamine-replacement therapy.