Monitoring of Parkinson’s disease (PD) has seen substantial improvement over recent years as digital sensors enable a passive and continuous collection of information in the home environment. However, the primary focus of this work has been motor symptoms, with little focus on the non-motor aspects of the disease. To address this, we combined longitudinal clinical non-motor assessment data and digital multi-sensor data from the Verily Study Watch for 149 participants from the Parkinson’s Progression Monitoring Initiative (PPMI) cohort with a diagnosis of PD. We show that digitally collected physical activity and sleep measures significantly relate to clinical non-motor assessments of cognitive, autonomic, and daily living impairment. However, the poor predictive performance we observed, highlights the need for better targeted digital outcome measures to enable monitoring of non-motor symptoms.

近年来，随着数字传感器能够被动、连续地收集家庭环境中的信息，帕金森病 (PD) 的监测取得了显着的进步。然而，这项工作的主要焦点是运动症状，很少关注疾病的非运动方面。为了解决这个问题，我们将纵向临床非运动评估数据和来自 Verily 研究观察的数字多传感器数据结合起来，这些数据来自帕金森病进展监测计划 (PPMI) 队列的 149 名参与者，诊断为帕金森病。我们表明，数字收集的身体活动和睡眠测量与认知、自主神经和日常生活障碍的临床非运动评估显着相关。然而，我们观察到的预测性能不佳，凸显了需要更有针对性的数字结果测量来监测非运动症状。