Sensor-based remote monitoring could help better track Parkinson’s disease (PD) progression, and measure patients’ response to putative disease-modifying therapeutic interventions. To be useful, the remotely-collected measurements should be valid, reliable, and sensitive to change, and people with PD must engage with the technology. We developed a smartwatch-based active assessment that enables unsupervised measurement of motor signs of PD. Participants with early-stage PD (N = 388, 64% men, average age 63) wore a smartwatch for a median of 390 days. Participants performed unsupervised motor tasks both in-clinic (once) and remotely (twice weekly for one year). Dropout rate was 5.4%. Median wear-time was 21.1 h/day, and 59% of per-protocol remote assessments were completed. Analytical validation was established for in-clinic measurements, which showed moderate-to-strong correlations with consensus MDS-UPDRS Part III ratings for rest tremor (⍴ = 0.70), bradykinesia (⍴ = −0.62), and gait (⍴ = −0.46). Test-retest reliability of remote measurements, aggregated monthly, was good-to-excellent (ICC = 0.75–0.96). Remote measurements were sensitive to the known effects of dopaminergic medication (on vs off Cohen’s d = 0.19–0.54). Of note, in-clinic assessments often did not reflect the patients’ typical status at home. This demonstrates the feasibility of smartwatch-based unsupervised active tests, and establishes the analytical validity of associated digital measurements. Weekly measurements provide a real-life distribution of disease severity, as it fluctuates longitudinally. Sensitivity to medication-induced change and improved reliability imply that these methods could help reduce sample sizes needed to demonstrate a response to therapeutic interventions or disease progression.

基于传感器的远程监控可以帮助更好地跟踪帕金森病 (PD) 的进展，并测量患者对假定的疾病缓解治疗干预措施的反应。为了发挥作用，远程收集的测量结果应该有效、可靠并且对变化敏感，患有 PD 的人必须参与这项技术。我们开发了一种基于智能手表的主动评估，可以在无人监督的情况下测量 PD 的运动体征。患有早期 PD 的参与者 ( N = 388，64% 为男性，平均年龄 63 岁）佩戴智能手表的中位数为 390 天。参与者在诊所（一次）和远程（每周两次，持续一年）执行无人监督的运动任务。辍学率为5.4%。平均佩戴时间为 21.1 小时/天，完成了 59% 的符合协议的远程评估。为临床测量建立了分析验证，显示与静止震颤 (⍴ = 0.70)、运动迟缓 (⍴ = −0.62) 和步态 (⍴ = −0.46) 的共识 MDS-UPDRS 第 III 部分评级有中度至强相关性). 每月汇总的远程测量的重测可靠性从好到极好 (ICC = 0.75–0.96)。远程测量对多巴胺能药物的已知作用很敏感（开与关 Cohen's d = 0.19–0.54）。值得注意的是，临床评估通常不能反映患者在家中的典型状态。这证明了基于智能手表的无监督主动测试的可行性，并建立了相关数字测量的分析有效性。每周测量提供了疾病严重程度的真实分布，因为它是纵向波动的。对药物引起的变化的敏感性和提高的可靠性意味着这些方法可以帮助减少证明对治疗干预或疾病进展的反应所需的样本量。