Digital Markers of Mobility in Daily Life to Track Progression in Newly Diagnosed Parkinson's Disease

项目概要/摘要 帕金森病（PD）和其他疾病的疾病改善干预措施的发展存在严重限制， 神经退行性疾病的一个重要原因是缺乏可靠的、客观的疾病进展指标。步行和 帕金森病早期出现转向功能障碍，使用惯性传感器测量行走和 翻身可以提供疾病进展以及生活质量下降的敏感、客观的标志。 新的可穿戴技术可以提供可靠，客观的行走和转弯措施， 临床试验然而，在无人监督的日常生活中量化行走和转弯， 有可能提供对疾病进展、生活质量更敏感的客观指标 和跌倒的风险。我们预测，车削质量可能甚至 在早期PD中，由于增加了动力学，比直走对疾病进展更敏感 平衡挑战。目的我将在100人中确定最敏感的流动性措施（日常生活）， 早期未经治疗的PD和50名老年对照受试者。我们假设无人监督的日常生活活动 措施将是敏感和具体的早期PD。目标二将确定日常生活中流动性的衡量标准 对疾病进展最敏感。我们假设，在日常生活中的转向特征（特别是 性能的可变性）将是最近3年内变化最敏感的流动性指标 被诊断出患有帕金森病的人Aim III将根据日常生活中行走的客观测量来预测未来的福尔斯， 转身。我们假设日常生活步态和转弯质量的客观测量将显着改善 与临床测量相比的谁将跌倒和首次跌倒时间的预测（即，跌倒风险）。识别 使用可穿戴设备进行真实的生活活动期间，一组最敏感的移动性残疾进展指标 技术将提供量化和客观的结果措施，以测试新的 改善疾病的疗法改善活动性下降的预后也将改善临床治疗的时机。 干预措施。

Project Summary/Abstract A critical limitation in development of disease-modifying interventions for Parkinson's disease (PD) and other neurodegenerative diseases is the lack of reliable, objective measures of disease progression. Walking and turning dysfunction appear early in Parkinson's disease and use of inertial sensors to measure walking and turning may provide sensitive, objective markers of disease progression as well as of decline in quality of life. New wearable technology can provide reliable, objective measures of walking and turning that are feasible for clinical trials. However, quantifying walking and turning during unsupervised, daily life has the untapped potential to provide objective measures that are even more sensitive to disease progression, to quality of life and fall risk than current subjective clinical measures of mobility. We predict that turning quality may be even more sensitive to progression of disease in early PD, than straight walking because of the added dynamic balance challenges. Aim I will determine the most sensitive measures of mobility (daily life) in 100 people with early, untreated PD and 50 older control subjects. We hypothesize that unsupervised daily life mobility measures will be sensitive and specific for early PD. Aim II will determine the measures of mobility in daily life most sensitive to disease progression. We hypothesize that turning characteristics during daily life (particularly variability of performance) will be the most sensitive mobility measures to change over 3 years in recently diagnosed people with PD. Aim III will predict future falls based on daily life objective measures of walking and turning. We hypothesize that objective measures of daily life gait and turning quality will significantly improve prediction of who will fall and time-to-first-fall compared to clinical measures (i.e., fall risk). Identification of the most sensitive set of measures of mobility disability progression during real life activities with wearable technology will provide quantifiable and objective outcome measures for testing the effectiveness of new disease-modifying therapies. Improved prognosis of mobility decline will also improve timing of clinical interventions.