Continuous Monitoring of Turning in Patients with Parkinson's Disease

描述（由申请人提供）：行走时安全转身的能力是一项重要的运动技能，对于受年龄和神经系统疾病影响的独立行动。帕金森氏症（PD）患者的翻身通常会导致“冻结”和/或摔倒，通常与髋部骨折有关。然而，要求PD患者在临床环境中执行一个转弯通常并不能揭示他们的损伤。有跌倒风险的患者将受益于一个系统，该系统可以识别和描述他们的日常活动行为，以预测他们跌倒的风险、治疗的益处或副作用以及疾病的进展。目前还没有一种系统能够在自发的日常活动中不显眼地识别和表征转弯性能。我们的长期目标是开发一种独特的系统并将其商业化，该系统可以全天使用可穿戴传感器来测量移动性（步态和动态平衡）。我们的OHSU/PSU初创公司APDM正在开发系统，使临床医生和临床研究人员能够使用他们的核心技术“Opal”运动监测器来监测活动和临床运动症状。我们已经通过ITUG应用程序在起床和走任务中建立了在临床环境中自动表征步态和规定180度转弯的价值。我们现在想添加一个新产品，将移动监控带入家庭和社区。这种新的仪器化系统（itturn）将允许患者自我监测自己的日常活动，并允许临床医生回顾患者几天或几周的日常活动情况。本应用程序的目的是开发一种新的方法来识别和量化个人在日常生活中的转变。这个的具体目的

DESCRIPTION (provided by applicant): The ability to turn safely while walking is an important motor skill for independent mobility that is affected by aging and neurological diseases. Turning often results in 'freezing' and/or falling in patients with Parkinson's disease (PD), and is commonly associated with hip fractures. However, asking a PD patient to execute a turn in a clinical environment often does not reveal their impairments. Patients at risk for a fall would benefit from a system that identifies and characterizes their daily mobility behavior to predict their risk of falling, benefits or side effects of treatment, and progression of disease. No curren system exists that identifies and characterizes turning performance unobtrusively during spontaneous, daily activity. Our long-term goal is to develop and commercialize a unique system to measure mobility (gait and dynamic balance) using wearable sensors throughout the day. Our OHSU/PSU start-up company, APDM, is developing systems to allow clinicians and clinical researchers to monitor mobility and clinical motor symptoms using their core technology, 'Opal' movement monitors. We already have established the value of automatically characterizing gait and prescribed 180-degree turns in clinical environments during a Get Up and Go task with our ITUG application. We now want to add a new product that takes mobility monitoring into the home and community. This new, instrumented system (ITurn) will allow patients to self-monitor their own daily mobility and allow clinicians to review days or weeks of their patient's daily mobility. The objective of this application is to develop a novel method to identify and quantify turns made by individuals during their daily lives. The specific aims of this Phase I project are: 1) To develop a new algorithm that identifies and characterizes turning events during spontaneous activity with our Opal wearable sensors and 2) To determine the feasibility of having older subjects and subjects with PD to use a docking station to recharge their sensors and upload data onto our server after continuous monitoring in the home. The algorithms developed and hardware and software adaptations made for home use will be used to form the foundation of our Phase II project that will test the benefits of measuring turning deficits throughout the day in patients with Parkinson's disease to predict future falls. The abiliy to monitor turning performance, in addition to straight ahead walking, will provide a major breakthrough for pharmaceutical and exercise clinical trials aimed at improving mobility disability and provide a powerful new tool for patients, caregivers and clinicians who want more accurate information about their ability to safely ambulate in their own environments.