Continuous Monitoring of Turning in Patients with Parkinson's Disease

帕金森病患者翻身的持续监测

• 批准号: 8495435
• 负责人: FAY BAHLING HORAK
• 金额: $ 34.92万
• 依托单位: APDM, INC.
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-07-01 至 2015-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8495435
• 关键词: Acceleration; Address; Adverse effects; Affect; Age; Aging; Algorithms; Behavior; Biological Markers; Biomedical Engineering; Caregivers; Characteristics; Charge; Clinical; Clinical Trials; Communities; Complex; Computer software; Coupling; Data; Detection; Disease; Disease Progression; Docking; Elderly; Environment; Equilibrium; Event; Exercise; Fall prevention; Foundations; Fracture; Freezing; Future; Gait; Gait abnormality; Goals; Hip Fractures; Home environment; Impairment; Individual; Intervention; Laboratories; Locomotion; Measurement; Measures; Methods; Monitor; Motor; Motor Activity; Motor Skills; Movement; Movement Disorders; Neurosciences; Parkinson Disease; Patients; Performance; Pharmacologic Substance; Phase; Physicians; Research; Research Personnel; Risk; Sampling; Symptoms; System; Technology; Testing; Walking; clinical practice; data management; disability; equilibration disorder; fall risk; falls; graphical user interface; improved; improved mobility; indexing; innovation; instrument; interest; nervous system disorder; novel; sensor; tool

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.

描述（由申请人提供）：步行时安全转动的能力是受衰老和神经疾病影响的独立移动性的重要运动技能。转弯通常会导致帕金森氏病（PD）患者的“冷冻”和/或掉落，并且通常与髋部骨折有关。但是，要求PD患者在临床环境中执行转弯通常不会揭示其障碍。处于跌倒风险的患者将受益于确定和表征其日常活动行为的系统，以预测其跌倒，益处或治疗副作用以及疾病进展的风险。在自发的日常活动中，没有curren系统可以识别和表征绩效的特征。我们的长期目标是整日使用可穿戴传感器来开发和商业化独特的系统，以测量移动性（步态和动态平衡）。我们的OHSU/PSU初创公司APDM正在开发系统，以允许临床医生和临床研究人员使用其核心技术“蛋白石”运动监视器监测移动性和临床运动症状。我们已经确定了自动表征步态的价值，并在临床环境中在临床环境中开出了180度转弯，并在我们的ITUG应用程序中进行任务。现在，我们想添加一种将移动性监视的新产品进入家庭和社区。这个新的仪器系统（ITURN）将使患者可以自我监测自己的日常活动，并允许临床医生审查患者日常活动的天数或数周。该应用的目的是开发一种新颖的方法来识别和量化个人在日常生活中的转弯。这个特定的目的 第一阶段项目是：1）开发一种新的算法，该算法可以通过我们的蛋白石可穿戴传感器来识别和表征自发活动期间的转弯事件和2），以确定拥有较旧的受试者和具有PD的受试者的可行性，以使用docking站使用docking站，以将其传感器置于家庭中，并在家庭中连续监视后，将其上传到我们的服务器上。开发的算法以及用于家庭使用的硬件和软件适应性将用于构成我们II期项目的基础，该项目将测试帕金森氏病患者全天测量变动赤字的好处，以预测未来的跌倒。除了直行行走外，要监视转向性能的Abiliy还将为药物和运动临床试验提供重大突破，旨在改善移动性残疾 并为希望在自己的环境中安全行动能力的患者，看护人和临床医生提供强大的新工具。