Ambulatory Monitoring of Near Falls: A Novel Measure of Fall Risk

临近跌倒的动态监测：跌倒风险的一种新测量方法

• 批准号: 7896176
• 负责人: JEFFREY M HAUSDORFF
• 金额: $ 14.47万
• 依托单位: TEL-AVIV SOURASKY MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-08-15 至 2012-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7896176
• 关键词: Acceleration; Activities of Daily Living; Age; Algorithms; Ambulatory Monitoring; Archives; Area; Arrhythmia; Back; Cardiac; Cardiovascular system; Characteristics; Chronic; Clinic; Communities; Databases; Detection; Elderly; Electrocardiogram; Environment; Equilibrium; Evaluation; Exercise stress test; Frequencies; Funding; Gait; Gold; Health Care Costs; Holter Electrocardiography; Home environment; Hour; Laboratories; Lead; Life; Measures; Medicine; Memory; Methods; Metric; Modality; Morbidity - disease rate; Motivation; Movement; Nature; Neurologist; Outcome; Parkinson Disease; Participant; Patient Self-Report; Patients; Performance; Population Heterogeneity; Predisposition; Property; Recording of previous events; Recovery; Recurrence; Resources; Rest; Risk; Risk Assessment; Risk Factors; Source; Specificity; Speed; Stress Tests; Techniques; Testing; Time; Treatment Efficacy; Walking; Work; base; design; experience; fall risk; falls; gait examination; improved; insight; interest; mortality; novel; novel strategies; prevent; prospective; public health relevance; research clinical testing; sensor; success; tool; web site; young adult

DESCRIPTION (provided by applicant): Falls are a common, debilitating problem among older adults and a significant source of morbidity. The objective of the present proposal is to investigate a novel approach to the evaluation of fall risk. During the past three decades, tremendous advances have been made in the understanding of the factors that contribute to falls, however, assessment tools are not yet optimal. In the clinic, observational gait analysis may be performed to characterize balance, walking abilities and fall risk. For further insight, balance and gait may be challenged, e.g., using an obstacle course. However, if these approaches prove insufficient and the geriatrician or neurologist needs to understand what occurs as a patient carries out routine activities of daily living, self-report will be relied upon. In fact, despite its subjective nature and the known problems concerning recall, self-report is currently, to a large degree, the gold standard of fall frequency and risk. We suggest that much can be gained by offering the clinician who wishes to evaluate falls an approach similar to that of the cardiologist's Holter monitor: ambulatory monitoring of near falls (NF). A near fall refers to a misstep, trip, stumble or loss of balance in which recovery mechanisms are activated to prevent a fall. Automatic identification of NF should, a priori, provide a sensitive and objective marker of fall risk, perhaps over a shorter study period. We recently began to investigate the potential of using an ambulatory monitor to identify NF. In preliminary work in laboratory testing, mostly in young adults, we were able to achieve detection rates better than 85% sensitivity and 85% specificity. The present proposal is designed as a bridge to larger scale validity studies. To this end, we have defined the following specific aims: 1. To develop algorithms to automatically identify NF in older adults under laboratory conditions. 2. To develop and evaluate algorithms for the detection of NF (using accelerometers and gyroscopes and determining which configuration and combinations are ideal) in real-world conditions. 3. A) To establish an annotated data base of NF, as recorded by movement sensors, as study participants carry out their routine activities of daily living. B) To make this archive available via the open-access NIH-funded PhysioNet Resource website. To achieve these objectives, 30 older adults with a history of multiple falls, 30 age-matched controls and 10 patients with Parkinson's disease with a history of recurrent falls will be tested in the lab using previously established tests of balance, gait and fall risk. Subsequently, they will be asked to wear an ambulatory monitor for 3 consecutive days. We will assess which methods optimally detect NF and the association between NF and laboratory-based measures. The results of this exploratory study should help to promote a third approach to the study of falls and falls risk, one based on ambulatory monitoring that may, ultimately, lead to more comprehensive fall risk assessment options. PUBLIC HEALTH RELEVANCE: Falls in older adult are a major cause of morbidity and mortality, with significant associated healthcare costs. We suggest that much can be gained by developing a new approach to fall risk assessment: ambulatory monitoring of near falls. Automatic identification of near falls (e.g., trips, missteps, stumbles), as subjects carry out their routine activities of daily living, may provide a sensitive and objective marker of fall risk based on actual performance that may, ultimately, lead to improved assessment and treatment options.

描述（由申请人提供）：跌倒是老年人的常见，令人衰弱的问题，也是发病率的重要来源。本提案的目的是研究一种新的评估跌倒风险的方法。在过去的三十年中，在理解导致跌倒的因素方面取得了巨大进步，但是评估工具尚不最佳。在诊所中，可以进行观察步态分析以表征平衡，步行能力和跌倒风险。为了进一步的见识，可能会挑战平衡和步态，例如使用障碍物。但是，如果这些方法证明不足，老年医生或神经科医生需要了解随着患者进行日常生活的常规活动，则将依靠自我报告。实际上，尽管具有主观性质和有关召回的已知问题，但自我报告目前在很大程度上是秋季频率和风险的黄金标准。 我们建议，通过提供希望评估的临床医生可以获得很多与心脏病专家的恐怖仪监测仪类似的方法：近瀑布（NF）的卧床监测。近秋天是指将恢复机制激活以防止跌倒的失误，旅行，绊倒或失去平衡。自动识别NF应该在较短的研究期内提供一个敏感和客观的跌倒风险标记。我们最近开始研究使用卧床监测器识别NF的潜力。在实验室测试的初步工作（主要是在年轻人中），我们能够获得比85％敏感性和85％的特异性的检测率。本提案被设计为进行大规模有效性研究的桥梁。为此，我们定义了以下特定目的：1。开发算法以在实验室条件下自动识别老年人的NF。 2。为了开发和评估算法以检测NF（使用加速度计和陀螺仪，并确定在实际条件下哪些构型和组合是理想的）。 3。 b）通过开放式NIH资助的Physionet Resource网站使此档案馆可用。为了实现这些目标，将使用先前确定的平衡，步态和下落风险的测试在实验室中测试了30名具有多个跌倒病史，30个年龄匹配的对照病史的老年人和10例具有经常性跌倒史的患者。随后，他们将连续3天要求他们穿着卧床监视器。我们将评估哪些方法最佳检测NF以及NF与基于实验室的措施之间的关联。这项探索性研究的结果应有助于促进第三种方法来研究跌倒和跌倒风险，这是基于卧床监测的，最终可能会导致更全面的跌倒风险评估选择。 公共卫生相关性：老年人跌倒是发病率和死亡率的主要原因，具有显着相关的医疗费用。我们建议通过开发一种新的跌落风险评估方法来获得很多收益：对近瀑布的门诊监测。由于受试者进行日常生活的常规活动，可以自动识别近跌倒（例如旅行，失误，绊脚石），可能会基于实际绩效提供敏感和客观的秋季风险标记，最终可能会改善评估和治疗方案。