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

描述（由申请人提供）：跌倒是老年人中常见的使人衰弱的问题，也是发病率的重要来源。本提案的目的是研究一种评估跌倒风险的新方法。在过去三十年中，在了解导致跌倒的因素方面取得了巨大进展，然而，评估工具尚未达到最佳水平。在临床上，可以通过观察步态分析来描述平衡、行走能力和跌倒风险。为了进一步了解，平衡和步态可能会受到挑战，例如，使用障碍赛道。然而，如果这些方法被证明是不够的，老年病专家或神经科医生需要了解患者在日常生活中进行日常活动时发生了什么，那么将依赖自我报告。事实上，尽管自我报告的主观性质和已知的召回问题，但目前在很大程度上，自我报告是跌倒频率和风险的黄金标准。我们建议，通过为希望评估跌倒的临床医生提供一种类似于心脏病专家的动态心电图监测仪的方法：近跌倒的动态监测（NF），可以获得很多好处。“差点摔倒”指的是失足、绊倒、绊倒或失去平衡，此时恢复机制被激活以防止摔倒。在较短的研究期内，NF的自动识别应该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动态监护仪识别NF的可能性。在实验室检测的初步工作中，主要是在年轻人中，我们能够达到高于85%灵敏度和85%特异性的检出率。本建议旨在为更大规模的效度研究搭建桥梁。为此，我们确定了以下具体目标：开发在实验室条件下自动识别老年人NF的算法。2. 开发和评估在现实条件下检测NF的算法（使用加速度计和陀螺仪并确定哪种配置和组合是理想的）。3. A)在研究参与者进行日常生活的日常活动时，通过运动传感器记录一个带注释的NF数据库。B)通过开放获取的nih资助的PhysioNet资源网站提供该档案。为了实现这些目标，30名有多次跌倒史的老年人、30名年龄匹配的对照组和10名有反复跌倒史的帕金森病患者将在实验室中使用先前建立的平衡、步态和跌倒风险测试进行测试。随后，他们将被要求连续3天佩戴动态监护仪。我们将评估哪些方法最适合检测NF以及NF与实验室测量之间的关系。这项探索性研究的结果应该有助于促进第三种方法来研究跌倒和跌倒风险，一种基于动态监测的方法，最终可能导致更全面的跌倒风险评估选择。

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.