Floor Monitor for Gait Assessment and Falls Detection

用于步态评估和跌倒检测的地板监视器

• 批准号: 6742741
• 负责人: MARTIN Carl BARUCH
• 金额: $ 10.08万
• 依托单位: EMPIRICAL TECHNOLOGIES CORPORATION
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-03-15 至 2005-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6742741
• 关键词: clinical research; gait; human middle age (35-64); human subject; monitoring device; technology /technique development

DESCRIPTION (provided by applicant): Falls among the elderly, one of the most common reasons requiring medical intervention and a contributing factor in 40% of nursing home admissions, are a major health problem. Several studies have identified quantifiable gait markers that appear to distinguish between elderly "fallers" and non-fallers. These studies have relied on data acquired in gait-laboratories. Extending gait assessment capability, and falls detection, into the home could provide valuable before-the-fact information on gait weakness evolution, which in turn could be used to assess the efficiency of counter measures. Current mobile gait analysis techniques are insufficient because they rely on compliance or are too intrusive. The development of a new gait assessment and falls monitor is proposed. The device is passive, can transmit acquired data wirelessly, and obtains gait data from sensing floor vibrations, precluding the need to wear a device, walk on special surfaces or be observed by cameras. Its ability to detect different gait modes with high fidelity as well as differentiate between falling objects and simulated falls has been demonstrated. This study's principal aim is to validate the device's performance through a comparison with accepted gait assessment techniques at the Physical Medicine and Rehabilitation Gait lab at the University of Virginia Health System.

描述（由申请人提供）：老年人中的福尔斯是需要医疗干预的最常见原因之一，也是40%的疗养院入院的一个促成因素，是一个主要的健康问题。几项研究已经确定了可量化的步态标记，似乎可以区分老年人“跌倒者”和非跌倒者。这些研究依赖于步态实验室获得的数据。将步态评估能力和福尔斯检测扩展到家庭中可以提供关于步态弱点演变的有价值的事前信息，这反过来可以用于评估对抗措施的效率。目前的移动的步态分析技术是不够的，因为它们依赖于顺应性或过于侵入。 提出了一种新的步态评估和福尔斯监测仪的开发。该设备是被动的，可以无线传输采集的数据，并通过感应地板振动获得步态数据，从而无需佩戴设备，在特殊表面上行走或通过摄像头观察。它能够检测不同的步态模式与高保真度，以及区分下降的物体和模拟福尔斯已被证明。这项研究的主要目的是通过与弗吉尼亚大学健康系统物理医学和康复步态实验室接受的步态评估技术进行比较来验证该设备的性能。