FALL BIOMECHANICS AND HIP FRACTURE RISK

描述：(来自应用程序的逐字记录)跌倒和跌倒相关 伤害是最严重、最常见、代价高昂的医疗问题 老年人。在美国，每年大约有3000万次瀑布，大约每1次 第二，在1000万人中。此外，在大约30万名髋关节中， 每年发生的骨折中，90%以上与跌倒有关。我们有 如前所述，向一侧坠落并对臀部产生影响是相关的 髋部骨折风险增加20倍以上(与 与骨密度降低相关的风险增加3倍)。因此， 当筛选干预措施和骨折预防计划时 (药物、粗隆填充物或锻炼)，成本要低得多 从公共卫生的角度有效和高效地尝试确定 每年将有1000万老年人摔倒(现在可以使用 相对简单的现场测试)，而不是集中在500,000到60万 老年受试者将向一侧摔倒(对于可比的受试者 测试尚未推出)。此竞争性续订申请的目标是 都专注于这个目标。在上一个资助期内，我们完成了 目标1：侧滑的动力学，演示缓慢的步态速度和 跌倒或晕倒的姿势障碍与跌倒有关 侧面和对臀部的影响。我们还开发了第一个可用的 多节段，全身模型摔倒，并展示了它是一个 这是研究向一侧坠落的生物动力学的有力工具。为我们的 上一个目标2：侧跌风险指数，我们完成了开发和 拟议指数的细化阶段，表明线性 串联步态、髋关节外展力量、步速不对称的组合 从快速测试，并摇摆变量时，站在 半串联体位可用于区分老年受试者 从所有其他方向摔倒的人都倒在一边。在我们新的 拟议目标1：验证侧向坠落风险指数(SFRI)，我们将确定 我们在之前的投资中开发的侧向跌落风险指数 Period可以前瞻性地用来识别哪些老年受试者会患上 在边上。作为我们之前关于侧落动力学的工作的延伸， 在目标2：步态可变性作为侧向跌倒的预测因子，我们将分析 老年跌倒者在仪器化平台上行走时的地面压力时程 垫子。我们将把现代信号分析理论应用于地压时间。 历史。利用混沌理论和分形学分析并注意到 心血管和神经肌肉病理的特点是 分别观察心率和步态的规律性，我们将判断步态是否 根据地压时间历史确定的参数可用于 识别摔倒在一侧的虚弱的老年受试者。

DESCRIPTION: (Verbatim from the application) Falls and fall-related injuries are the most serious, common costly medical problems facing the elderly. In the US each year there are about 30 millions falls, or about 1 per second, among 10 million fallers. In addition, of the approximately 300,000 hip fractures that occur each year, over 90% are associated with falls. We have shown previously that falls to the side with impact on the hip are associated with more than 20-fold increase in the risk of hip fractures (compared to a 3-fold increase in risk associated with reduced bone density). Thus, when screening for interventions and fracture prevention programs (pharmaceutical agents, trochanter padding or exercise), it is far less cost effective and efficient from a public health perspective to attempt to identify the 10 million elderly who will fall each year (which can now be done using relatively simple field tests) than it is to focus on the 500,000 to 600,000 elderly subjects who will fall to the side (for which comparable validated tests are not yet available). The aims of this competitive renewal application are focused on this goal. During the previous funding period, we completed the goals of Aim 1: Dynamics of Side Falls, demonstrating that slow gait speed and the postural disturbances of slipping or fainting are associated with falls to the side and impact on the hip. We have also developed the first available multi‑segment, whole body model for falling and showed it to be a powerful tool for studying the biodynamics of falling to the side. For our previous Aim 2: Side Fall Risk Index, we completed both the development and refinement phases of the proposed index, demonstrating that a linear combination of tandem gait, hip abduction strength, step velocity asymmetry from the quick-step test, and sway variables while standing in a semi-tandem position could be used to distinguish elderly subjects who fell to the side from those who fell in all other directions. Under our new proposed Aim 1: Validation of Side Fall Risk Index (SFRI), we will determine whether the Side Fall Risk Index we have developed during the previous funding period can be used prospectively to identify elderly subjects who will fall to the side. As an extension of our previous work on the dynamics of side falls, under Aim 2: Gait Variability as a Predictor of Side Falls we will analyze the ground pressure time histories of elderly fallers ambulating on an instrumented mat. We will apply modern signal analysis theory to the ground pressure time histories. Using chaos theory and fractal analysis and noting that cardiovascular and neuromuscular pathologies are characterized by increased regularity of heartbeat and gait, respectively, we will determine if gait parameters determined from ground pressure time histories can be used to identify frail elderly subjects who fall to the side.