Muscle Fatigue, Gait Alterations and Increased Energy Cost of Walking in Aging

项目总结 保持机动性是延长我们健康寿命的基础。机动性下降的原因可能是 疲劳性，这是一种新的衡量性能恶化和随之而来的 感知到的努力。老年人的肌肉疲劳(最大功率随着活动的减少)，而且更严重 有活动障碍的人的学位，可能通过改变在衰老中的疲劳性 肌肉协调，导致步态机制改变和更高的新陈代谢成本。我们的科学 提出肌肉疲劳作用的前提是建立在强有力的证据基础上的，即老年人有更多 大运动肌在低负荷、高速最大向心收缩时的肌肉疲劳； 与年轻人相比，跑步机步行导致的膝关节伸肌疲劳更严重。然而， 缺乏证据表明肌肉疲劳是如何导致年龄或损伤相关的肌肉无力改变的。 步态神经力学，以及与步行成本和疲劳性的联系。我们的总体目标是生成一个 通过量化神经机械效应和能量来理解疲劳性的新框架 肌肉疲劳对步态的影响，因此可以采取有效的干预措施来防止或扭转疲劳性 被追捕。我们的中心假设是，肌肉疲劳通过加剧年龄相关的疲劳而导致疲劳性 步态力学和可变性的变化(目标1)通过步态控制和协调的变化(目标1) 2)，这样，在肌肉疲劳的情况下，老年人步行需要更多的能量(目标3)。为了测试这一点 假设，将收集4组数据，每组15名男性和15名女性：久坐的年轻人(30-40岁)和 老年(70-80岁)健康成年人、行动不便的老年人(70-80岁)和活跃的老年人(70-80岁)。这 这些群体的组合将使我们能够评估年龄、体力活动和活动能力的独立影响 损害，并测试性影响。除活动较多的老年人外，所有群体都将相对久坐，类似于 普通的美国人。我们将使用我们新的生理和临床相关的30分钟跑步机 步行导致腿部肌肉疲劳，并通过步态力学和步态测量量化反应 步行的可变性、肌电和能量成本。基于模型的步态计算机模拟 代表四个组将有助于从机械上理解步态的肌肉基础 全身能量学的适应和后果。建模和实验的方法是 紧密结合，以确定个别肌肉如何有助于疲劳诱导的步态力学和 随着年龄和残疾的增加，步行的能量消耗增加(目标2和3)。需要解决的问题是- 疲劳性及其在老龄化中对机动性的影响--NIH和NIA的既定目标。项目成功将 通过弥合现有的知识鸿沟，从肌肉无力和疲劳到 疲劳性，目前阻碍了许多老年人实现最佳健康寿命。

PROJECT SUMMARY Maintaining mobility is fundamental to extending our healthspan. Reduced mobility may be driven by fatigability, a new metric that quantifies deterioration in performance and the accompanying increase in perceived effort. Muscle fatigue (decrease in maximal power with activity) in older adults, and to a greater degree in those with mobility impairments, could contribute to greater fatigability in aging through changes in muscle coordination, leading to altered gait mechanics and a higher metabolic cost of walking. Ourscientific premise for the proposed role of muscle fatigue is built on robust evidence that older adults have greater muscle fatigue in major locomotor muscles during low-load, high-velocity maximal concentric contractions; and greater knee extensor muscle fatigue in response to a treadmill walk than younger adults. However, evidence is lacking for how muscle fatigue compounds age- or impairment-related muscle weakness to alter gait neuromechanics, and the connections to cost of walking and fatigability. Our overall goal is to generate a new framework for understanding fatigability by quantifying the neuromechanical effects and energetic consequences of muscle fatigue on gait, so that efficacious interventions to prevent or reverse fatigability can be pursued. Our central hypothesis is that muscle fatigue contributes to fatigability by exacerbating age-related changes in gait mechanics and variability (Aim 1) through changes in the control and coordination of gait (Aim 2), such that with muscle fatigue greater energy is required for walking in older adults (Aim 3). To test this hypothesis, data will be gathered for 4 groups of 15 men and 15 women each: sedentary young (30-40 yr) and older (70-80) healthy adults, mobility-impaired older adults (70-80), and active older adults (70-80 yr). This combination of groups will allow us to evaluate the independent effects of age, physical activity and mobility impairment, and test for sex effects. All groups, except the active older, will be relatively sedentary, similar to the general US population. We will use our new, physiologically- and clinically-relevant 30 minute treadmill walk to cause lower-extremity muscle fatigue and quantify the response with measures of gait mechanics and variability, electromyography, and energy cost of walking. Computer simulations of walking based on models representing the 4 groups will help provide a mechanistic understanding of the muscular basis for the gait adaptations and consequences for whole body energetics. The modeling and experimental approaches are tightly integrated to identify how individual muscles contribute to fatigue-induced altered gait mechanics and increased energy cost of walking with age and impairment (Aim 2 & 3). The problem to be addressed- fatigability and its impact on mobility in aging- tackles stated goals of the NIH and NIA. Project success will have a significant impact by bridging an existing knowledge gap from muscle weakness and fatigue to the fatigability that currently prevents many older adults from achieving an optimal healthspan.