Development, Evaluation and Translation of Robotic Apparel for Alleviating Low Back Pain

项目摘要/摘要 对于许多在建筑、制造、物流、医疗保健和 在农业方面，典型的工作日包括频繁的过度劳累活动(重复的弯曲、扭转、 提举和持续的屈曲姿势)会增加背部受伤的风险。劳累过度是最常见的 导致肌肉骨骼疾病(MSD)的事件-超过65%的MSD与过度劳累有关，以及 在所有导致休工天数的MSD中，有三分之一是由于禁用职业性慢性低血压造成的 背痛(CLBP)。大多数背部损伤被认为是非特异性的，因为确切的伤害原因通常是 无法辨认。在生物物理危险因素中，研究表明，累积和峰值负荷 背部是下腰痛的预测指标。举重是一项动态和高度可变的活动，是最 通常报道的导致腰背痛的事件，占所有腰痛急症的近三分之一 房间探访。举起姿势笨拙(不对称举起，水平或垂直负重距离较大)，以 高频率或多次重复会导致受伤风险增加，因为峰值增加 以及背部累积的机械载荷和疲劳效应。导致急性或急性死亡的主要因素 复发性背部损伤是通过背部过度的峰值和累积的力量而过度劳累，而原发性 参与急性腰背损伤进展为cLBP的因素包括不适应的运动控制策略， 肌肉过度活跃，运动变异性降低，以及恐惧认知的发展。这个项目将 专注于开发具有集成生物反馈组件的机器人服装可以减少体力消耗， 鼓励安全、多样化的运动策略，促进恢复。机器人服装将能够提供 通过响应动态的自适应控制算法，在需要时对背部和髋关节施加支撑力 行动，并在不再需要援助时变得完全透明。这项技术或许能够 用于预防过度运动的人的慢性腰痛；通过这种方式，机器人服装将 补充在许多手工材料处理职业中实施的人体工程学培训，以鼓励 在工作场所采取适当的起重策略。机器人服装还将为理疗师和 临床社区通过协助安全进展恢复正常来加强康复计划 活动，使人们能够更快地回到工作岗位，同时鼓励非适应不良的运动策略。 这项研究将采取分阶段的方法，并基于人在环中的开发过程， 通过频繁的人类主题研究评估组件和系统功能，其中量化(机器人， 生物力学和生理学)以及定性(即人为因素)数据将被收集。

PROJECT SUMMARY/ABSTRACT For many individuals working in industries such as construction, manufacturing, logistics, healthcare, and agriculture, a typical workday involves exposure to frequent overexertion activities (repetitive bending, twisting, lifting, and sustained flexion postures) that increase the risk of back injury. Overexertion is the most common event leading to musculoskeletal disorders (MSDs)—over 65% of MSDs are associated with overexertion, and one-third of all MSDs resulting in days away from work are accounted for by disabling occupational chronic low back pain (cLBP). A majority of back injuries are considered non-specific, as an exact nociceptive cause is often impossible to identify. Among biophysical risk factors, studies have shown that cumulative and peak loads on the back are predictors of low back pain. Lifting is a dynamic and highly variable activity and is the most commonly reported event leading to low back pain, accounting for nearly one-third of all back pain emergency room visits. Lifting with awkward poses (asymmetrical lifting, large horizontal or vertical load distances), at a high frequency, or performing multiple repetitions can result in an increased risk of injury due to increased peak and cumulative mechanical loading of the back and fatigue effects. A primary factor contributing to acute or recurrent back injury is overexertion via excessive peak and cumulative forces on the back, and that primary factors involved in the progression of acute low back injury to cLBP include maladaptive motor control strategies, muscle hyperactivity, reduced movement variability, and the development of fear cognitions. This project will focus on the development of robotic apparel with integrated biofeedback components can reduce exertion, encourage safe, varied movement strategies, and promote recovery. Robotic apparel will be capable of providing supportive forces to the back and hip joints when needed via adaptive control algorithms that respond to dynamic movements, and become fully transparent when assistance is no longer needed. This technology can may be able to be used to prevent cLBP in individuals who are exposed to overexertion; in this way, robotic apparel will supplement ergonomic training implemented in many manual materials handling occupations to encourage proper lifting strategies in the workplace. Robotic apparel will also provide a new tool to physical therapists and the clinical community to enhance rehabilitation programs by assisting in the safe progression back to normal activity, enabling people to get back to work sooner while encouraging non-maladaptive movement strategies. This research will undertake a staged approach and be based on a human-in-the-loop development process that evaluates component and system functions through frequent human subject studies, where quantitative (robot, biomechanical and physiological) as well as qualitative (i.e., human factors) data will be collected.