Measurement and simulation of human-device interaction: application to lower-limb orthoses

人机交互的测量和模拟：在下肢矫形器中的应用

• 批准号: RGPIN-2018-04696
• 负责人: Brandon, Scott
• 金额: $ 1.97万
• 依托单位: University of Guelph
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=753172
• 关键词: Measurement; simulation; human; device; interaction

Over the next decade, there is expected to be a rapid proliferation of devices, such as braces and powered exoskeletons, that assist human locomotion. While passive braces have been used for years, and some exoskeleton devices are now approved for market, device designers still don't fully understand whether current devices are safe and effective, or how devices should be tuned to achieve optimal performance for different individuals. My research program will address two primary limitations in this field, with broad applications for devices that assist human motion. First, we don't have adequate tools to measure and predict how external assistive devices interact with soft tissues of human limbs. When external devices apply forces to the body, there is significant deformation of underlying skin, muscle, and fat. This induces misalignment of device and human joint axes, which not only affects the efficiency of force transmission but also causes undesirable and uncomfortable shear loading of skin and other tissues. In the proposed research, we will develop simple, low-cost devices to measure tissue stiffness across an individual's limb, then create computational models to predict how assistive device design might be optimized for each individual. We will develop and validate this approach using a progression of experimental test cases, beginning with simple 1-DOF indentation and culminating in full 6-DOF interaction between the human lower-limb and instrumented orthoses (e.g. knee and ankle braces) with both passive springs and active actuator controls.Second, we lack adequate tools to predict how the human neuromuscular system will respond when external devices apply forces to assist locomotion. Since it is not generally feasible to measure the forces generated by human muscles, computational models are often used to estimate muscle forces. Yet, traditional models assume that muscular efforts are coordinated only to maximize endurance, and these models do not account for altered muscle coordination patterns seen in people with disabilities, or people using external devices. In the proposed research, we will explore novel simulation approaches to estimate muscle forces while accounting for the stabilizing effect of external devices. Our approach will use a weighted combination of competing objectives to minimize metabolic cost while achieving the desired joint stiffness at hip, knee, and ankle joints. Finally, it is anticipated that the experimental and computational tools developed in this research program will yield direct benefits for assistive device designers in both academia and industry. Leveraging our experimental and computational expertise, it will be feasible to test how current devices affect internal loading of soft tissues muscles, ligaments, and cartilage - in the human body. New collaborations will lead to the design of novel, more effective assistive devices.

在接下来的十年里，预计将有一种快速扩散的设备，如支架和电动外骨骼，以帮助人类运动。虽然被动支架已经使用多年，一些外骨骼设备现在也得到了市场的批准，但设备设计者仍然不能完全理解当前的设备是否安全有效，或者设备应该如何调整才能为不同的个人实现最佳性能。我的研究计划将解决这一领域的两个主要限制，并广泛应用于辅助人体运动的设备。首先，我们没有足够的工具来测量和预测外部辅助设备如何与人体四肢软组织相互作用。当外部设备向身体施加力时，底层皮肤、肌肉和脂肪会发生显著变形。这会导致设备与人体关节轴不对准，不仅影响力的传递效率，还会导致皮肤和其他组织受到不希望的和不舒服的剪切载荷。在这项拟议的研究中，我们将开发简单、低成本的设备来测量个人肢体的组织硬度，然后创建计算模型来预测如何为每个人优化辅助设备设计。我们将使用一系列实验测试案例来开发和验证这一方法，从简单的1自由度压痕开始，最终实现人类下肢与带有被动弹簧和主动执行器控制的仪器化矫形器(如膝盖和脚踝支架)之间的完全6自由度交互。第二，我们缺乏足够的工具来预测当外部设备施加力帮助运动时人类神经肌肉系统将如何反应。由于测量人体肌肉产生的力通常是不可行的，所以经常使用计算模型来估计肌肉力。然而，传统的模型认为，肌肉的协调作用只是为了最大限度地提高耐力，而这些模型没有考虑到残疾人或使用外部设备的人的肌肉协调模式发生了变化。在拟议的研究中，我们将探索新的模拟方法来估计肌力，同时考虑外部设备的稳定效应。我们的方法将使用相互竞争的目标的加权组合来最小化代谢成本，同时在髋关节、膝关节和脚踝关节实现所需的关节僵硬。最后，预计在本研究计划中开发的实验和计算工具将为学术界和工业界的辅助设备设计者带来直接好处。利用我们的实验和计算专业知识，测试目前的设备如何影响人体内软组织肌肉、韧带和软骨的负载将是可行的。新的合作将导致设计出新的、更有效的辅助设备。