Collaborative Research: Adaptive Control and Functional Electrical Stimulation for the Control and Understanding of Muscle Dynamics.

合作研究：用于控制和理解肌肉动力学的自适应控制和功能性电刺激。

• 批准号: 0828114
• 负责人: Alexander Leonessa
• 金额: $ 20.8万
• 依托单位: Virginia Polytechnic Institute and State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-01 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0828114&HistoricalAwards=false
• 关键词: Collaborative; Research; Adaptive; Control; Functional

CBET-0828114LeonessaFunctional electrical stimulation (FES) is a neuroprosthesis technique used to restore the motor function of individuals with spinal cord injuries (SCI). For SCI patients, there are some muscles below the injury level which are still innervated, though not volitionally controllable. The principle of FES is to use surface or implantable electrodes to generate pulses of current in intact motor neurons. This is done to induce contraction of these muscles and corresponding joint movement. Several challenges hinder the application of closed-loop FES outside of research labs, such as that muscles present highly nonlinear and time-varying characteristics. Furthermore, a stimulated muscle changes when fatigue occurs, and muscle models are different for each individual type of muscle. Even more challenging is the fact that there is a significant delay between stimulation and muscle contraction, adding to the processing and transmission delays in the electrical stimulation system. Research efforts in this project will focus on the development a Model Reference Adaptive Control approach which utilizes the approximation capabilities of Neural Networks. This approach addresses several open problems including uncertain and unmodeled dynamics, actuator dynamics, actuator amplitude and rate saturations, delays, and discrete and real-time implementation. The control algorithm is tested using a muscle-driven forward dynamic model of the lower limb as implemented using OpenSim, a publicly-available musculoskeletal modeling and simulation software environment. An experimental setup is developed to test, understand, and compare muscle dynamics in both open and closed-loop situations. The merit of this effort includes the extension of current nonlinear control techniques, such as backstepping, dynamic surfacing, and model reference adaptive control, to account for time delays, actuator amplitude and rate saturation limitations, and partial and noisy measurements, thereby substantially increasing the practical applicability of such algorithms. The real-time implementation and the requirement that the FES equipment is easy to setup and simple to use by therapists and patients add additional constraints to the control structure, which needs to be robust yet not overly complicated. Advanced control techniques developed by control engineers have not previously been merged with the advanced neuromusculoskeletal models and the biological understanding of clinicians and biomechanists. Doing so will increase knowledge of muscle characteristics and could lead to the development of an enhanced prosthetic system. This research effort offers many potential benefits to society, including the possibility of improving the quality of life for patients with paralysis, as well as individuals with other neuromuscular disability including traumatic brain injury, multiple sclerosis, and cerebral palsy. Development of a robust control strategy in cooperation with muscle-driven simulations of movement will provide a framework for guiding rehabilitation strategies for specific impairments. Through a potential future collaboration with rehabilitation researchers and clinicians on the Wake Forest medical campus, the techniques developed as part of this effort will be applied to specific patient populations. From an educational point of view, students from the Mechanical Engineering and Human Nutrition, Foods and Exercise Departments, and Biomedical Engineering will work together to learn and experience in lectures and labs the application of closed loop control techniques to bioengineering problems, bolstering their interest in this field. The interdisciplinary aspects of bioengineering will be covered and disseminated through course development and outreach.

CBET-0828114LEONESSAFUSSICAL性电刺激（FES）是一种神经假体技术，用于恢复脊髓损伤患者的运动功能（SCI）。对于SCI患者，损伤水平以下的一些肌肉仍被神经支配，尽管在自愿性无法控制的情况下。 FES的原理是使用表面或可植入电极来产生完整运动神经元中电流的脉冲。这样做是为了引起这些肌肉的收缩和相应的关节运动。一些挑战阻碍了研究实验室之外的闭环FES的应用，例如肌肉具有高度非线性和随时间变化的特征。此外，疲劳发生时刺激的肌肉变化，每种单独的肌肉肌肉模型都不同。更具挑战性的是，刺激和肌肉收缩之间存在显着延迟，从而增加了电刺激系统中的处理和传播延迟。该项目的研究工作将集中于开发一种模型参考自适应控制方法，该方法利用神经网络的近似功能。该方法解决了几个开放问题，包括不确定和未建模的动态，执行器动力学，执行器振幅和速率饱和，延迟以及离散和实时实现。使用Opensim实现的肌肉驱动的下肢的肌肉驱动的向前动态模型对控制算法进行了测试，这是一种公共可用的肌肉骨骼建模和仿真软件环境。开发了一个实验设置，以测试，理解和比较开环和闭环情况下的肌肉动力学。这项工作的优点包括扩展当前的非线性控制技术，例如反向刺激，动态表面和模型参考自适应控制，以说明时间延迟，执行器振幅和速率饱和度限制以及部分和嘈杂的测量，从而实质上增加了此类算法的实际适用性。实时实施以及FES设备易于设置，治疗师和患者易于使用的要求，对控制结构增加了其他限制，这需要坚固耐用，却不过于复杂。控制工程师开发的先进控制技术以前尚未与先进的神经肌肉骨骼模型以及对临床医生和生物力学的生物学理解合并。这样做将增加对肌肉特征的知识，并可能导致增强的假肢系统的发展。这项研究工作为社会带来了许多潜在的好处，包括改善麻痹患者的生活质量以及其他神经肌肉残疾的患者，包括脑外伤，多发性硬化症和大脑麻痹。与肌肉驱动的运动模拟合作制定强大的控制策略将为指导特定损害的康复策略提供一个框架。通过与Wake Forest医疗校园的康复研究人员和临床医生的潜在合作，作为这项工作的一部分开发的技术将应用于特定的患者人群。从教育的角度来看，机械工程和人类营养，食品和运动部门以及生物医学工程的学生将共同努力，学习和经验在讲座上，并实验封闭环控制技术在生物工程问题上的应用，并在该领域增强他们的兴趣。生物工程的跨学科方面将通过课程开发和宣传来涵盖和传播。