Objective-based Iterative Learning Control for Robotics and Rehabilitation

机器人和康复的基于目标的迭代学习控制

• 批准号: EP/G014078/1
• 负责人: Christopher Freeman
• 金额: $ 29.93万
• 依托单位: University of Southampton
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2009
• 资助国家: 英国
• 起止时间: 2009 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FG014078%2F1
• 关键词: Objective; based; Iterative; Learning; Control

The purpose of this project is to develop and significantly enhance an exciting new technology that has been shown to help stroke patients regain arm function. This technology is based on using Electrical Stimulation to assist subjects in performing arm movements which they cannot otherwise manage. By making muscles work, Electrical Stimulation solves the problem that people have when they try to re-learn skills after having a stroke. This problem is that re-learning skills takes practice, and this requires feedback which you can't get when you are unable to move your arm at all. The way in which people re-learn skills after a stroke is exactly the same process as you do when you learn to play tennis. You become better at it, because new nerve connections have been made within your brain and spinal cord. Not only do you need to practice, but you also need feedback of your performance so that you can correct your movement.When Electrical Stimulation is applied to muscles, electrical impulses travel along the nerves in much the same way as the electrical impulses from your brain. If stimulation is carefully controlled, a useful movement can be made. The re-learning process works better if the person is attempting the movement themselves. Recent innovative research has exploited this fact by combining a person's own effort with just enough Electrical Stimulation to achieve the intended movement. This research involved subjects performing horizontal reaching movements with Electrical Stimulation applied to their triceps. Their task was to track a spot of light as it moved slowly in front of them, and a technique called 'Iterative Learning' was used to decide what stimulation to apply to help them perform the tracking task accurately. By carefully varying this stimulation to best assist the subject, this research has established that Electrical Stimulation is able to help people re-learn movement after a stroke.The aim of this project is to maximise the therapeutic benefit of Electrical Stimulation during treatment. Foundations will also be laid that are necessary for the development of an inexpensive system that can be used in patient's own homes to increase access to this innovative technology. The way in which this will be done is to develop 'Iterative Learning' into a much more powerful and flexible tool for governing the stimulation. It will then be used to help people perform far more natural movements such as picking up a bottle and pouring from it, pressing a series of buttons, and turning a handle. Since these sort of tasks are important for day to day living, the technology then directly helps patients re-learn the tasks that are most useful to them. Another advantage is that the 'Iterative Learning' will also be able to respond to the wishes of the physiotherapist who supervises the treatment. If they decide that the movement the subject is trying to do is not ideal, they will have the freedom to change the way in which the stimulation helps the subject perform the movement. Furthermore, the simple way in which the tasks are presented to people means that very little equipment is needed, as there is no trajectory to display, no form of constraint to the movement, nor any robotic assistance used. This therefore removes a substantial obstacle preventing the technology from moving from the lab and into patient's homes.Although stroke rehabilitation is the application focussed on, the added flexibility given to 'Iterative Learning' will also benefit many processes that are found in industry. Examples of these include robots which perform the same operation over and over again in production lines. This flexibility will give the way in which the repeated task is performed the freedom to vary in order to maximise efficiency, respond to changes in the task, and satisfy desired constraints. This will all be achieved whilst still maintaining a high degree of accuracy.

该项目的目的是开发并显着增强一项令人兴奋的新技术，该技术已被证明可以帮助中风患者恢复手臂功能。该技术基于使用电刺激来帮助受试者执行他们无法进行的手臂运动。通过使肌肉发挥作用，电刺激解决了人们在中风后尝试重新学习技能时遇到的问题。这个问题是，重新学习技能需要练习，而这需要反馈，而当你根本无法移动手臂时，你就无法获得反馈。人们在中风后重新学习技能的方式与你学习打网球时的过程完全相同。你会变得更擅长，因为你的大脑和脊髓内已经建立了新的神经连接。您不仅需要练习，还需要对您的表现进行反馈，以便纠正您的动作。当对肌肉施加电刺激时，电脉冲沿着神经传播，就像来自大脑的电脉冲一样。如果仔细控制刺激，就可以做出有用的运动。如果一个人自己尝试这个动作，重新学习的过程效果会更好。最近的创新研究利用了这一事实，通过将人自己的努力与足够的电刺激相结合来实现预期的运动。这项研究涉及受试者通过对三头肌施加电刺激来进行水平伸展运动。他们的任务是跟踪在他们面前缓慢移动的光点，并使用一种称为“迭代学习”的技术来决定应用什么刺激来帮助他们准确地执行跟踪任务。通过仔细改变这种刺激以最好地帮助受试者，这项研究已经确定电刺激能够帮助人们在中风后重新学习运动。该项目的目的是在治疗过程中最大限度地发挥电刺激的治疗效果。还将为开发可在患者自己家中使用的廉价系统奠定必要的基础，以增加对这一创新技术的使用。实现这一目标的方法是将“迭代学习”发展成为一种更强大、更灵活的刺激管理工具。然后，它将用于帮助人们执行更自然的动作，例如拿起瓶子并从中倒水、按下一系列按钮以及转动手柄。由于此类任务对于日常生活很重要，因此该技术可以直接帮助患者重新学习对他们最有用的任务。另一个优点是“迭代学习”还能够响应监督治疗的物理治疗师的愿望。如果他们认为受试者尝试做的运动不理想，他们将可以自由地改变刺激帮助受试者执行运动的方式。此外，向人们呈现任务的简单方式意味着需要很少的设备，因为没有可显示的轨迹，没有对运动的任何形式的约束，也没有使用任何机器人辅助。因此，这消除了阻止该技术从实验室转移到患者家中的重大障碍。虽然中风康复是该应用的重点，但“迭代学习”所增加的灵活性也将使工业中的许多流程受益。例如，机器人在生产线上一遍又一遍地执行相同的操作。这种灵活性将使执行重复任务的方式可以自由变化，以便最大限度地提高效率、响应任务的变化并满足所需的约束。这一切都将在保持高精度的同时实现。

项目成果

Model and experience-based initial input construction for iterative learning control

用于迭代学习控制的模型和基于经验的初始输入构建

• DOI: 10.1002/acs.1209
• 发表时间: 2010
• 期刊: International Journal of Adaptive Control and Signal Processing
• 影响因子: 3.1
• 作者: Freeman C

Phase-lead iterative learning control algorithms for functional electrical stimulation-based stroke rehabilitation

• DOI: 10.1177/0959651811408976
• 发表时间: 2011-09-01
• 期刊: PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING
• 影响因子: 1.6
• 作者: Freeman, C. T.;Tong, D.;Burridge, J. H.
• 通讯作者: Burridge, J. H.

The application of precisely controlled functional electrical stimulation to the shoulder, elbow and wrist for upper limb stroke rehabilitation: a feasibility study.

• DOI: 10.1186/1743-0003-11-105
• 发表时间: 2014-06-30
• 期刊: Journal of neuroengineering and rehabilitation
• 影响因子: 5.1
• 作者: Meadmore KL;Exell TA;Hallewell E;Hughes AM;Freeman CT;Kutlu M;Benson V;Rogers E;Burridge JH
• 通讯作者: Burridge JH

Functional electrical stimulation mediated by iterative learning control and 3D robotics reduces motor impairment in chronic stroke.

• DOI: 10.1186/1743-0003-9-32
• 发表时间: 2012-06-07
• 期刊: Journal of neuroengineering and rehabilitation
• 影响因子: 5.1
• 作者: Meadmore KL;Hughes AM;Freeman CT;Cai Z;Tong D;Burridge JH;Rogers E
• 通讯作者: Rogers E