ADAPTATION TO NOVEL FORCE FIELDS IN HEMIPARETIC STROKE

机器人操纵器被视为一种潜在的重要的康复工具，因为它们可以被编程为在受试者移动时施加各种力（力场）。它们也可以重复使用，同时监测和记录受试者的表现，允许比人类治疗师目前可行的更密集和更长时间的治疗。剩下的问题是什么类型的力场最适合于帮助偏瘫患者恢复运动功能，以及中风幸存者应该如何在这样的力场中训练。当正常受试者暴露在一个新的力场中，以系统的方式干扰他们的运动时，他们会逐渐适应，这样当干扰力场意外地被移除时，他们就会表现出特有的后效。最初的适应和后效都是在主体没有意识到适应过程的情况下发生的。由于后效可以通过神经肌肉骨骼系统的动态模型来预测，因此我计划使用动态建模技术作为设计力的工具，该力将在偏瘫中风患者中产生期望的后效，这些患者表现出刻板的运动错误。目前，有证据表明，偏瘫中风患者的恢复是加强时，他们的经验，辅助力场。其他证据表明，在伸展运动过程中对抗阻力场的训练也可能有助于患者在移除阻力场后执行所需的运动。该项目的主要目标是确定哪种类型的场-辅助性场或阻力性场-最适合实现理想的康复结果。为此，我将使用一个可编程的双连杆机器人，它在水平面上的伸展运动中施加力。我计划首先确定在多大程度上可以使后遗症持续下去。然后，我将开发和测试一个计算框架，设计辅助和阻力力场。最后将确定是否辅助或阻力力场是最适合调解所需的补偿效果对偏瘫中风幸存者的运动。这些实验的结果应该有利于开发和应用更复杂的康复环境，使用机器人，并提供了一个明确的方向，在该地区的机器人辅助康复更长期的临床试验。

Robotic manipulators are seen as a potentially important instrument for rehabilitation because they can be programmed to exert a variety of forces (force fields) while the subject moves. They can also be used repetitively, while monitoring and recording subject's performance, allowing more intensive and prolonged treatment than is currently feasible with a human therapist. The question that remains is what type of force field is best suited for assisting in the recovery of motor function in hemiparetic human subjects, and how should the stroke survivor be trained in such a force field. When normal subjects are exposed to a novel force field that disturbs their motion in a systematic fashion, they adapt progressively so that they exhibit characteristic after-effects when the disturbing force field is unexpectedly removed. Both the initial adaptation and the after-effects occur without subjects being aware of the adaptive process. Since after-effects can be predicted by dynamic models of the neuro-musculoskeletal system, I plan to use dynamic modeling techniques as a tool for designing forces that will yield desirable after- effects in hemiparetic stroke patients that show stereotypical errors in movement. Currently there is evidence that hemiparetic stroke patients recovery is enhanced when they experience assistive force fields. Other evidence suggests that training against resistive force fields during reaching movements may also help the patient perform a desirable motion once the resistive field is removed. The main goal of this project is to determine which type of field -- assistive or resistive -- is best suited to attaining desirable rehabilitation outcomes. To this end I will use a programmable two-link robot that exerts forces during reaching movements in the horizontal plane. I plan to determine first to what extent after-affects can be made to persist. I will then develop and test a computational framework that designs assistive and resistive force fields. Finally will determine whether assistive or resistive force fields are best suited for mediating the desired compensatory effects on movements in hemiparetic stroke survivors. The results of these experiments should favor the development and application of more sophisticated rehabilitation environments using robots and provide a clear direction for more long-term clinical trials in the area of robot assisted rehabilitation.