End-point robot manipulandum

我目前的大部分研究项目涉及调查感觉运动学习。具体来说，我的工作特征是感觉可塑性在运动学习中的作用，这个成功的项目自2005年以来一直由我的NSERC发现基金资助。本研究计划探讨视觉和感觉诱导（本体感受）对手臂运动学习和运动控制的贡献，以及手部运动的本体感受（感觉）敏锐度。能够严格测量和控制手臂的运动是量化本体感觉敏锐度和理解以及模拟其对运动学习和运动控制的贡献所必需的。我已经发表了36篇同行评议的文章（仅在过去的5年里就发表了11篇），这些文章都涉及到使用cfi资助的InMotion2机器人操纵器（我在2005年获得的）来仔细控制手部的运动。经过15年的常规使用，尽管更换了所有的计算机组件，这台机械手已经不能再运行了。为了继续这项重要的研究，我们迫切需要购买一个替代品，比如Kinarm端点机器人，以实现我的nserc资助项目的目标，即研究和模拟大脑如何结合不同类型的感觉信息来控制和适应运动。这样的替换也将使我的hqp能够完成他们的论文，并继续进行本地和国际合作，这将有利于加拿大在这一领域获得高知名度。此外，一个新的机器人操纵平台也将允许我纳入更复杂的虚拟现实刺激，从而扩展我的研究计划，以解决大脑如何学习，并存储与对象交互所必需的对象和工具动态信息。我的研究结果将提供对大脑用于控制、纠正、适应和学习新动作的信息来源的更丰富的理解，以及这些信息整合背后的神经机制。结果将不仅提供基本的洞察我们的效应器的位置估计，也为我们如何学习与我们互动和操纵的物体的运动相关属性。这对于开发更容易操作和导航的工具和环境具有重要的实际好处。总的来说，从拟议的研究中获得的见解将导致康复技术的改进，更好的人机界面，以及更好的运动技能训练，以适应各种水平的表现。

Much of my current research program involves investigating sensorimotor learning. Specifically, my work characterizes the role of sensory plasticity in motor learning and this successful program has been continuously funded by my NSERC Discovery Grants since 2005. This research program investigates both the visual and sensory induced (proprioceptive) contributions to motor learning and motor control of the arm, as well as proprioceptive (felt) acuity of the hand motion. Being able to rigorously measure and control movements of the arm is necessary to quantify proprioceptive acuity and understanding and model its contribution to motor learning and motor control. I have published 36 peer-reviewed articles (11 in the past 5 years alone) that involved these carefully controlled movement of the hand using a CFI-funded InMotion2 robot manipulandum that I acquired in 2005. After 15 years of regular use, this manipulandum is no longer operating despite replacing all the computer components. To continue this important research, it is urgent that we purchase a replacement, like a Kinarm endpoint robot, to fulfill the goals of my NSERC-funded program to investigate and model how the brain combines different types of sensory information to control and adapt movements. Such replacement will also allow my HQPs to complete their dissertations and continue local and international collaborations which will benefit Canada to gain high profile in this field. Moreover, a new robot manipulandum platform would also allow me to incorporate more sophisticated virtual reality stimuli and thereby expand my research program to address how the brain learns, and stores information about object and tool dynamics that are necessary for interacting with objects. The results of my research will provide a richer understanding of the sources of information used by the brain for controlling, correcting, adapting and learning new movements, and the neural mechanisms underlying the incorporation of this information. The results will provide not only fundamental insight into location estimates of our effectors, but also into how we learn movement-related properties of objects that we interact with and manipulate. This has important practical benefits for the development of tools and environments that are easier to manipulate and navigate. In general, the insights gained from the proposed research will lead to improved technology for rehabilitation, better human-machine interfaces, and better motor-skills training for all levels of performance.