Design of Human-Robot Interaction for Novel Interlimb Motor Adaptation Scenarios

新型肢体间运动适应场景的人机交互设计

• 批准号: RGPIN-2016-03859
• 负责人: VanderLoos, Hendrik
• 金额: $ 1.89万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=708874
• 关键词: Design; Human; Robot; Interaction; Novel

The long-term objectives of my research program are: 1) to discover human sensorimotor adaptations, through the application of robotics principles, that can ultimately be exploited, based on the principles/mechanisms elucidated in this Discovery Grant program, in novel therapy regimens; 2) to enhance motor adaptation, through adaptive interaction design and 3) to drive functionality up and cost down through new formulations of human-robot mechatronic devices and sensate wearable technologies. In the short term, during the next five years I propose to advance each of these areas through the following initiatives: 1) To characterize upper-limb movement synergies through research studies that engage participants in bimanual motor tasks under a variety of stimulus-response conditions. Asymmetries in bimanual movements reduce movement quality in both able-bodied persons and those who have become hemiparetic (weak on one side) as a result of, for example, a stroke. Normal and accentuated asymmetries provide an opportunity to study neural mechanisms of motor adaptation in the adult nervous system. Two robots, with one being controlled by the kinematics of the other using novel algorithms, will allow participants to focus attention on their asymmetries during bimanual reaching motions. Practice is expected to lead to quantifiable improvements in interlimb coordination and the characterization of motor adaptation. 2) To create motor adaptation scenarios involving the upper and lower limbs simultaneously in balance and reaching tasks. Over the past 5 years, we have developed RISER, a robotic platform to study human balance, lower-limb motor adaptation, and interlimb coordination. I propose to augment our platform with mechanisms and sensors to allow all four limbs of a participant standing on RISER to be involved in a balance task or in a bimanual reaching task. The goal is to explore different combinations of sensor gains for upper and lower limbs, and for left and right limbs, to focus participant attention on asymmetries and synergies in their movements. The characterization of motor adaptation under different robot-mediated conditions can lead to an improved understanding of the neural mechanisms involved in the human control of movement. 3) To develop robust, lower-cost, wearable mechatronic devices with embedded sensing, actuator and display capabilities. The research studies described above require augmentations, in both hardware and software, to the robot devices currently available in our lab. To provide the unconventional stimuli needed, the goal is to develop partially wearable systems, in combination with robot arms and our platform set up as programmable exercise and balance devices. Multi-sensor and -actuator systems require an iterative user-centred approach to real-time programming and pilot testing to assess human reactions to novel interaction experiences.

我的研究计划的长期目标是：1）通过应用机器人原理来发现人类感觉运动适应，并最终可以根据本发现资助计划中阐明的原理/机制，在新颖的治疗方案中加以利用； 2）通过自适应交互设计来增强运动适应性，3）通过人机机电设备和传感可穿戴技术的新配方来提高功能并降低成本。 短期内，我建议在未来五年内通过以下举措推进这些领域的发展： 1）通过让参与者在各种刺激-反应条件下参与双手运动任务的研究来表征上肢运动协同作用。双手运动的不对称会降低身体健全者和因中风等原因导致偏瘫（一侧无力）的人的运动质量。正常和严重的不对称性为研究成人神经系统运动适应的神经机制提供了机会。两个机器人，其中一个由另一个使用新颖算法的运动学控制，将允许参与者在双手伸手动作期间将注意力集中在他们的不对称性上。实践预计将导致肢体间协调和运动适应特征的可量化改善。 2）创建涉及上肢和下肢同时完成平衡和伸展任务的运动适应场景。在过去的 5 年里，我们开发了 RISER，一个用于研究人体平衡、下肢运动适应和肢体间协调的机器人平台。我建议通过机制和传感器来增强我们的平台，让站在 RISER 上的参与者的所有四个肢体都参与平衡任务或双手伸展任务。目标是探索上肢和下肢以及左肢和右肢传感器增益的不同组合，以将参与者的注意力集中在其运动中的不对称性和协同性上。 在不同机器人介导的条件下运动适应的表征可以提高对人类运动控制所涉及的神经机制的理解。 3) 开发具有嵌入式传感、执行器和显示功能的稳健、低成本、可穿戴机电一体化设备。上述研究需要对我们实验室目前可用的机器人设备进行硬件和软件方面的增强。为了提供所需的非常规刺激，我们的目标是开发部分可穿戴系统，结合机械臂和我们设置为可编程锻炼和平衡设备的平台。多传感器和执行器系统需要采用以用户为中心的迭代方法进行实时编程和试点测试，以评估人类对新颖交互体验的反应。