MRI: Development of New Instrumentation to Measure Upper Extremity Motion for Research and Teaching in Rehabilitation Science, Bioengineering and Robotics.

MRI：开发测量上肢运动的新仪器，用于康复科学、生物工程和机器人学的研究和教学。

• 批准号: 0722575
• 负责人: Naomi Gerber
• 金额: $ 50万
• 依托单位: George Mason University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0722575&HistoricalAwards=false
• 关键词: MRI; Development; New; Instrumentation; Measure

Proposal #: CNS 07-22575PI(s): Gerber, Naomi L. DeJong, Kenneth A.; Duric, ZoranInstitution: George Mason University Fairfax, VA 22030-4443Title: MRI/Dev.: New Instrumentation to Measure Upper Extremity Motion for Research and Teaching in Rehabilitation Science, Bioengineering and Robotics Project Proposed:This project, developing new instrumentation for the study of upper extremity activity in humans and mobile robots, aims to assist people with impaired extremity function in maintaining independence and employment. The work integrates independent advances in quantitative data collection through haptic technologies, wireless myoelectric sensors, motion capture technologies, and computer vision to solve some of the challenges in designing robots that extend capabilities in friendly and hostile environments. Since a primary shortcoming of existing instrumentation for upper extremity activity is lack of quantitative data collection that does not interfere with natural movement, a newly developed wireless instrumentation quantifies upper extremity motion to assess requirements for human function and robotic activity. The instrumentation captures and integrates in real time kinematic, kinetic (force and torques data), kinesthetic (proprioceptive), myoelectric data, and computer vision and motion analysis data, specifically integrating force data collected from haptic devices, 6-degrees-of-freedom motion data collected from wireless electromagnetic sensors ("flock of birds"), myoelectric data from strategically placed surface electrodes, and motion analysis data collected from digitized visual data. Thus, the project enables. Combining existing instrumentation to permit real time feedback to subjects or robots to correct movement patterns, extinguish muscle activity, and/or reduce force;. Quantifying stereotypic upper extremity activities ranging from a fluid, continuous pointing task to a high torque power grip activity;. Breaking movement patterns and their associated forces into simpler components or primitives (an approach that has been very effective in providing useful graphic-user interface in current haptic research); and. Assessing which combinations are most significant to completer various tasks.The instrumentation also allows exploring tele-control of force feedback to explore feasibility of its use in robotic control and assistive technology for people with upper extremity impairments, particularly for robots in hostile environments and for people in remote areas.Broader Impact: The instrumentation will also be used for supporting existing and new courses on motion analysis, human-machine computer science, haptics and rehabilitation science. Moreover, it contributes to interdisciplinary collaborations within the institution and with a small business. The infrastructure is likely to be commercialized, and the research results disseminated through usual venues.

提案编号：CNS 07- 22575 PI：Gerber，Naomi L. DeJong，Kenneth A.;机构：乔治梅森大学 费尔法克斯，VA 22030- 4443标题： MRI/器械：用于康复科学、生物工程和机器人学研究和教学的测量上肢运动的新仪器项目建议：该项目开发用于研究人类和移动的机器人上肢活动的新仪器，旨在帮助肢体功能受损的人保持独立和就业。这项工作通过触觉技术、无线肌电传感器、运动捕捉技术和计算机视觉整合了定量数据收集方面的独立进展，以解决设计机器人时面临的一些挑战，这些机器人可以在友好和恶劣的环境中扩展功能。由于上肢活动的现有仪器的主要缺点是缺乏不干扰自然运动的定量数据收集，新开发的无线仪器量化上肢运动，以评估人类功能和机器人活动的要求。该仪器捕获并集成真实的时间运动学、动力学（力和扭矩数据），动觉（本体感受）、肌电数据以及计算机视觉和运动分析数据，特别是整合从触觉设备收集的力数据、从无线电磁传感器收集的6自由度运动数据（“鸟群”）、来自策略性放置的表面电极的肌电数据和从数字化视觉数据收集的运动分析数据。因此，该项目能够。结合现有的仪器，以允许对受试者或机器人进行真实的时间反馈，以纠正运动模式、消除肌肉活动和/或减少力;量化刻板上肢活动，范围从流体，连续指向任务到高扭矩动力抓握活动;将运动模式及其相关的力分解为更简单的组件或基元（在当前触觉研究中提供有用的图形用户界面的方法非常有效）;以及。评估哪些组合对完成各种任务最重要。该仪器还允许探索力反馈的远程控制，以探索其在机器人控制和上肢残疾人辅助技术中使用的可行性，特别是对于恶劣环境中的机器人和偏远地区的人。该仪器还将用于支持运动分析、人机计算机科学、触觉和康复科学方面的现有和新课程。此外，它有助于机构内和与小企业的跨学科合作。基础设施可能会商业化，研究成果可能会通过通常的渠道传播。