CPS:Medium: Towards Neural-controlled Artificial Legs using High-Performance Embedded Computers

CPS：中：使用高性能嵌入式计算机实现神经控制假腿

• 批准号: 0931820
• 负责人: He Huang
• 金额: $ 138.4万
• 依托单位: University of Rhode Island
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0931820&HistoricalAwards=false
• 关键词: CPS; Medium; Towards; Neural; controlled

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).The objective of this research is to develop a trustworthy and high-performance neural-machine interface (NMI) that accurately determines a user?s locomotion mode in real-time for neural-controlled artificial legs. The proposed approach is to design the NMI by integrating a new pattern recognition strategy with a high-performance computing embedded system.This project tackles the challenges of accurate interpretation of information from the neuromuscular system, a physical system, using appropriate computation in a cyber system to process the information in real-time. The neural-machine interface consists of multiple sensors that reliably monitor the neural and mechanical information and a set of new algorithms that can fuse and coordinate the highly dynamic information for accurate identification of user intent. The algorithm is to be implemented on a high-performance graphic processing unit (GPU) to meet real-time requirements.This project has the potential to enable the design of neural-controlled artificial legs and may initiate a new direction for research in and the design of prosthetic leg systems. Innovations in this domain have the potential to improve the quality of life of leg amputees, including soldiers with limb amputations. The proposed approaches seek to permit cyber systems to cope with physical uncertainty and dynamics, a common challenge in cyber-physical systems, and to pave a way for applying high-performance computing in biomedical engineering. Besides providing comprehensive training to undergraduate and graduate students, the investigators plan to introduce community college students to cyber-physical systems concepts in an interactive and engaging manner.

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。这项研究的目标是开发一个值得信赖的和高性能的神经机接口（NMI），准确地确定一个用户？的运动模式的实时神经控制人工腿。 本研究将一种新的模式识别策略与一个高性能的嵌入式系统相结合，设计出一种新的神经肌肉识别系统，该系统通过在网络系统中使用适当的计算来实时处理来自神经肌肉系统（一个物理系统）的信息，从而解决了精确解释信息的挑战。 神经-机器接口由多个传感器组成，这些传感器可以可靠地监测神经和机械信息，以及一套新算法，可以融合和协调高度动态的信息，以准确识别用户意图。 该算法将在一个高性能的图形处理单元（GPU）上实现，以满足实时性的要求。该项目有可能使神经控制的假肢的设计，并可能启动一个新的方向的研究和假肢系统的设计。 这一领域的创新有可能改善腿部截肢者的生活质量，包括截肢士兵的生活质量。 所提出的方法旨在使网络系统，以科普物理的不确定性和动态，在网络物理系统的共同挑战，并铺平了道路，在生物医学工程中应用高性能计算。 除了为本科生和研究生提供全面的培训外，研究人员还计划以互动和参与的方式向社区大学生介绍网络物理系统的概念。