NSF Engineering Research Center for Sensorimotor Neural Engineering

NSF 感觉运动神经工程工程研究中心

基本信息

  • 批准号:
    1028725
  • 负责人:
  • 金额:
    $ 1817.5万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Cooperative Agreement
  • 财政年份:
    2011
  • 资助国家:
    美国
  • 起止时间:
    2011-08-15 至 2021-07-31
  • 项目状态:
    已结题

项目摘要

Over the last decade, the field of neural engineering has demonstrated to the world that a computer cursor, a wheelchair, or a simple prosthetic limb can be controlled using direct brain-machine and brain-computer neural signals. However, technologies that allow such accomplishments do not yet enable versatile and highly complex interactions with sophisticated environments. Today's intelligent systems and robots can neither sense nor move like biological systems, and devices implanted in or interfaced with neural systems cannot process neural data robustly, safely, and in a functionally meaningful way. Doing so requires a critical missing ingredient: a novel, neural-inspired approach based on a deep understanding of how biological systems acquire and process information. This is the focus of this proposal.The NSF ERC for Sensorimotor Neural Engineering (ERC/SNE or "Center") will become a global hub for delivering neural-inspired sensorimotor devices. Using devices that mine the rich data in neural signals available from implantable, wearable, and interactive interfaces, the ERC/SNE will build end-to-end integrated systems. Examples include: implantable neurochips that can activate paralyzed limbs by electrically stimulating muscles or nerve roots; stationary robots that extract neural signals from a user's touch to provide home-based, post-stroke therapy; neural-controlled adaptive prosthetic limbs that provide sophisticated sensory feedback, and wearable caps that control external exploration devices. Unlike traditional approaches that stress accommodation to the needs of people with neurological disabilities, the ERC/SNE will focus on proactive technologies that provide seamless and adaptive person-machine interaction. It will accomplish this mission with three core engineering thrusts: (1) communication and interface design for devices and data management, (2) reverse and forward engineering of neural systems and neural-inspired devices, and (3) control and adaptation technologies that express sensorimotor functions for individual needs.The ERC/SNE will nurture future global multidisciplinary leaders. It will develop middle and high school project-based curricula that introduce neural engineering principles to students underrepresented in engineering. It will create multi-institution, undergraduate and graduate Neural Engineering courses with new degree structures and develop vertical research mentoring chains to build a strong research culture from faculty to K-12. It will build long-lasting and deep relationships through faculty and student exchange programs across all disciplines and partnering institutions, with a goal of removing barriers in communication across different fields, countries, and diverse backgrounds. The neural engineering field creates new pathways from the less quantitatively-based biological sciences to the more quantitatively-based engineering fields as well as pathways for people with disabilities to work in an engineering field that addresses their own experience and needs. The women and underrepresented minorities who currently account for over 40% of the Center's leadership team will serve as role models for students and starting faculty. Further, the ERC/SNE will extend its impact by identifying key technologies according to market significance and technical risk. The Center's portfolio will be constructed to deliver a steady stream of innovations over the near and long term. Its industry partnership structure includes not only small and large firms that will help shape Center IPs, but also hospitals and investment firms that will ground research activities to technologies that will truly assist people in need and steer future neural engineering market directions.The ERC/NSE will strive to enhance the human experience both for persons with neurological disabilities and for the coming generation of global and diverse engineering innovators. The Center's seasoned, multi-disciplinary team will transform healthcare, manufacturing, and the educational infrastructure to guarantee neural engineering global leadership.
在过去的十年中,神经工程领域向世界证明了计算机光标,轮椅或简单的假肢可以使用直接脑机和脑部计算机神经信号来控制。但是,允许此类成就的技术尚未实现与复杂环境的通用和高度复杂的相互作用。当今的智能系统和机器人既无法像生物系统那样感知也不动,并且植入或与神经系统接触的设备不能以有意义的方式进行牢固,安全和功能上的方式处理神经数据。这样做需要一种关键的缺失成分:一种基于对生物系统如何获取和过程信息的深刻了解,一种新型的,神经启发的方法。这是该提案的重点。Sensorimotor神经工程(ERC/SNE或“ Center”)的NSF ERC将成为提供神经启发的感觉运动设备的全球枢纽。使用可植入,可穿戴和交互式接口可用的神经信号中的丰富数据的设备,ERC/SNE将构建端到端集成系统。示例包括:可植入的神经化学,可以通过电刺激肌肉或神经根来激活瘫痪的肢体;从用户的触摸中提取神经信号的固定机器人,以提供基于家庭的震后治疗;神经控制的自适应假肢四肢,可提供复杂的感觉反馈,以及控制外部勘探装置的可穿戴帽。与对神经残疾人的需求强调需求的传统方法不同,ERC/SNE将专注于提供无缝且适应性的人际关系相互作用的主动技术。它将通过三个核心工程推力来完成这项任务:(1)用于设备和数据管理的通信和接口设计,(2)神经系统和神经启发的设备的反向和前向工程,以及(3)为个人需求表达感官函数的控制和适应技术。它将开发中学和高中项目的课程,该课程向工程领域不足的学生介绍神经工程原则。它将创建具有新学位结构的多机构,本科和研究生神经工程课程,并开发垂直研究指导链,以建立从教师到K-12的强大研究文化。它将通过所有学科和合作机构的教师和学生交流计划建立持久而深厚的关系,目的是消除不同领域,国家和不同背景的沟通障碍。神经工程领域创造了新的途径,从较少基于定量的生物学科学到基于数量的工程领域,以及为残疾人在工程领域工作的途径,以解决自己的经验和需求。目前占该中心领导力团队40%以上的妇女和代表性不足的少数民族将成为学生的榜样并创立教职员工。此外,ERC/SNE将通过根据市场意义和技术风险确定关键技术来扩展其影响。该中心的投资组合将被构建,以在近期和长期内提供稳定的创新。它的行业合作伙伴关系结构不仅包括将有助于塑造中心IP的小型和大型公司,而且还包括将研究活动奠定的医院和投资公司,这些研究活动将真正帮助有需要的人,并指导未来的神经工程市场方向。ERC/NSE将努力增强与神经障碍的人的人类体验,以使神经系统障碍以及即将到来的全球和多样性的发动机创新的创新者。该中心经验丰富的多学科团队将改变医疗保健,制造业和教育基础设施,以确保神经工程的全球领导能力。

项目成果

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Rajesh Rao其他文献

Amorphous/crystalline silicon heterojunction solar cells via Remote plasma chemical vapor deposition: Influence of hydrogen dilution, RF power, and sample Z-height position
通过远程等离子体化学气相沉积的非晶/晶体硅异质结太阳能电池:氢气稀释、射频功率和样品 Z 高度位置的影响
Surgery: Is There a Difference Between Men and Women? Postoperative Complications Following Orthopedic Spine
手术:男性和女性之间有区别吗?
  • DOI:
  • 发表时间:
    2019
  • 期刊:
  • 影响因子:
    0
  • 作者:
    J. Heyer;Na Cao;R. Amdur;Rajesh Rao
  • 通讯作者:
    Rajesh Rao
Mo1504: IN SILICO EVALUATION AND PRE-CLINICAL EFFICACY OF ANTI-TNF AND ANTI-IL-23 COMBINATION THERAPY IN INFLAMMATORY BOWEL DISEASE
  • DOI:
    10.1016/s0016-5085(22)61876-6
  • 发表时间:
    2022-05-01
  • 期刊:
  • 影响因子:
  • 作者:
    Jacqueline Perrigoue;Luciana R. Muniz-Bongers;Luvena L. Ong;Yanqing Chen;Leon Chang;Karen Ngo;Aleksandar Stojmirovic;Christopher D. O’Brien;Matthew Germinaro;Rajesh Rao;Marion Vetter;Jennifer Towne
  • 通讯作者:
    Jennifer Towne
Gómez-López-Hernández syndrome: a case report on pediatric neurotrophic corneal ulcers and review of the literature
  • DOI:
    10.1016/j.jaapos.2021.08.299
  • 发表时间:
    2021-12-01
  • 期刊:
  • 影响因子:
  • 作者:
    Jonathan Chao;Rajesh Rao;Chirag Gupta
  • 通讯作者:
    Chirag Gupta

Rajesh Rao的其他文献

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{{ truncateString('Rajesh Rao', 18)}}的其他基金

RI: Small: Probabilistic Goal-Based Imitation Learning
RI:小:基于概率目标的模仿学习
  • 批准号:
    1318733
  • 财政年份:
    2013
  • 资助金额:
    $ 1817.5万
  • 项目类别:
    Standard Grant
Electrocorticographic Brain-Machine Interfaces for Communication and Prosthetic Control
用于通信和假肢控制的皮质电脑机接口
  • 批准号:
    0930908
  • 财政年份:
    2009
  • 资助金额:
    $ 1817.5万
  • 项目类别:
    Standard Grant
Exploring the Neural Dynamics of Cognition through Human Electrocorticography
通过人体皮层电图探索认知的神经动力学
  • 批准号:
    0642848
  • 财政年份:
    2007
  • 资助金额:
    $ 1817.5万
  • 项目类别:
    Continuing Grant
BIC: Probabilistic Neural Computation: Models and Applications in Robotics and Brain-Machine Interfaces
BIC:概率神经计算:机器人和脑机接口中的模型和应用
  • 批准号:
    0622252
  • 财政年份:
    2006
  • 资助金额:
    $ 1817.5万
  • 项目类别:
    Continuing Grant
Probabilistic Imitation Learning in Infants and Robots
婴儿和机器人的概率模仿学习
  • 批准号:
    0413335
  • 财政年份:
    2004
  • 资助金额:
    $ 1817.5万
  • 项目类别:
    Standard Grant
CAREER: Neurally Inspired Active Vision: Theory, Models, and Applications in Mobile Robotics
职业:神经启发主动视觉:移动机器人的理论、模型和应用
  • 批准号:
    0133592
  • 财政年份:
    2002
  • 资助金额:
    $ 1817.5万
  • 项目类别:
    Continuing Grant
Adaptive Neurally-Inspired Computing: Models, Algorithms, and Silicon-Based Architectures
自适应神经启发计算:模型、算法和基于硅的架构
  • 批准号:
    0130705
  • 财政年份:
    2001
  • 资助金额:
    $ 1817.5万
  • 项目类别:
    Standard Grant

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