I/UCRC for Building Reliable Advances and Innovation in Neurotechnology (BRAIN)
I/UCRC 致力于神经技术 (BRAIN) 领域的可靠进步和创新
基本信息
- 批准号:1650566
- 负责人:
- 金额:$ 75万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2017
- 资助国家:美国
- 起止时间:2017-03-15 至 2022-06-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Age-related diseases are increasingly a leading cause of disability. Millions of younger adults live with neurological disorders, limb loss from amputation or paralysis from spinal cord injury. Traumatic brain injury can have lifelong effects on cognitive-motor function, significantly decreasing quality and length of life. There is a critical need for state-of-the art technology to effectively address the care and rehabilitation of these individuals. However, innovation in biomedical devices and other neurotechnologies faces several challenges: 1) The pace of innovation is moving more quickly than the rate of evaluation for acceptable performance; 2) Standards and regulatory science for the rigorous validation of safety, efficacy, and long-term reliability are missing; 3) Lack of open access to technologies that slows the transfer of novel technologies to the market; and 4) Current technologies are not affordable. To address these challenges, Arizona State University will partner with University of Houston to establish and host a multi-institution Industry/University Cooperative Research Center (I/UCRC) for Building Reliable Advances and Innovation in Neurotechnology (BRAIN). The BRAIN Center's vision is a synergistic, interdisciplinary approach to develop and validate affordable patient-centered technologies. BRAIN will leverage expertise in neural systems, cognitive and rehabilitation engineering, robotics, clinical testing, and reverse-translational research at the University of Houston and Arizona State University to 1) enhance the rate of development and empirical validation of new technologies through partnerships with industry leaders and other strategic partners; 2) develop standards and technologies in human and non-human models, using a multi-scale approach ranging from single neurons to organismal systems; 3) characterize innovative technologies such as biosensors and quantitative analysis tools for systems and behaviors; 4) evaluate the impact of these technologies on quality of life; and 5) reduce the cost of neurotechnologies. The BRAIN Center's mission is multifold: to accelerate the progress of science and advance national health by transferring engineering innovations in neurotechnology to the end users, and to rectify underrepresentation in science, technology, engineering, and math (STEM) fields by broadening new participation and retaining current participants in STEM. It also will focus on problems in the neurological space that affect underrepresented groups disproportionately. BRAIN will become an innovative neurotechnology hub for the Southwest, creating a pipeline from discoveries to solutions while helping talented students, scientists, and engineers in the region take their innovations to the next level and solve one of the greatest unmet medical and health care needs of our time.BRAIN will leverage a unique concentration of researchers and innovative research and development ecosystems with industrial partnerships to design, develop, test, and characterize neural technologies that can effectively transform the lives of disabled individuals. The Center will investigate all levels of neural function to enhance not only current technologies but also understanding of the mechanisms underlying neurological disease and injury. The Arizona State University IUCRC Site will focus on multi-scale, multi-modal, and multi-disciplinary and noninvasive approaches to understanding human neural function, and to deploying noninvasive technologies treating human disability. The Arizona State University site will bring a broad range of expertise spanning invasive and non-invasive neurotechnology and rehabilitation engineering to improve neural function across the human lifespan, as well as intervention techniques including peripheral, brain-machine interfaces, neuroprostheses, neuromodulation, data analytics, wearable assistive devices, and rehabilitation robotics. The Arizona State University innovation ecosystem includes a strong culture of entrepreneurship, use-inspired research, and interdisciplinary collaborations among faculty, industry, and clinical partners.
与年龄有关的疾病日益成为致残的主要原因。数以百万计的年轻人患有神经系统疾病、截肢导致的肢体丧失或脊髓损伤导致的瘫痪。创伤性脑损伤可对认知运动功能产生终身影响,显著降低生活质量和寿命。迫切需要最先进的技术来有效地处理这些人的护理和康复问题。然而,生物医学设备和其他神经技术的创新面临着几个挑战:1)创新的步伐比可接受性能的评估速度快得多;2)缺乏安全性、有效性和长期可靠性严格验证的标准和监管科学;3)缺乏对技术的开放获取,减缓了新技术向市场的转移;4)目前的技术是负担不起的。为了应对这些挑战,亚利桑那州立大学将与休斯顿大学合作,建立并主办一个多机构的工业/大学合作研究中心(I/UCRC),以建立可靠的神经技术进步和创新(BRAIN)。脑中心的愿景是一个协同的,跨学科的方法来开发和验证负担得起的以患者为中心的技术。BRAIN将利用休斯顿大学和亚利桑那州立大学在神经系统、认知和康复工程、机器人技术、临床测试和逆向转化研究方面的专业知识,1)通过与行业领导者和其他战略合作伙伴的合作,提高新技术的开发速度和经验验证;2)利用从单个神经元到组织系统的多尺度方法,开发人类和非人类模型的标准和技术;3)描述创新技术,如生物传感器和系统和行为的定量分析工具;4)评估这些技术对生活质量的影响;5)降低神经技术的成本。大脑中心的使命是多重的:通过将神经技术的工程创新转移给最终用户来加速科学的进步和促进国民健康,并通过扩大新的参与和保留现有的STEM参与者来纠正科学、技术、工程和数学(STEM)领域的代表性不足。它还将关注神经学领域的问题,这些问题不成比例地影响着未被充分代表的群体。BRAIN将成为西南地区创新的神经技术中心,创建从发现到解决方案的管道,同时帮助该地区有才华的学生、科学家和工程师将他们的创新提升到一个新的水平,解决我们这个时代最大的未满足的医疗和卫生保健需求之一。BRAIN将利用独特的研究人员和创新的研发生态系统,与工业合作伙伴一起设计、开发、测试和表征能够有效改变残疾人生活的神经技术。该中心将研究神经功能的各个层面,不仅提高现有技术,而且提高对神经系统疾病和损伤机制的理解。亚利桑那州立大学IUCRC网站将专注于多尺度、多模式、多学科和非侵入性方法,以了解人类神经功能,并部署非侵入性技术治疗人类残疾。亚利桑那州立大学的站点将带来广泛的专业知识,包括侵入性和非侵入性神经技术和康复工程,以改善人类生命周期中的神经功能,以及干预技术,包括外围设备、脑机接口、神经假肢、神经调节、数据分析、可穿戴辅助设备和康复机器人。亚利桑那州立大学的创新生态系统包括强大的创业文化、使用启发式研究以及教师、行业和临床合作伙伴之间的跨学科合作。
项目成果
期刊论文数量(23)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Length of Time-Series Gait Data on Lyapunov Exponent for Fall Risk Detection
用于跌倒风险检测的李亚普诺夫指数的时间序列步态数据的长度
- DOI:
- 发表时间:2021
- 期刊:
- 影响因子:2.1
- 作者:Hussain, V.S;Frames, C.W.;and Lockhart, T.E.
- 通讯作者:and Lockhart, T.E.
Integrated Sensing System for Monitoring Interrelated Physiological Parameters in Young and Aged Adults: A Pilot Study.
用于监测年轻人和老年人相关生理参数的集成传感系统:一项试点研究。
- DOI:10.36001/ijphm.2021.v12i4.2914
- 发表时间:2021
- 期刊:
- 影响因子:2.1
- 作者:Sprowls, M.;Serhan, M.;Chou, E.F.;Lin, L.;Frames, C.;Kucherenko, I.;Mollaeian, K.;Jammula, V.;Logeswaran, D.;Khine, M.
- 通讯作者:Khine, M.
MON-P301: Relationship between Serum 25-Hydroxyvitamin D Levels and Fall Risk as Measured by Dynamic Stability and Mobility-Related Outcomes in Older Adults
MON-P301:通过老年人的动态稳定性和行动相关结果来衡量血清 25-羟基维生素 D 水平与跌倒风险之间的关系
- DOI:10.1016/s0261-5614(17)30788-4
- 发表时间:2017
- 期刊:
- 影响因子:6.3
- 作者:Lockhart, T.;Garvey, S.;Kelly, O.
- 通讯作者:Kelly, O.
PREDICTION OF THE SPATIO-TEMPORAL GAIT PARAMETERS USING INERTIAL SENSOR
利用惯性传感器预测时空步态参数
- DOI:10.1142/s021951941840002x
- 发表时间:2018
- 期刊:
- 影响因子:0.8
- 作者:LIU, JIAN;LOCKHART, THURMON;KIM, SUKWON
- 通讯作者:KIM, SUKWON
Falls When Standing, Falls When Walking: Different Mechanisms, Different Outcomes in Parkinson Disease
- DOI:10.7759/cureus.5329
- 发表时间:2019-08-06
- 期刊:
- 影响因子:1.2
- 作者:Lieberman, Abraham;Deep, Aman;Lockhart, Thurmon E.
- 通讯作者:Lockhart, Thurmon E.
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Marco Santello其他文献
Deep Learning Detection of Hand Motion During Microvascular Anastomosis Simulations Performed by Expert Cerebrovascular Neurosurgeons
- DOI:
10.1016/j.wneu.2024.09.069 - 发表时间:
2024-12-01 - 期刊:
- 影响因子:
- 作者:
Thomas J. On;Yuan Xu;Jiuxu Chen;Nicolas I. Gonzalez-Romo;Oscar Alcantar-Garibay;Jay Bhanushali;Wonhyoung Park;John E. Wanebo;Andrew W. Grande;Rokuya Tanikawa;Dilantha B. Ellegala;Baoxin Li;Marco Santello;Michael T. Lawton;Mark C. Preul - 通讯作者:
Mark C. Preul
Behavioral evidence for motor learning and transfer without visual feedback
无视觉反馈的运动学习和迁移的行为证据
- DOI:
- 发表时间:
2015 - 期刊:
- 影响因子:0
- 作者:
Ryuta Kitani;Jiajia Yang;Yinghua Yu;Akinori Kunita;Satoshi Takahashi;Jinlong Wu;Qiushi Fu;Marco Santello - 通讯作者:
Marco Santello
Extending kinematic decoding approaches to kinetics
将运动学解码方法扩展到动力学
- DOI:
10.1016/j.plrev.2025.03.007 - 发表时间:
2025-07-01 - 期刊:
- 影响因子:14.300
- 作者:
Marco Santello - 通讯作者:
Marco Santello
‘I Said I’m Young You Know I Can Plan Something Good You Know’: Understanding Language and Migration Through Time
“我说我还年轻,你知道我可以计划一些好事情,你知道”:随着时间的推移理解语言和迁徙
- DOI:
10.1093/applin/amae031 - 发表时间:
2024 - 期刊:
- 影响因子:3.6
- 作者:
Marco Santello - 通讯作者:
Marco Santello
Neuroimaging evidence for tactile object recognition
触觉物体识别的神经影像证据
- DOI:
- 发表时间:
2015 - 期刊:
- 影响因子:0
- 作者:
Ryuta Kitani;Jiajia Yang;Yinghua Yu;Akinori Kunita;Satoshi Takahashi;Jinlong Wu;Qiushi Fu;Marco Santello;Jiajia Yang - 通讯作者:
Jiajia Yang
Marco Santello的其他文献
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{{ truncateString('Marco Santello', 18)}}的其他基金
IUCRC Phase II ASU: Building Reliable Advances and Innovations in Neurotechnology (BRAIN)
IUCRC 第二阶段 ASU:在神经技术 (BRAIN) 领域建立可靠的进步和创新
- 批准号:
2137272 - 财政年份:2022
- 资助金额:
$ 75万 - 项目类别:
Continuing Grant
Collaborative Research: Effector and Task Neural Representations of Hand-Object Interactions
协作研究:手-物体交互的效应器和任务神经表征
- 批准号:
1827752 - 财政年份:2018
- 资助金额:
$ 75万 - 项目类别:
Standard Grant
Collaborative Research: Sensorimotor control of hand-object interactions
合作研究:手与物体交互的感觉运动控制
- 批准号:
1455866 - 财政年份:2015
- 资助金额:
$ 75万 - 项目类别:
Standard Grant
Planning Grant: Collaborative Research: I/UCRC for Building Reliable Advances and Innovation in Neurotechnology (BRAIN)
规划资助:合作研究:I/UCRC 建立神经技术的可靠进步和创新 (BRAIN)
- 批准号:
1539979 - 财政年份:2015
- 资助金额:
$ 75万 - 项目类别:
Standard Grant
Collaborative Research: Sensory Integration and Sensorimotor Transformations for Dexterous Manipulation
合作研究:灵巧操作的感觉统合和感觉运动转化
- 批准号:
1153034 - 财政年份:2012
- 资助金额:
$ 75万 - 项目类别:
Continuing Grant
RI: Medium: Collaborative Research: Robotic Hands: Understanding and Implementing Adaptive Grasping
RI:媒介:协作研究:机器人手:理解和实施自适应抓取
- 批准号:
0904504 - 财政年份:2009
- 资助金额:
$ 75万 - 项目类别:
Standard Grant
Collaborative Research: Dextrous Control of Multi-Digit Grasping
协作研究:多手指抓取的灵巧控制
- 批准号:
0819547 - 财政年份:2008
- 资助金额:
$ 75万 - 项目类别:
Standard Grant
Collaborative Research: Coordination of Multi-Digit Forces During Grasping
协作研究:抓取过程中多手指力量的协调
- 批准号:
0519152 - 财政年份:2006
- 资助金额:
$ 75万 - 项目类别:
Continuing Grant
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