IRES Track I: International Research Experience for Students on Assistive Technology for Aging and Disability
IRES 轨道 I:老龄化和残疾辅助技术学生的国际研究经验
基本信息
- 批准号:2106996
- 负责人:
- 金额:$ 30万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-10-01 至 2024-09-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This IRES project will promote international multidisciplinary research opportunities for U.S. students at the overlap of wearable computing, robotics, machine learning and medical science with the aim of advancing assistive technologies. Assistive technologies can help overcome impairments, cognitive difficulties, and disabilities in the senior and disabled populations. Training students in machine learning, wearable sensors, and data processing for assistive technologies is unique and requires an integrative approach. IRES participants will be immersed in producing and understanding human signal analytics and creating algorithms and software to assist aging and disability users. The IRES program will engage faculty researchers from the University at Buffalo and from the University of Leeds the Institute for Robotics, Autonomous Systems and Sensing (IRASS) in assistive technology research. Programs and workshops will be established so that IRES participants are trained in machine learning for assistive systems and present their research results in international settings. Weekly presentations at the international site and guidance by international mentors will enrich the cohort research experience. Embedding students in the IRASS research labs funded by large United Kingdom (UK) projects will provide knowledge on UK and international research practices, healthcare standards, and policies. Students will spend ten summer weeks at the University of Leeds IRASS to improve their research skills and elevate their cultural competencies. This international research endeavor will energize students to innovate and disseminate results globally. This IRES collaborative project will produce important research advances through joint development of intelligent hardware and machine learning methodologies to address the grand challenges of sensors, human-robot interaction, machine learning, healthcare informatics, cognitive modeling, and usability study of next-generation assistive healthcare systems. This collaborative IRES project between the University at Buffalo and the University of Leeds will engage students in targeting fundamental issues in assistive technologies that need to be addressed urgently, including 1) energy-efficient wearable computing architectures; 2) cognitive robotics for mental health; 3) explainable artificial intelligence models for healthcare. The experience and lessons learned through this research can benefit the development of advanced assistive technologies for healthcare and medicine applications and is expected to enhance the professional development of participating U.S. students. Through the success of the student training, mentoring, and research activities, this IRES project will strengthen existing computer engineering research and education programs, and eventually contribute to preparing young scientists and engineers in the fast-growing area of assistive technology for the aging and disabled populations.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
该 IRES 项目将为美国学生提供可穿戴计算、机器人、机器学习和医学交叉领域的国际多学科研究机会,旨在推进辅助技术。辅助技术可以帮助老年人和残疾人克服障碍、认知困难和残疾。对学生进行机器学习、可穿戴传感器和辅助技术数据处理方面的培训是独特的,需要采用综合方法。 IRES 参与者将致力于生成和理解人类信号分析,并创建算法和软件来帮助老年人和残疾用户。 IRES 项目将邀请布法罗大学和利兹大学机器人、自主系统和传感研究所 (IRASS) 的教员研究人员参与辅助技术研究。将设立项目和研讨会,以便 IRES 参与者接受辅助系统机器学习方面的培训,并在国际环境中展示他们的研究成果。每周在国际现场的演讲和国际导师的指导将丰富队列研究经验。让学生参与由英国大型项目资助的 IRASS 研究实验室,将提供有关英国和国际研究实践、医疗保健标准和政策的知识。学生将在利兹大学 IRASS 度过十个夏季周,以提高他们的研究技能并提高他们的文化能力。这项国际研究工作将激励学生创新并在全球范围内传播成果。该 IRES 合作项目将通过联合开发智能硬件和机器学习方法来取得重要的研究进展,以解决传感器、人机交互、机器学习、医疗信息学、认知建模和下一代辅助医疗系统可用性研究的巨大挑战。布法罗大学和利兹大学之间的这个合作 IRES 项目将让学生致力于解决辅助技术中急需解决的基本问题,包括 1) 节能的可穿戴计算架构; 2)用于心理健康的认知机器人; 3)可解释的医疗保健人工智能模型。通过这项研究获得的经验和教训可以有利于医疗保健和医学应用的先进辅助技术的开发,并有望促进参与的美国学生的专业发展。通过学生培训、指导和研究活动的成功,该 IRES 项目将加强现有的计算机工程研究和教育计划,并最终有助于在快速增长的老龄化和残疾人辅助技术领域培养年轻科学家和工程师。该奖项反映了 NSF 的法定使命,并通过使用基金会的智力价值和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Wenyao Xu其他文献
Information Reuse to Accelerate Customized Product Slicing for Additive Manufacturing
信息重用加速增材制造的定制产品切片
- DOI:
- 发表时间:
2018 - 期刊:
- 影响因子:0
- 作者:
Hang Ye;Tsz;Chi Zhou;Wenyao Xu - 通讯作者:
Wenyao Xu
Exploiting Mallows Distance to Quantify EEG Distribution for Personal Identification
利用锦葵距离量化脑电图分布以进行个人识别
- DOI:
- 发表时间:
2019 - 期刊:
- 影响因子:0
- 作者:
Baicheng Chen;Kun Woo Cho;Chenhan Xu;Feng Lin;Zhanpeng Jin;Wenyao Xu - 通讯作者:
Wenyao Xu
Anomalous Pattern Recognition in Vital Health Signals via Multimodal Fusion
通过多模态融合识别重要健康信号中的异常模式
- DOI:
10.1007/978-3-030-95593-9_12 - 发表时间:
2021 - 期刊:
- 影响因子:0
- 作者:
Soumyadeep Bhattacharjee;Huining Li;Wenyao Xu - 通讯作者:
Wenyao Xu
Analyzing dynamic components of social scene parsing strategy in autism spectrum disorder
分析自闭症谱系障碍社交场景解析策略的动态组成部分
- DOI:
10.1109/bhi.2016.7455852 - 发表时间:
2016 - 期刊:
- 影响因子:0
- 作者:
Chen Song;Aosen Wang;K. Doody;Michelle Hartley;Jana Mertz;Feng Lin;Wenyao Xu - 通讯作者:
Wenyao Xu
PDLens: smartphone knows drug effectiveness among Parkinson's via daily-life activity fusion
PDLens:智能手机通过日常生活活动融合了解帕金森病的药物有效性
- DOI:
10.1145/3372224.3380889 - 发表时间:
2020 - 期刊:
- 影响因子:0
- 作者:
Hanbin Zhang;Gabriel Guo;Chen Song;Chenhan Xu;K. Cheung;Jasleen Alexis;Huining Li;Dongmei Li;Kun Wang;Wenyao Xu - 通讯作者:
Wenyao Xu
Wenyao Xu的其他文献
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{{ truncateString('Wenyao Xu', 18)}}的其他基金
CyberTraining: Implementation: Small: Infrastructure Cybersecurity Curriculum Development and Training for Advanced Manufacturing Research Workforce
网络培训:实施:小型:基础设施网络安全课程开发和先进制造研究人员培训
- 批准号:
2230025 - 财政年份:2023
- 资助金额:
$ 30万 - 项目类别:
Standard Grant
REU Site: Frontier Technologies for Biometrics and Authentication
REU 网站:生物识别和身份验证前沿技术
- 批准号:
2050910 - 财政年份:2021
- 资助金额:
$ 30万 - 项目类别:
Standard Grant
EAGER: SARE: Collaborative Research: Exploring and Mitigating Attacks of Millimeter-wave Radar Sensors in Autonomous Vehicles
EAGER:SARE:协作研究:探索和减轻自动驾驶汽车中毫米波雷达传感器的攻击
- 批准号:
2028872 - 财政年份:2020
- 资助金额:
$ 30万 - 项目类别:
Standard Grant
SaTC: CORE: Small: Collaborative: Cardiac Password: Exploring a Non-Contact and Continuous Approach to Secure User Authentication
SaTC:核心:小型:协作:心脏密码:探索非接触式和连续的安全用户身份验证方法
- 批准号:
1718375 - 财政年份:2017
- 资助金额:
$ 30万 - 项目类别:
Standard Grant
TWC SBE: Medium: Collaborative: Brain Hacking: Assessing Psychological and Computational Vulnerabilities in Brain-based Biometrics
TWC SBE:媒介:协作:大脑黑客:评估基于大脑的生物识别技术中的心理和计算漏洞
- 批准号:
1564104 - 财政年份:2016
- 资助金额:
$ 30万 - 项目类别:
Continuing Grant
EAGER: Cybermanufacturing: Software/Hardware Combined Acceleration for 3D Printing in Mass Customization
EAGER:网络制造:大规模定制中 3D 打印的软件/硬件组合加速
- 批准号:
1547167 - 财政年份:2015
- 资助金额:
$ 30万 - 项目类别:
Standard Grant
EAGER-DynamicData: Collaborative: Exploiting the Dynamically Architectural Configurability for Compressed Sensing
EAGER-DynamicData:协作:利用压缩感知的动态架构可配置性
- 批准号:
1462498 - 财政年份:2015
- 资助金额:
$ 30万 - 项目类别:
Standard Grant
TWC SBE: Small: Collaborative: Brain Password: Exploring A Psychophysiological Approach for Secure User Authentication
TWC SBE:小型:协作:大脑密码:探索安全用户身份验证的心理生理学方法
- 批准号:
1423061 - 财政年份:2014
- 资助金额:
$ 30万 - 项目类别:
Standard Grant
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