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IRES Track I: International Research Experience for Students on Assistive Technology for Aging and Disability

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
批准号:
2106996
负责人:
Wenyao Xu
金额:
$30.0万
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
项目状态:
已结题
起止时间:
2021-10-01 至 2024-09-30

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项目成果

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中文摘要
翻译
这个IRES项目将促进美国学生在可穿戴计算、机器人、机器学习和医学科学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。训练学生学习机器学习、可穿戴传感器和辅助技术的数据处理是独特的,需要一个综合的方法。IRES参与者将沉浸在产生和理解人类信号分析,并创建算法和软件,以帮助老年人和残疾人用户。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)的研究人员参与辅助技术研究。将建立项目和研讨会,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。每周在国际现场的报告和国际导师的指导将丰富队列研究经验。将学生纳入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。学生们将在利兹大学IRASS度过十个暑期周,以提高他们的研究技能,提升他们的文化能力。这项国际研究努力将激励学生创新并在全球传播成果。该IRES合作项目将通过智能硬件和机器学习方法的联合开发产生重要的研究进展,以解决传感器,人机交互,机器学习,医疗保健信息学,认知建模和下一代辅助医疗系统可用性研究的重大挑战。布法罗大学和利兹大学之间的这个合作IRES项目将让学生参与到迫切需要解决的辅助技术的基本问题中,包括1)节能的可穿戴计算架构;2)心理健康认知机器人;3)可解释的医疗保健人工智能模型。从这项研究中获得的经验和教训将有利于医疗保健和医学应用的先进辅助技术的发展,并有望促进参与研究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,并最终为快速发展的老年人和残疾人辅助技术领域的年轻科学家和工程师做出贡献。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
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.
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