2025年10月初，约翰斯·霍普金斯大学人工智能与技术老龄化研究合作实验室（JH AITC）宣布了第五轮资助的获得者。该项目启动于2021年，由美国国家老龄化研究所（NIA）资助2000万美元成立。这一轮项目资助金额略高于150万美元，通过资助AI（人工智能技术）的发展来支持合作伙伴的使命，以改善数百万美国老年人及其护理人员的健康和生活质量。本轮项目申请，通过竞争性的国家拨款审查程序，从109个申请中选出了来自学术界、工业界和临床实践的9个项目。每位获奖者将在一年内获得高达20万美元的直接费用，并获得霍普金斯大学计算机科学、护理、医学和技术商业化等领域专家的资源和指导。
通过报道，可以注意到当今美国顶尖高校科研的特点就是聚焦AI（人工智能技术）的应用。这里的应用主要是指“商业化”（commercialization）。这与我本人这些年来开展的专利商业化研究存在相同之处。随着技术发展和社会需求的变化，越来越多的AI技术与技术商业化过程联系在一起。这是美国霍普金斯大学JH AITC公布第五轮项目给人的最大启迪。
此外，还可以注意到项目研究的开放性。美国顶尖高校科研项目组，其成员构成是由导师与博士生、硕士生和本科生构成的群体。这也是与我们国家大学的一个显著区别。美国大学强调的创新教育和科研训练，离不开实验室开放性的支持。本科生进入大学后，可以申请进入他们感兴趣的实验室。这就从人才角度保证了项目组的活力、项目研究的持续性和创新性。
详细的相关报道如下：
The Johns Hopkins Artificial Intelligence and Technology Collaboratory for Aging Research, or JH AITC, has announced the recipients of its fifth round of grant funding. Totaling just over $1.5 million, this round supports the collaboratory’s mission by funding the development of artificial intelligence technologies to improve the health and quality of life of millions of older Americans and their caregivers.
Nine projects from academia, industry, and clinical practice were selected out of 109 applications through a competitive national grant review process. Each awardee will receive up to $200,000 in direct costs over a one-year period, as well as access to resources and mentorship from Hopkins experts in fields such as computer science, nursing, medicine, and technology commercialization.
Launched in 2021 with a $20 million grant from the National Institute on Aging, the JH AITC is a national hub for innovation in healthy aging and cross-disciplinary collaboration within the Johns Hopkins community and beyond.
This round, the JH AITC has invested in research that leverages AI to support healthy aging and mitigate the effects of dementia.
Anis Davoudi, an assistant scientist in the Department of Epidemiology at the Bloomberg School of Public Health and a member of the Johns Hopkins Center on Aging and Health, aims to develop an AI-driven screening tool that uses eye tracking and speech analysis to identify digital biomarkers in older adults that indicate mild cognitive impairment.“The findings of this pilot study will be used to create a non-invasive and accessible assessment method that can be used in clinical and community settings to facilitate early intervention and support healthy cognitive aging,” says Davoudi.
Another Hopkins-led pilot will provide clinical validation of an AI-driven gait-monitoring device equipped with actionable gait insights, designed to help prevent older patients and care providers more efficiently track rehabilitation progress and enhance mobility health.
“Our Re-Kinesis technology, enabled by AI analytics, aims to discover gait conditions that lead to gait disorders and potential falls in the aging population,” says Nitish V. Thakor, a professor of biomedical engineering, electrical and computer engineering, and neurology, who is the principal investigator of the project. “We aim to apply this AI-enabled technology to develop solutions for gait and fall conditions.”
“Using a high-density pressure sensor array and AI-driven sampling, we can obtain a very high-resolution ‘pressure video’ of the distribution under the feet, which we feed into another AI model that predicts body movement,” explains project team member Arik Slepyan, a PhD student of electrical and computer engineering. “We have miniaturized our electronics into a battery-powered wearable so that people can use our gait monitor at home or on the go.”
“Our AI model can predict the angles of the hips, knees, and ankles from the plantar pressure distribution by identifying the most probable joint positions,” adds Samuel Bello, a PhD student of biomedical engineering working on the project. “This allows us to accurately measure a person’s gait without the need for cumbersome cameras or inertial measurement units.”
“The question we wanted to answer was, ‘How do we make rehabilitation accessible to more people?’” adds Junjun Chen, Engr ’22 (BS/MSE), the co-founder of the Re-Kinesis project concept. “Our solution was to leverage our collective sensing and AI expertise to create a wearable gait analysis lab. Older adults can wear it unobtrusively at home to get lab-grade gait monitoring, while physicians and therapists can remotely access the data to provide better rehabilitation and, most importantly, promote healthy aging.”
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