STTR Phase I: Camera-Based Multimodal AI for Health Monitoring

STTR 第一阶段：基于摄像头的多模态人工智能，用于健康监测

• 批准号: 2136728
• 负责人: Mona Azarbayjani
• 金额: $ 25.6万
• 依托单位: FORESIGHTCARES INC.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-03-15 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2136728&HistoricalAwards=false
• 关键词: STTR; Phase; Camera; Based; Multimodal

The broader impact of this Small Business Technology Transfer (STTR) Phase I project will be to mitigate healthcare costs and challenges associated with the nation's growing aging population. The outcome of this project will be a system that enables holistic, accurate, and faster monitoring of elderly people that will 1) improve quality of life and health of senior citizens, 2) address the future nursing shortage, particularly in the geriatric field, and 3) reduce healthcare costs. The proposed technology can impact a wide range of public health applications that require continuous, non-intrusive health monitoring.This Small Business Technology Transfer (STTR) Phase I project applies real-time computer vision and sensor fusion processing for real-time continuous monitoring and analysis of health-related activities. In addition, this project takes an essential step beyond current solutions by analyzing seniors' group behavior and interactions with objects to determine whether they suffer from loneliness, behavioral disorders, or confusion states. This project utilizes multiple artificial intelligence algorithms to maximize the discriminative power to understand human micro-body motions and thereby create a training framework for personalized behavioral understanding and monitoring. It also proposes an innovative solution to leverage the results of computer vision as attention feedback to thermal sensors to enhance the accuracy and robustness of thermal processing against temperature variations. Furthermore, the project offers an integrative edge-based Internet of Things solution to protect citizens' privacy while providing real-time continuous feedback to responsible personnel. The proposed system offers a novel user experience while protecting personally identifiable information.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.

该小企业技术转让 (STTR) 第一阶段项目的更广泛影响将是减轻医疗保健成本和与国家不断增长的人口老龄化相关的挑战。该项目的成果将是建立一个能够全面、准确和更快地监测老年人的系统，该系统将 1) 改善老年人的生活质量和健康，2) 解决未来的护理短缺问题，特别是在老年领域，以及3）降低医疗费用。所提出的技术可以影响需要连续、非侵入式健康监测的广泛公共卫生应用。这个小型企业技术转让（STTR）第一阶段项目应用实时计算机视觉和传感器融合处理来进行实时连续监测和分析与健康相关的活动。此外，该项目在当前解决方案的基础上迈出了重要一步，通过分析老年人的群体行为和与物体的互动来确定他们是否患有孤独、行为障碍或困惑状态。该项目利用多种人工智能算法，最大限度地提高理解人体微体运动的判别能力，从而创建个性化行为理解和监控的训练框架。它还提出了一种创新的解决方案，利用计算机视觉的结果作为对热传感器的注意力反馈，以提高热处理针对温度变化的准确性和鲁棒性。此外，该项目还提供基于边缘的综合物联网解决方案，以保护公民的隐私，同时向负责人员提供实时持续反馈。拟议的系统提供了新颖的用户体验，同时保护个人身份信息。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。