SCC-PG: Getting the Edge on Data-Driven Self-Managed Care: A Focus on Older Veterans in Arizona

老年人努力保持独立和健康，但与年轻人相比，他们患慢性疾病和社会孤立的风险更大。需要解决方案，为老年人创造茁壮成长，联系，贡献和塑造他们的社区的方式。物联网（IoT）的日益普及，特别是可穿戴设备和智能家居设备（例如，智能手表、语音激活的家庭助理）为自我护理管理的实时干预提供了重要机会，特别是如果它们是定制的，以满足每个人的独特需求和目标。这个规划项目的重点是亚利桑那州凤凰城的老年退伍军人。该项目正在建立一个多学科团队，以形成一个研究议程，用于研究，开发和部署基于物联网的解决方案，以提供高质量，低成本和社区感知的自我管理护理。该项目还为来自多个学科的各级学生提供教育和劳动力发展，特别是为项目所在地亚利桑那州立大学的许多代表性不足的学生创造创新和机会。通过焦点小组和试点数据收集，该规划项目正在为实时和隐私保护学习系统的创新奠定基础，这些系统采用物联网和边缘计算来支持对实时个人健康数据的学习，并在不损害用户隐私的情况下提供实时个性化反馈。该项目还涉及异构数据集成和学习技术，以检测社会情绪和健康变化，并支持预防和早期干预。该项目以人类系统工程学和卫生信息学为基础。这一办法旨在满足老年人的各种需求，使他们能够更有效地管理自己的健康;该项目包括对社会、文化、该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响评估来支持的搜索.

Older adults strive to be independent and healthy yet compared with younger individuals, they are at greater risk of chronic health conditions and social isolation. Solutions are needed that create ways for older adults to thrive, connect, contribute to, and shape their communities. The increasingly available Internet of Things (IoTs), particularly wearables and smart home devices (e.g., smartwatches, voice-activated home assistants), offer important opportunities for real-time interventions for self-management of care, especially if they are customized to meet each person’s unique needs and goals. This planning project focuses on older military veteran populations in Phoenix, Arizona. The project is building a multidisciplinary team to form a research agenda for studying, developing, and deploying an IoT based solution for providing high quality, low cost, and community-sensituve self-managed care. This project can benefit Arizona’s large populations of older adults and veterans, with potential to impact underserved aging populations across the U.S. The project also provides education and workforce development to all levels of students from multiple disciplines, and in particular creates innovations and access for many underrepresented students at Arizona State University, where the project is based.Through focus groups and pilot data collection, this planning project is laying the groundwork for innovations in real-time and privacy-preserving learning systems which that employ IoTs and edge computing to support learning on live, personal health data and provide real-time, personalized feedback without compromising user privacy. The project also entails heterogeneous data integration and learning techniques to detect social-emotional, and health changes and support prevention and early interventions. The project builds on human-systems engineering and health informatics. This approach is designed to meet the diverse needs of older adults and to allow them to more effectively take charge of their health; The project includes an analysis of social, cultural, and relationship factors and their effects on cognitive and affective processes in older veterans.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.