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SCC-IRG JST: Active sensing and personalized interventions for pandemic-induced social isolation

SCC-IRG JST：针对大流行引起的社会隔离的主动感知和个性化干预

基本信息

批准号：
2125561
负责人：
Insup Lee
金额：
$ 75万
依托单位：
University of Pennsylvania
依托单位国家：
美国
项目类别：
Continuing 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：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2125561&HistoricalAwards=false
关键词：
SCC IRG JST Active sensing

项目摘要

Social connections are essential for individuals' health and the growth of a community. Social isolation is an increasing concern in developed countries with aging populations. The American Academy of Social Work and Social Welfare calls social isolation ``a silent killer as dangerous to health as smoking.'' The onset of the COVID-19 pandemic greatly exacerbated the problems of social isolation, depriving older adults of their personal interactions with peers and often even with caregivers. This proposal aims to develop and evaluate techno-social solutions to increase the social interactions between older adults within a community, reducing the level of social isolation within a community, while maintaining the required social distancing --- issues of great importance in the US and Japan. This project represents a collaboration between academic researchers and community partners in the U.S. and Japan, who will provide a potential pathway for transitioning research results to practice. Although this project focuses on social isolation in older adults, knowledge developed through this project can be applied to other age groups and other domains in mental health and healthcare.The aim is to develop a technology platform and tools to facilitate re-engagement of community members at high risk for social isolation. It will enable the delivery of tailored interventions to connect community members with peers and caregivers in the community at the individual level, as well as interventions to plan and coordinate services at the community level. The potential of this work will be demonstrated with two distinctly different communities of older adults at high risk for social isolation, one in the U.S. and one in Japan. This proposal addresses the following technical challenges: (1) Identification of new sensing modalities to complement sensors already used in the field. (2) Develop techniques and algorithms to analyze collected state information to predict with sufficient likelihood the onset of a problem early enough for caregivers to react to the problem. (3) Personalization of the proposed interventions, i.e., adapting interventions to a specific individual at runtime, with a focus on decision-making at the community level. (4) Develop a platform to integrate sensors with data storage and the analysis engine ensuring security of the system and protecting privacy of the individuals.This project is a joint collaboration between the National Science Foundation and the Japan Science and Technology Agency.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.

社会关系对个人的健康和社区的发展至关重要。在人口老龄化的发达国家，社会孤立越来越令人担忧。美国社会工作和社会福利学会称社会孤立是“一个无声的杀手，对健康的危害与吸烟一样大。“新冠肺炎疫情的爆发大大加剧了社交孤立的问题，剥夺了老年人与同龄人甚至照顾者的个人互动。该提案旨在开发和评估技术社会解决方案，以增加社区内老年人之间的社会互动，减少社区内的社会隔离程度，同时保持所需的社会距离-美国和日本非常重要的问题。该项目代表了美国和日本的学术研究人员和社区合作伙伴之间的合作，他们将为将研究成果转化为实践提供潜在的途径。虽然本项目的重点是老年人的社交孤立，但通过本项目开发的知识可以应用于其他年龄组和精神健康和医疗保健的其他领域，目的是开发一个技术平台和工具，以促进社交孤立风险较高的社区成员重新参与。这将有助于提供量身定制的干预措施，在个人层面上将社区成员与社区中的同龄人和照顾者联系起来，并采取干预措施，规划和协调社区一级的服务。这项工作的潜力将在两个截然不同的老年人社区中得到证明，一个在美国，一个在日本。该提案解决了以下技术挑战：（1）确定新的传感模式，以补充已在现场使用的传感器。(2)开发技术和算法来分析收集的状态信息，以足够的可能性预测问题的发生，以便护理人员能够尽早对问题做出反应。 (3)建议干预措施的个性化，即，使干预措施在运行时适合具体个人，重点是社区一级的决策。 (4)开发一个集成传感器、数据存储和分析引擎的平台，确保系统的安全性和保护个人隐私。该项目是国家科学基金会和日本科学技术厅的共同合作项目。该奖项反映了NSF的法定使命，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（10）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Using digital phenotyping to understand health-related outcomes: A scoping review

使用数字表型分析来了解健康相关结果：范围界定审查

DOI：
10.1016/j.ijmedinf.2023.105061
发表时间：
2023
期刊：
International Journal of Medical Informatics
影响因子：
4.9
作者：
Lee, Kyungmi;Lee, Tim Cheongho;Yefimova, Maria;Kumar, Sidharth;Puga, Frank;Azuero, Andres;Kamal, Arif;Bakitas, Marie A.;Wright, Alexi A.;Demiris, George
通讯作者：
Demiris, George

Interpretable Detection of Distribution Shifts in Learning Enabled Cyber-Physical Systems

对支持学习的网络物理系统中分布变化的可解释检测

DOI：
10.1109/iccps54341.2022.00027
发表时间：
2022
期刊：
ACMIEEE International Conference on CyberPhysical Systems
影响因子：
0
作者：
Yang, Yahan;Kaur, Ramneet;Dutta, Suradeep;Lee, Insup
通讯作者：
Lee, Insup

iCareLoop: Closed-Loop Sensing and Intervention for Gerontological Social Isolation and Loneliness

iCareLoop：针对老年社会孤立和孤独感的闭环感知和干预

DOI：
10.1145/3576841.3589632
发表时间：
2023
期刊：
ACM
影响因子：
0
作者：
Ji, Xiayan;Yuh, Ahhyun;Choi, Hyonyoung;Watson, Amanda;Kendell, Claire;Li, Xian;Weimer, James;Nagahara, Hajime;Higashino, Teruo;Mizumoto, Teruhiro
通讯作者：
Mizumoto, Teruhiro

PAC-Wrap: Semi-Supervised PAC Anomaly Detection

PAC-Wrap：半监督 PAC 异常检测

DOI：
发表时间：
2022
期刊：
KDD
影响因子：
0
作者：
Ji, X.;Li, S.;Dobriban, E.;Sokolsky, O.;Lee I.
通讯作者：
Lee I.

Incremental Anomaly Detection with Guarantee in the Internet of Medical Things

DOI：
10.1145/3576842.3582374
发表时间：
2023-05
期刊：
Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation
影响因子：
0
作者：
Xiayan Ji;Hyonyoung Choi;O. Sokolsky;Insup Lee
通讯作者：
Xiayan Ji;Hyonyoung Choi;O. Sokolsky;Insup Lee