SHB: Medium: Collaborative Research: Crafting a Human-Centric Environment to Support Human Health Needs

研究人员和供应商都认识到，以人为中心的智能环境可以提供健康监测服务，并通过适应性干预措施支持老龄化。人口老龄化、正规保健的费用以及个人对在自己家中保持独立的重要性，都突出了发展这种技术的必要性。该项目的目标是设计、实施和评估用于生成活动和社会互动报告的家庭技术，这些技术有助于监测痴呆症患者的健康状况和自动化干预策略。该计划旨在设计机器学习技术，有效利用传感器数据来执行自动活动监测和基于提示的干预措施，这对居民及其护理人员和家人都有益。环境是以人为中心的，因为它学习有关其人类居民的信息，并使用这些信息提供活动感知监测和干预服务。通过将日常环境转变为智能环境，许多有认知和身体障碍的老年人可以在自己的家中独立生活。该项目的一个关键组成部分是在实际家庭中对志愿老年人的技术进行评估，从而评估目标人群是否接受这些技术。该项目涉及NSF？Smart Health and Wellbeing的目标是利用计算专业知识，在算法开发方面取得根本性进步，从而改善安全、有效和以患者为中心的健康和保健服务。通过老年科技课程的设计，我们正在训练学生设计和使用这些技术。这项工作包括REU和IGERT的学生参与研究项目，该项目涉及来自这个多学科合作努力中代表性不足的群体的学生。为了促进社区范围内的使用、比较和合作，我们所有的数据集、工具和课程材料将从我们的项目网页上发布。

Researchers and providers alike are recognizing that human-centric smart environments can provide health monitoring services and support aging in place through adaptive interventions. The need for the development of such technologies is underscored by the aging of the population, the cost of formal health care, and the importance that individuals place on remaining independent in their own homes. The goal of this project is to design, implement, and evaluate in-home techniques for generating reports of activities and social interactions that are useful for monitoring well being and for automating intervention strategies for persons with dementia. The plan is to design machine learning techniques that make effective use of sensor data to perform automated activity monitoring and prompting-based interventions that are beneficial for the residents as well as for their caregivers and family. The environment is human-centric because it learns information about its human residents and uses this information to provide activity-aware monitoring and intervention services. By transforming everyday environments into smart environments, many older adults with cognitive and physical impairment can lead independent lives in their own homes. A key component of this project is an evaluation of the technologies in actual homes with volunteer older adults and thus will assess the technologies for acceptance with the target population. This project addresses NSF?s Smart Health and Wellbeing goal of leveraging computational expertise leading to fundamental advances in the development of algorithms to create improvements in safe, effective, and patient-centered health and wellness services. Through design of a Gerontechnology class we are training students to design and use these technologies. This effort includes REU and IGERT students in the research project, which involves students from underrepresented groups in this multidisciplinary, collaborative effort. To facility community-wide use, comparison and collaboration, all of our datasets, tools, and course materials will be disseminated from our project web page.