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

SHB：媒介：合作研究：打造以人为本的环境来支持人类健康需求

• 批准号: 1404673
• 负责人: Sajal Das
• 金额: $ 21.99万
• 依托单位: Missouri University of Science and Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-31 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1404673&HistoricalAwards=false
• 关键词: SHB; Medium; Collaborative; Research; Crafting

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.

研究人员和提供商都认识到，以人为中心的智能环境可以提供健康监测服务，并通过适应性干预支持就地老龄化。人口老龄化、正规医疗保健的成本以及个人对在自己家里保持独立的重视，都突显了发展这类技术的必要性。这个项目的目标是设计、实施和评估家庭技术，以生成活动和社交互动的报告，这些报告对监测痴呆患者的福祉和自动化干预策略是有用的。该计划是设计机器学习技术，有效利用传感器数据来执行自动化活动监测和基于提示的干预，对居民及其照顾者和家人有利。环境是以人类为中心的，因为它了解关于人类居民的信息，并使用这些信息提供活动感知的监测和干预服务。通过将日常环境转变为智能环境，许多患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有志愿老年人的实际家庭中对这些技术进行评估，从而评估目标人群接受这些技术的情况。该项目致力于实现美国国家科学基金会S智能健康与福祉的目标，即利用计算专业知识在算法开发方面取得根本性进展，以改进安全、有效和以患者为中心的健康与健康服务。通过设计Gerontech课程，我们正在培训学生设计和使用这些技术。这一努力包括REU和IGERT的学生参与研究项目，该项目让来自代表性不足群体的学生参与这一多学科的合作努力。为了方便整个社区的使用、比较和协作，我们的所有数据集、工具和课程材料都将通过我们的项目网页进行传播。