SCC-PG: Fostering Aging-in-Place and Autonomy in Elderly Persons through Intelligent Tracking

SCC-PG：通过智能追踪促进老年人就地养老和自主

• 批准号: 1952236
• 负责人: Tracy Hammond
• 金额: $ 15万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2022-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1952236&HistoricalAwards=false
• 关键词: SCC; PG; Fostering; Aging; Place

As people age they begin to need assistance with activities of daily life (ADLs). Losing the ability to perform ADLs requires that these individuals receive care from family members, move to senior living communities or experience a significant drop in their quality of life. Given the projected rise in the number of older adults over the coming decades, the resources available to care for this population will be spread thin, potentially leaving some with lower quality of care or even without any form of care. One means of addressing this is developing systems that allow older adults to live independently while maintaining their quality of life for longer. Such systems would not only meet a well-documented desire to live independently, but also reduce the burden of care on caregivers and/or the need for more expensive forms of long-term care. This project will lay the groundwork for the development of a scalable gerontechnological system consisting of sensors and novel algorithms designed to recognize ADL performance in real-world settings. Through tracking of resident performance of ADLs we aim to facilitate more timely and relevant care and interventions.The project works with multiple senior living communities to develop a gerontechnological system that allows for a quantified daily health profile to enable meaningful care for those who wish to age-in-place. This planning grant attempts to answer the following research questions through interviews and observational studies with each collaborating senior living community and determination of preliminary technological details: (1) What are the specific needs of both caregivers and residents from a gerontechnological system built on the recognition of ADLs and resident location? (2) What are the requirements of the indoor positioning system (IPS)? (3) What are the privacy needs and concerns of the caretakers and residents and how can the system address them? The information gained from the planning grant will allow us to submit a multi-year Integrative Research Grant that will attempt to answer the following research questions: (1) Can common ADLs be accurately recognized using a combination of wearable devices and novel machine learning algorithms and methodologies? (2) How does the recognition of activity patterns, feedback to residents and caregivers, and individually-tailored interventions support and/or impact the lives of senior living community residents? (3) How does the recognition of activity patterns, feedback to residents and caregivers, and individually-tailored ADL support and/or impact the workload and ease the burden of care on the caregivers within the senior living facilities? Successful completion of this work has the potential to transform the current paradigm of elderly healthcare from reactive to proactive by monitoring and supporting the health of the elderly population.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.

随着年龄的增长，他们开始需要日常生活活动(ADL)方面的帮助。丧失执行ADL的能力需要这些人接受家庭成员的照顾，搬到老年生活社区，或者经历他们生活质量的显著下降。鉴于预计未来几十年老年人的数量将会增加，可用于照顾这一群体的资源将分散开来，可能会使一些人的护理质量较低，甚至没有任何形式的护理。解决这一问题的一种方法是开发系统，使老年人能够独立生活，同时更长时间地保持他们的生活质量。这种系统不仅能满足充分证明的独立生活的愿望，而且还能减轻照顾者的护理负担和/或对更昂贵的长期护理形式的需求。该项目将为开发一种可扩展的老年技术系统奠定基础，该系统由传感器和新算法组成，旨在识别现实世界中的ADL性能。通过跟踪居民的ADL表现，我们旨在促进更及时和相关的护理和干预。该项目与多个老年生活社区合作，开发一种老年技术系统，允许量化每日健康状况，使那些希望就地老龄化的人能够获得有意义的护理。本规划拨款试图通过对每个合作的老年生活社区的访谈和观察性研究，并确定初步的技术细节，试图回答以下研究问题：(1)基于ADL和居民位置识别的老年技术系统对照顾者和居民的具体需求是什么？(2)室内定位系统(IPS)的要求是什么？(3)照顾者和居民的隐私需求和担忧是什么，该系统如何解决这些需求？从规划拨款中获得的信息将使我们能够提交一份多年综合研究补助金，试图回答以下研究问题：(1)结合使用可穿戴设备和新颖的机器学习算法和方法，能否准确识别常见的ADL？(2)活动模式的识别、对居民和照顾者的反馈以及个性化的干预措施如何支持和/或影响老年社区居民的生活？(3)活动模式的识别、对居民和照顾者的反馈、和个人量身定做的ADL支持和/或影响工作量和减轻老年生活设施内照顾者的护理负担？这项工作的成功完成有可能通过监测和支持老年人的健康状况，将当前的老年医疗保健范式从反应性转变为主动性。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势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

Recognizing Seatbelt-Fastening Behavior with Wearable Technology and Machine Learning

• DOI: 10.1145/3411763.3451705
• 发表时间: 2021-05
• 期刊: Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems
• 作者: J. M. Leland;Ellen Stanfill;Josh Cherian;T. Hammond

An Activity Recognition System for Taking Medicine Using In-The-Wild Data to Promote Medication Adherence

使用野外数据促进服药依从性的服药活动识别系统

• DOI: 10.1145/3397481.3450673
• 发表时间: 2021
• 期刊: IUI '21: 26th International Conference on Intelligent User Interfaces
• 作者: Cherian, Josh;Ray, Samantha;Hammond, Tracy
• 通讯作者: Hammond, Tracy