Smart environment technology for longitudinal behavior analysis and intervention

描述(申请人提供)：世界人口正在老龄化，由此导致的慢性病流行是我们社会必须应对的挑战。我们的愿景是通过设计智能环境技术来应对这一挑战，让老年人尽可能长时间地在自己的家中独立运作。智能环境已被用作监测有健康状况的居民的活动的基础。然而，目前缺乏大规模的纵向研究来确定痴呆症的早期标志物和其他健康状态变化，并预测功能衰退。该项目的目标是对在自己的智能家居中进行日常活动的老年人进行为期5年的纵向研究。通过在很长一段时间内跟踪居民的日常行为，我们的智能软件可以执行自动功能评估，并识别作为急性健康变化(例如感染、伤害)和缓慢进行性下降(例如痴呆症)的指标的趋势。通过实施支持功能独立性和促进健康生活方式行为(例如，社交、锻炼、规律睡眠)的即时干预措施，我们可以全面提高 健康和幸福。我们假设，智能家居技术可以用来检测和预测功能变化，减缓功能变化和延长功能独立性，并改善有过渡到MCI和t痴呆风险的老年人的生活质量。这一假设是基于申请者提供的初步数据提出的，这些数据支持使用智能家居技术进行功能状态评估以及促使个人开始和完成活动的有效性 MCI和痴呆症。拟议工作的基本原理是，了解衰老和痴呆症之间功能变化的自然历史将导致早期预防和积极干预，从而减缓功能变化，从而推迟养老院的安置和社会护理成本。我们计划追求以下具体目标：(1)通过最小监督活动识别和活动发现来表征智能环境居民的日常生活方式，(2)设计检测行为数据趋势的软件算法，以及(3)评估活动感知自动提示技术在延长功能独立性和提高生活质量方面的效果。这项拟议的工作具有创新性，因为它将跟踪大量个人在自己家中的纵向情况，并确定这项技术是否可以用于促进健康的生活方式行为，并检测可能导致早期干预、提高生活质量和降低医疗保健利用率的医疗保健变化。该项目意义重大，因为它将引入需要最低限度监督的活动发现和跟踪新技术，贡献预测认知衰退和发出更剧烈健康状态变化信号的算法，并首次证明活动感知自动提示技术可以用于支持和/或减缓老年人的功能变化，并提高生活质量。

DESCRIPTION (provided by applicant): The world's population is aging and the resulting prevalence of chronic illnesses is a challenge that our society must address. Our vision is to address this challenge by designing smart environment technologies that keep older adults functioning independently in their own homes as long as possible. Smart environments have been used as the basis of monitoring activities for residents with health conditions. However, there is currently a lack of large scale, longitudinal research to identify early markers of dementia and other health status changes and to predict functional decline. The objective of this project is to perform a 5-year longitudinal study of older adults performing daily activities in thir own smart homes. By tracking residents' daily behavior over a long period of time our intelligent software can perform automated functional assessment and identify trends that are indicators of acute health changes (e.g., infection, injury) and slower progressive decline (e.g., dementia). By implementing prompt-based interventions that support functional independence and promote healthy lifestyle behaviors (e.g., social contact, exercise, regular sleep), we can improve overall health and well- being. We hypothesize that smart home technologies can be used to detect and predict functional change, to slow functional change and extend functional independence, and to improve quality of life in elderly individuals who are at risk of transitioning to MCI and t dementia. This hypothesis has been formulated on the basis of preliminary data produced by the applicants which supports the efficacy of using smart home technologies for both functional status assessment and for prompting the initiation and completion of activities in individuals with MCI and dementia. The rationale of the proposed work is that understanding the natural history of functional change between aging and dementia will lead to early prevention and proactive interventions that will slow functional change, thereby delaying nursing home placement and cost of care to society. We plan to pursue the following specific aims: (1) Characterize the daily lifestyle of smart environment residents through minimal-supervision activity recognition and activity discovery, (2) Design software algorithms that detect trends in behavioral data, and (3) Evaluate the efficacy of activity-aware automated prompting technology for extending functional independence and improving quality of life. The proposed work is innovative because it will track a large number of individuals longitudinal in their own homes and determine whether this technology can be used to promote healthy lifestyle behaviors and detect health care changes that may lead to early interventions, improved quality of life, and decreased health care utilization. The project is significant because it will introduce new technologies for activity discovery and tracking that require minimal- supervision, contribute algorithms that predict cognitive decline and signal more acute health status change, and demonstrate for the first time that activity-aware automated prompting technologies can be used to support and/or slow functional change and to increase quality of life in elderly individuals.