Smart Environment Technologies for Health Assessment and Assistance

描述(申请人提供)：由于人口老龄化，由于认知或身体障碍而无法在家中独立生活的美国人的数量正在显著上升。关于如何应用机器学习技术改善健康监测，以及如何利用这些技术实施旨在维持独立生活的干预措施，目前在知识库中存在一个根本性的空白。这项工作的长期目标是通过开发有助于健康监测和干预的智能环境来改善人类健康并影响医疗保健的提供。这一特定应用的目标是设计、实施和评估用于评估日常功能限制和为早期痴呆症患者提供自动化干预策略的技术。对于大多数人来说，家是一个避难所，但今天那些需要特殊照顾的人，主要是老年人，必须离开家来满足临床需求。中心假设是，许多有认知障碍的老年人可以在自动化帮助和健康监测的帮助下，在自己的家里独立生活。拟议工作的合理性是，智能环境技术可以提高老年人的生活质量和医疗保健，他们需要在日常功能活动中得到帮助，并减轻照顾者和社会的情感和经济负担。在强大的初步数据以及计算机科学和临床神经心理学研究人员的合作伙伴关系的指导下，我们的中心假设将通过追求以下具体目标来验证：(1)设计使用智能环境数据识别真实世界环境中复杂的日常活动的软件算法，(2)使用智能环境自动进行功能健康评估并检查基于实验室的措施的生态有效性，(3)设计自动提醒和基于提示的干预措施，以帮助完成日常活动，以及(4)分析日常行为模式和生理数据之间的相关性。这项拟议的工作具有创新性，因为它定义了在我们最个人化的环境--我们的家--中检测和处理老龄化、早期痴呆症和残疾的方法。这项拟议的工作意义重大，因为它为对认知受限的个体进行自动、稳健的功能评估以及旨在提高这些个体的功能独立性的干预策略提供了基础。智能家居技术不依赖患者或告密者的自我报告，后者可能会或可能不会延长与患者相处的时间，智能家居技术将允许我们识别阻碍患者在开始发生时在家中保持独立能力的功能缺陷，并通过干预现实世界环境来延长在家中独立生活的时间。

DESCRIPTION (provided by applicant): The number of Americans unable to live independently in their homes due to cognitive or physical impairments is rising significantly due to the aging of the population. There is a currently a fundamental gap in the knowledge base concerning how to apply machine learning technologies to improve health monitoring and how to harness these technologies to implement interventions designed to sustain independent living. The long-term objective of this work is to improve human health and impact health care delivery by developing smart environments that aid with health monitoring and intervention. The objective of this particular application is to design, implement, and evaluate technologies for assessing everyday functional limitations and for providing automated intervention strategies for persons with early-stage dementia. To most people home is a sanctuary, yet today those who need special care, predominantly older adults, must leave home to meet clinical needs. The central hypothesis is that many older adults with cognitive impairment can lead independent lives in their own homes with the aid of automated assistance and health monitoring. The rational for the proposed work is that smart environment technologies can improve quality of life and health care for older adults who require assistance with everyday functional activities and reduce the emotional and financial burden for caregivers and society. Guided by strong preliminary data and a partnership between computer science and clinical neuropsychology researchers, our central hypothesis will be tested by pursuing the following specific aims: (1) Design software algorithms that use smart environment data to recognize complex everyday activities in real-world settings, (2) Use smart environments to automate functional health assessment and to examine the ecological validity of laboratory-based measures, (3) Design automated reminder and prompting-based interventions to aid with everyday activity completion, and (4) Analyze correlations between everyday behavioral patterns and physiological data. The proposed work is innovative because it defines methods of detecting and coping with aging, early dementia and disabilities in our most personal environments: our homes. The proposed work is significant because it provides the basis for automated, robust functional assessment of individuals with cognitive limitations and of intervention strategies designed to improve functional independence for these individuals. Rather than relying on self-reporting by the patient or by an informant who may or may not spend extended time with the patient, smart home technologies will allow us to identify functional deficits that impede a patient's ability to maintain independence in their home as they begin to occur, and to extend independent living at home by intervening in a real world setting.