SCH: INT: Collaborative Research: BESI: Behavioral and Environmental Sensing and Intervention for Dementia Caregiver Empowerment

一些痴呆症患者(PWD)表现出的焦虑导致的照顾者负担、压力和抑郁是PWD从就地老龄化过渡到长期护理机构的主要原因。由照顾者提供的非药物干预(例如，分散注意力、提供休息、平静环境、轻声说话、温柔触摸、选择最喜欢的音乐等)。可以减少PWD中的激越频率和严重程度。然而，情绪激动可能是不可预测的，并受到环境的影响，早期的情绪激动迹象往往没有被发现，并可能升级为更难管理的攻击性情绪激动。因此，大多数用于处理痴呆症患者激越的方法都是被动的，而不是主动的，并且在激越升级时使用太晚而不有效。预测躁动发作和检测躁动早期阶段的工具将使照顾者能够及早干预并最终减少躁动，从而减轻照顾者的负担，延长就地老龄化以及相关的生活质量和成本效益。这种基于照顾者赋权的残疾护理战略可能会对残疾儿童就地老龄化的能力产生重大影响。将开展社区外展工作，让残疾人及其照顾者在整个项目中参与进来，由此产生的知识产品可以传播给各种社会文化生态系统中的一系列利益攸关方，从研究人员到家庭成员和暂养者。该项目以普遍获取的做法为基础，展示了一种有益于最广泛的用户群体并可供其使用的设计。该项目还将为工程师、临床医生和护理社区之间的协作方法建立一个框架，以满足关键的医疗需求，这将成为新的课程模块和会议工作坊的基础。该项目将克服实现这种工具的基本科学障碍，并通过使用行为和环境传感和干预的三阶段研究计划。首先，将开发一个人体佩戴和居家传感器系统，以提供连续的、非侵入性的搅动评估和环境背景监测。第二，这个系统将被部署在社区居住的残障人士的家中，以模拟激怒与环境之间的关系，并识别早期激怒的特征，这两者都将为制定实时照顾者通知策略提供信息。第三，将通过一项人类受试者先导研究来演示概念验证，照顾者将收到实时通知，以便在可能的激动期之前改变环境，并在激动期的早期阶段实施PWD干预。调查团队结合了技术功能(计算机工程)、可访问性(以人为中心的设计)和适用性(医学研究和临床护理)方面的专业知识，以解决多模式传感系统系统、网络-社会-物理系统动力学建模和实时通知的基本挑战-所有这些都在关键的社会需求的背景下进行。不同的传感器流将通过融合多个时间尺度上的各种数据类型进行聚合，聚合数据将使用新的搅动评估和环境表征方法进行分析，提取的信息将用于开发动态系统模型，定制的自动通知将使护理人员能够在搅动升级之前进行干预-所有这些都将满足实时干预要求。这些模型将是特定于PWD护理者二元组的，需要动态的现场培训，并将为网络-社会-物理系统提供新的本体，其中结合了上下文、技术和社会二元组，以预测和缓解破坏性神经事件。痴呆症复杂系统干预的本体论尚不存在，但将通过该项目团队的探索、综合和分析努力而出现。有关该项目的更多信息，请参阅该项目的网站：http://wirelesshealth.virginia.edu/content/BESI

Caregiver burden, stress, and depression resulting from agitation exhibited by some people with dementia (PWD) are the primary reasons cited for PWD transitioning from aging-in-place to long-term care facilities. Non-pharmacological interventions provided by caregivers (e.g., distraction, providing rest, calming the environment, speaking softly, gentle touch, favorite music selections, etc.) can reduce the frequency and severity of agitation in PWD. However, agitation can be unpredictable and influenced by the environment, and early signs of agitation often go undetected and can escalate to aggressive agitation that is more difficult to manage. As a result, most methods used to deal with agitation in dementia are reactive rather than proactive and are administered too late in an agitation escalation to be effective. A tool to predict agitation episodes and detect early stages of agitation would empower caregivers to intervene early and ultimately reduce agitation, thus reducing caregiver burden and extending aging-in-place and the associated quality-of-life and cost benefits. This caregiver empowerment based strategy to PWD care could have a significant impact on the ability of PWD to age-in-place. Community outreach efforts will be conducted that engage PWD and their caregivers throughout the project, and the resulting knowledge products can be disseminated to a range of stakeholders across various sociocultural ecosystems, from researchers to family members and respite providers. The project rests on the practice of universal access, demonstrating a design that is beneficial to and accessible by the broadest range of user groups. This project will also establish a framework for a collaborative approach between engineers, clinicians, and the caregiving community to address critical healthcare needs, which will be the basis of new course modules and conference workshops.This project will overcome the fundamental scientific barriers to realizing such a tool with a three-phase research plan to employ Behavioral and Environmental Sensing and Intervention. First, a system of body-worn and in-home sensors will be developed to provide continuous, non-invasive agitation assessment and environmental context monitoring. Second, this system will be deployed in the homes of community-dwelling PWD to model the relationship between agitation and the environment and to identify features of early-stage agitation, both of which will inform the development of real-time caregiver notification strategies. Third, proof-of-concept for will be demonstrated through a human subject pilot study, with caregivers receiving real-time notifications to alter the environment in advance of probable agitation episodes and to administer PWD interventions in the early stages of agitation. Successful completion of this 3-phase project will motivate a follow-up large-scale proof-of-practice study.The investigative team combines expertise in technology function (computer engineering), accessibility (human centered design), and applicability (medical research and clinical care) to address fundamental challenges of multimodal sensing system-of-systems, modeling cyber-socio-physical system dynamics, and real-time notifications - all within the context of a critical societal need. Diverse sensor streams will be aggregated by fusing assorted data types across multiple time scales, aggregated data will be analyzed using novel agitation assessment and environmental characterization methods, extracted information will be used to develop dynamic system models, and customized automated notifications will empower caregivers to intervene before agitation escalation - all while meeting real-time intervention requirements. These models will be PWD-caregiver dyad specific, requiring dynamic in-situ training, and will present new ontologies for cyber-socio-physical systems that incorporate contexts, technologies, and social dyads to predict and mitigate disruptive neurological events. Ontologies for complex systems interventions in dementia do not yet exist but will emerge from the exploratory, integrative, and analytical efforts of this project team.For further information on this project, see the project web site: http://wirelesshealth.virginia.edu/content/BESI