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Using in-Home Monitoring Technology to Identify Deviations in Daily Routines Preceding Changes in Health Trajectory of Older Adults.

机译:使用室内监测技术来识别老年人健康轨迹变化之前的日常工作中的偏差。

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摘要

The boom of in-home monitoring technology offers unprecedented information about an individual's interaction with the environment. A variety of low cost sensors can continuously and unobtrusively collect information about activities in the living space. Capturing early changes in the daily routines of vulnerable older adults residing in these "smart homes" may allow clinicians to predict and prevent negative health consequences through timely intervention. However, the current state of science is hampered by the lack of theoretically driven approaches to analyze sensor data in relation to clinically meaningful health outcomes. The aims of the study are 1) to characterize an older adult's daily routine, as captured with smart home sensors, 2) to assess if deviations from it are indicative of changes in their health trajectory, such as falls, ER visits or unplanned hospitalizations, and 3) identify between person factors that affect the characteristics of the daily routine. It used previously collected data from 10 residents of TigerPlace, a unique retirement facility that evaluates health technology affiliated with University of Missouri, Columbia. Older adults live in apartments equipped with network of motion, depth and bed sensors that unobtrusively collect information about daily activity of its resident. Thirty months of continuous sensor data were analyzed in the context of bi-annual clinical assessments and nursing notes extracted from the electronic health record. A retrospective multiple case study approach is guided by the conceptual model developed for this study that is grounded in nursing and gerontological literature. Changes in the temporality and frequency of daily activity were found for common geriatric symptoms, such as urinary symptoms and confusion. Seasonal and weekly effect was evident across participants in the duration of time spent in various areas of the apartment. Participants varied in their baseline daily routines, but for the majority of symptoms there were prodromal changes in at home activity that was detected with sensors. As the cost of technology adoption decreases, nurses can use these innovative tools to coordinate care and intervene early to prevent or mitigate the functional decline associated with vulnerable older adults.
机译:家庭监控技术的兴起为个人与环境的互动提供了前所未有的信息。各种各样的低成本传感器可以连续且毫不干扰地收集有关居住空间活动的信息。捕获居住在这些“智能房屋”中的弱势老年人的日常生活的早期变化,可以使临床医生通过及时干预来预测和预防负面的健康后果。但是,由于缺乏理论驱动的方法来分析与临床有意义的健康结果相关的传感器数据,目前的科学状况受到了阻碍。这项研究的目的是:1)表征使用智能家居传感器捕获的老年人的日常活动; 2)评估偏离它的行为是否表明他们的健康状况发生了变化,例如跌倒,急诊就诊或计划外的住院治疗,和3)在人与人之间确定影响日常生活特征的因素。它使用了先前从TigerPlace的10位居民那里收集的数据,该设施是一种独特的退休设施,用于评估与哥伦比亚密苏里大学附属的卫生技术。老年人住在配有运动,深度和床形传感器网络的公寓中,这些传感器可以毫不干扰地收集有关其居民日常活动的信息。在两年期临床评估和从电子健康记录中提取的护理说明的背景下,分析了30个月的连续传感器数据。回顾性多案例研究方法以本研究开发的概念模型为指导,该模型基于护理和老年医学文献。发现常见的老年症状,如泌尿症状和精神错乱,日常活动的时间和频率发生变化。参与者在公寓各个区域所花费的时间持续时间对季节性和每周影响显而易见。参与者的基线日常活动各不相同,但是对于大多数症状,使用传感器检测到的家庭活动中存在前驱性变化。随着技术采用成本的下降,护士可以使用这些创新工具来协调护理并及早干预,以预防或减轻与弱势老年人相关的功能下降。

著录项

  • 作者

    Yefimova, Maria.;

  • 作者单位

    University of California, Los Angeles.;

  • 授予单位 University of California, Los Angeles.;
  • 学科 Nursing.;Behavioral sciences.;Gerontology.
  • 学位 Ph.D.
  • 年度 2016
  • 页码 129 p.
  • 总页数 129
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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