Detecting Health and Behavior Change by Analyzing Smart Home Sensor Data
Detecting Health and Behavior Change by Analyzing Smart Home Sensor Data
复制标题
通过分析智能家居传感器数据检测健康和行为变化
DOI：
10.1109/smartcomp.2016.7501687
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
M. Schmitter
中科院分区：
文献类型：
--
作者：
Gina Sprint;D. Cook;Roschelle Fritz;M. Schmitter
智能家居环境为悄悄监控人类行为提供了前所未有的机会。从智能家居收集的传感器数据可以使用活动识别进行标记，以帮助确定家庭行为与健康变化之间是否存在关系。为了检测和分析伴随健康事件而来的行为变化，我们引入了行为变化检测（BCD）方法。 BCD 检测时间窗口之间的活动时间和持续时间变化，确定检测到的变化的重要性，并分析变化的性质。我们通过两个案例研究来展示我们的方法，这些案例研究的对象是生活在智能家居中、经历过重大健康事件（包括癌症治疗和失眠）的老年人。我们的算法检测到的行为变化与这些病例的医学文献一致。结果表明可以使用 BCD 自动检测更改。所提出的智能家居、活动识别算法和变化检测方法是有用的数据挖掘技术，可用于了解主要健康状况的行为影响。
Smart home environments offer an unprecedented opportunity to unobtrusively monitor human behavior. Sensor data collected from smart homes can be labeled using activity recognition to help determine whether relationships exist between behavior in the home and health changes. To detect and analyze behavior changes that accompany health events, we introduce the behavior change detection (BCD) approach. BCD detects activity timing and duration changes between windows of time, determines the significance of the detected changes, and analyzes the nature of the changes. We demonstrate our approach using two case studies for older adults living in smart homes who experienced major health events, including cancer treatment and insomnia. Our algorithm detects behavior changes consistent with the medical literature for these cases. The results suggest the changes can be automatically detected using BCD. The proposed smart home, activity recognition algorithms, and change detection approach are useful data mining techniques for understanding the behavioral effects of major health conditions.
影响因子：
16.6
作者：
Bulling, Andreas;Blanke, Ulf;Schiele, Bernt
通讯作者：
Schiele, Bernt