Monitoring changes in behaviour from multi-sensor systems.
Monitoring changes in behaviour from multi-sensor systems.
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DOI：
10.1049/htl.2014.0089
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发表时间：
2014-10
影响因子：
2.1
通讯作者：
James CJ
中科院分区：
文献类型：
--
作者：
Amor JD;James CJ
行为模式是许多情况下健康状况的重要指标，行为的变化通常可以表明健康状况的变化。目前，有限的行为监控是使用纸质评估技术进行的。随着技术变得更加普遍和低成本，越来越多的人转向自动化行为监控系统。这些系统通常利用多传感器环境来收集数据。以这种方式产生大量数据，这在提取有用指标方面提出了重大问题。提出了一种新方法，用于检测行为模式并计算量化多传感器环境中行为变化的指标。展示了数据分析方法，并对该方法进行了实验验证，表明可以检测工作日和周末之间的差异。使用不同的传感器配置和测试环境对两名参与者进行了分析，在这两种情况下，结果表明，使用所提供的方法，工作日和周末的行为变化指标在 95% 的置信水平下存在显着差异。
Behavioural patterns are important indicators of health status in a number of conditions and changes in behaviour can often indicate a change in health status. Currently, limited behaviour monitoring is carried out using paper-based assessment techniques. As technology becomes more prevalent and low-cost, there is an increasing movement towards automated behaviour-monitoring systems. These systems typically make use of a multi-sensor environment to gather data. Large data volumes are produced in this way, which poses a significant problem in terms of extracting useful indicators. Presented is a novel method for detecting behavioural patterns and calculating a metric for quantifying behavioural change in multi-sensor environments. The data analysis method is shown and an experimental validation of the method is presented which shows that it is possible to detect the difference between weekdays and weekend days. Two participants are analysed, with different sensor configurations and test environments and in both cases, the results show that the behavioural change metric for weekdays and weekend days is significantly different at 95% confidence level, using the methods presented.