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Monitoring changes in behaviour from multi-sensor systems

机译:监视来自多传感器系统的行为变化

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摘要

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.
机译: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指示健康状况的变化。当前,使用基于纸张的评估技术来进行有限的行为监视。随着技术的日益普及和低成本,人们越来越倾向于自动化的行为监控系统。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,这在提取有用的指标方面构成了重大问题。提出了一种新颖的方法,用于检测行为模式并计算度量以量化多传感器环境中的行为变化。显示了数据分析方法,并对该方法进行了实验验证,结果表明可以检测工作日和周末之间的差异。分析了两个参与者,使用不同的传感器配置和测试环境,并且在两种情况下,结果均显示,使用提出的方法,工作日和周末的行为变化指标在95%置信度上有显着差异。

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