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Learning Based Falling Detection Using Multiple Doppler Sensors

机译:使用多个多普勒传感器的基于学习的跌倒检测

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Automated falling detection is one of the important tasks in this ageing society. Such systems are supposed to have little interference on daily life. Doppler sensors have come to the front as useful?devices to detect human activity without using any wearable sensors. The conventional Doppler sensor based falling detection mechanism uses the features of only one sensor. This paper presents falling detection using multiple Doppler sensors. The resulting data from sensors are combined or selected to find out the falling event. The combination method, using three sensors, shows 95.5% accuracy of falling detection. Moreover, this method compensates the drawbacks of mono Doppler sensor which encounters problems when detecting movement orthogonal to irradiation directions.
机译:自动跌倒检测是这个老龄化社会的重要任务之一。这样的系统应该对日常生活几乎没有干扰。多普勒传感器已经成为最有用的设备,无需使用任何可穿戴传感器即可检测人类活动。基于传统多普勒传感器的跌倒检测机制仅使用一个传感器的功能。本文介绍了使用多个多普勒传感器的跌倒检测。来自传感器的结果数据被组合或选择以找出掉落事件。使用三个传感器的组合方法显示跌落检测的准确度为95.5%。而且,该方法弥补了单多普勒传感器的缺陷,该缺陷在检测与辐射方向正交的运动时会遇到问题。

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