Inertial Sensor based Post Fall Analysis for False Alarming Reduction

Lin Ye, Kai Cao, Yingjie J Guo, Xiaojing Huang, Peter Beadle, Ahmadreza Argha, Massimo Piccardi, Guangquan Zhang, and Steven W. Su


Fall detection, Inertial sensor, Post fall behavior


One of the major public health problems among elderly people is falling injury. This study investigates fall detection and prevention by using inertial sensors for which the major existing challenging is how to significantly reduce false alarming in order to enhance the acceptance of elderly users during rehabilitation and daily exercises. Different from most existing approaches in the literature, the behavior after falling will be analyzed in details, which can not only greatly reduce false alarming, but also significantly improves the accuracy of the assessment of the severity of falling injuries

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