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Reliable Human Fall Prediction Utilizing Robot Fall Prediction Algorithm

机译:利用机器人跌倒预测算法进行可靠的人类跌倒预测

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The increasingly aging population has inspired a great deal of research in the prevention of fall injuries. A pragmatic and accurate technique to predict fall incidence, along with a corresponding mobile phone app, is proposed in this paper. The technique aims to integrate the benefits of traditional medical history based paradigm and non-historical paradigm and overcome the disadvantage on both paradigms, i.e. too long alert time of the history based paradigm and too short alert time for the non-historical approach. The breakthrough comes from the application of robot fall prediction algorithm to the human subjects. In our previous paper, a similar mobile app analyzes single leg motion to predict the fall of the carrying individual with a little too short alert time. Hence our previous method falls more on the side of non-historical paradigm, not a real hybrid or midway technique. The technique given in this paper represents the real solution, though the human side data is not presented. The missing data will be provided in our next paper.
机译:日益老龄化的人口激发了预防跌倒伤害的大量研究。本文提出了一种实用且准确的预测跌倒发生率的技术,以及相应的手机应用程序。该技术旨在整合传统医学历史范式和非历史范式的优势,并克服两种范式的缺点,即基于历史范式的警报时间过长,对于非历史方法而言警报时间过短。突破来自将机器人跌倒预测算法应用于人类对象。在我们之前的论文中,一个类似的移动应用程序分析了单腿运动,以预测预警时间太短的携带者的跌倒。因此,我们先前的方法更多地属于非历史范式,而不是真正的混合技术或中途技术。本文中给出的技术代表了真正的解决方案,尽管没有提供人为数据。缺少的数据将在我们的下一篇文章中提供。

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