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A New Adaptive Algorithm for Detecting Falls through Mobile Devices

机译:一种通过移动设备检测落下的新自适应算法

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Most of elderly people suffer physical degeneration that makes them particularly vulnerable to falls. Falls cause injuries, time of hospitalization, re-habilitation which is particularly difficult for the elderly and disabled. This paper presents a new system with advanced capacities for learning and adaptation spe-cifically designed to detect falls through mobile devices. The systems proposes a new adaptive algorithm able to learn, classify and identify falls from data obtained by mobile devices and user profile. The system is based on machine learning and data classification using decision trees. The main contribution of the proposed sys-tem is the use of posturographic data and medical patterns as a knowledge base, which notably improves the classification process.
机译:大多数老年人遭受身体变性,使它们特别容易受到摔倒。跌倒导致伤害,住院时间,对老年和残疾人特别困难的重新居所。本文介绍了一种新的系统,具有先进的学习和适应SPE-Cifically设计,用于通过移动设备检测落下。该系统提出了一种能够学习的新的自适应算法,分类和识别来自由移动设备和用户简档获得的数据的下降。该系统基于使用决策树的机器学习和数据分类。拟议的系统的主要贡献是使用后触发数据和医学模式作为知识库,这显着提高了分类过程。

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