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A New Adaptive Algorithm for Detecting Falls through Mobile Devices

机译:一种新的自适应检测移动设备跌落的算法

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Most of elderly people suffer physical degeneration that makes them particularly vulnerable to falls. Falls cause injuries, time of hospitalization, rehabilitation which is particularly difficult for the elderly and disabled. This paper presents a new system with advanced capacities for learning and adaptation specifically 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 system 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退化,这使他们特别容易跌倒。跌倒会导致受伤,住院时间和康复,这对于老年人和残疾人尤其困难。本文提出了一种具有先进的学习和适应能力的新系统,该系统专门用于检测通过移动设备的跌倒。该系统提出了一种新的自适应算法,该算法能够从移动设备和用户个人资料获得的数据中学习,分类和识别跌倒。该系统基于机器学习和使用决策树的数据分类。提出的系统的主要贡献是使用了地形学数据和医学模式作为知识库,这显着改善了分类过程。

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