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PIR sensing array for fall detection.

机译:PIR感应阵列用于跌倒检测。

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摘要

The purpose of the Fuzzy PIR Fall Detection Array is to keep the elderly safe by providing a means for an immediate response to falls while still allowing them to enjoy the same independence they felt before fall detection was necessary. To accomplish this goal, a vertical array of passive infrared (PIR) motion sensors can be positioned anywhere in the home near where a fall may occur. A fall is considered to be observed by the sensor array when the sensors, first, detect motion, then, stop detecting motion in order from top to bottom. To differentiate between a legitimate fall and normal motion, pattern recognition techniques were used to observe the signals from the sensing array and classify whether a window of data was observed during a fall or a non-fall. To accomplish this goal, a Gaussian Parzen Window (GPW) and a relevance vector machine (RVM) were used with some success. This research shows that, for this application, the RVM is a superior classification method to the Parzen Window, where the RVM was able to detect falls with an accuracy of about 80% to the Parzen Window's about 75%. Besides being more accurate, the RVM algorithm has a faster run time for classifying the data. The sensing array explored in this research could be a viable option as a non-wearable means for protecting the elderly in the event that they should fall in their home.
机译:Fuzzy PIR跌倒检测阵列的目的是通过提供一种对跌倒的立即响应的方式来保持老年人的安全,同时仍然允许他们享受跌倒检测之前所感受到的独立性。为了实现此目标,可以将无源红外(PIR)运动传感器的垂直阵列放置在房屋中可能发生跌倒的任何位置。当传感器首先检测运动,然后按从上到下的顺序停止检测运动时,则认为传感器阵列已观察到跌倒。为了区分合法跌落和正常运动,使用模式识别技术观察来自传感阵列的信号,并对跌倒或非跌落期间是否观察到数据窗口进行分类。为了实现这一目标,使用了高斯Parzen窗口(GPW)和相关向量机(RVM)取得了一些成功。这项研究表明,对于此应用程序,RVM是Parzen窗口的一种更好的分类方法,其中RVM能够以大约80%的准确度检测跌落,而Parzen窗口的准确率约为75%。除了更精确之外,RVM算法还具有更快的运行时间来对数据进行分类。在这项研究中探索的传感阵列可能是一种可行的选择,因为它是老年人应跌落在家中时的一种非穿戴式保护装置。

著录项

  • 作者

    Moore, Michael J.;

  • 作者单位

    University of Missouri - Columbia.;

  • 授予单位 University of Missouri - Columbia.;
  • 学科 Engineering Computer.
  • 学位 M.S.
  • 年度 2011
  • 页码 136 p.
  • 总页数 136
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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