Good-Eye:智能家居中老年人跌倒的自动预测和检测装置

Laavanya Rachakonda, S. Mohanty, E. Kougianos
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引用次数: 5

摘要

这是一个基于我们已发表的工作[1]的研究演示会议的扩展摘要。重要的是能够减少老年人跌倒的频率及其灾难性影响。Good-Eye提出了一种边缘设备,它基于图像方向和使用医疗物联网(IoMT)的生理传感器来预测或检测跌倒。使用LED灯,如果观察到的变化大于设定的阈值,则会通知用户进行跌倒预测和检测的决定。Good-Eye系统除了在可穿戴设备上安装一个摄像头外,还提供了一个远程离线墙上摄像头,以更准确地预测和检测跌倒。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Good-Eye: A Device for Automatic Prediction and Detection of Elderly Falls in Smart Homes
This is an extended abstract for a Research Demo Session based on our published work [1]. It is important to be able to reduce the frequency of elderly falls and their disastrous effects. Good-Eye proposes an edge device which predicts or detects falls based on image orientation and physiological sensors using the Internet-of-Medical-Things (IoMT). Using LED lights, the user is notified with the decision of fall prediction and detection if the observed change is greater than a set threshold. Along with a camera attached to the wearable, the Good-Eye system proposes a remote off-line on-wall camera to make more accurate prediction and detection of falls.
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