兼容心电诊断云计算框架及原型应用

Zhen Zhang, Hongqiang Li, Zheng Gong, Rize Jin, Tae-Sun Chung
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引用次数: 0

摘要

心电信号的分析和诊断算法已经研究了几十年。有一些最先进的算法已经被开发出来。在本文中,我们提出了一个兼容的心电自动诊断云计算框架,以整合这些现有的算法。另一方面,基于物联网的健康诊断系统也有很多研究。但针对个人使用的健康监测与诊断技术还不多见。基于我们提出的框架,用户可以随时随地方便地通过移动应用程序对自己的心脏健康状况进行诊断。心电特征自动分类计算算法通过在云计算端引入混合编程技术,兼容Python和MATLAB。因此,研究人员可以很容易地将他们开发的算法集成到该框架中,从而快速构建应用程序。我们还开发了一个原型应用程序来验证这个框架的可用性。
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A Compatible ECG Diagnosis Cloud Computing Framework and Prototype Application
The ECG signal analysis and diagnosis algorithms have been studied for decades. There are some state of art algorithms that have been developed. In this paper, we proposed a compatible ECG automatic diagnosis Cloud Computing framework in order to integrate these exist algorithms. On the other hand, there are many studies regarding the IoT based health diagnosis system. But there are few of that aiming at the personal use health monitor and diagnose. Basing on our proposed framework, users can diagnose their heart health status by themselves conveniently anywhere and anytime through the mobile application. The ECG character automatic classification computing algorithm is compatible for Python and MATLAB by introducing the hybrid programming technic on the cloud computing side. So that, it is easy for researchers to integrate their developed algorithm into this framework to build an application quickly. We developed a prototype application as well to verify the availability of this framework.
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