心律失常心电图远程分诊

T. Limpiti, Thunchanok Chokchaichumnankit, Jirayu Sanguanchom, Natchanon Soyphan, N. Puttarak
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引用次数: 0

摘要

在新冠肺炎疫情期间,远程医疗已成为接受医疗服务的一种有利方式。它减少了身体接触,也有利于那些住在离医院较远的人。在本文中,我们提出了一种使用心电图(ECG)进行心律失常远程分诊的方法。该系统由心律失常诊断算法和Android应用程序组成。该诊断算法可以检测五种类型的心脏问题——心律失常、心动过缓、心动过速、慢速心律失常和快速心律失常。Android应用程序是患者和医疗保健提供者之间的主要沟通渠道。用户上传他们的心电图,并通过应用程序接收他们心脏健康的初步诊断。当系统检测到异常情况时,会通知用户。然后,用户可以在网上预约到医院进行进一步检查。采用PhysioNet-MITBIH正常窦性心律数据库、MIT-BIH心律失常数据库、MIT-BIH房颤数据库和CU室性心动过速数据库四个数据库对该系统的功能进行了评估。实验结果表明,该算法检测异常心电信号的平均准确率为82.1%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cardiac Arrhythmia Teletriage using Electrocardiogram
Telehealth has become a favorable method for receiving medical care during the COVID-19 pandemic. It reduces physical contact and also benefits those who live a distance from hospitals. In this paper we present a cardiac arrhythmia teletriage using electrocardiogram (ECG). The system consists of a diagnostic algorithm for arrhythmias and an Android application. The diagnostic algorithm can detect five types of cardiac problems–arrhythmia, bradycardia, tachycardia, bradyarrhythmia, and tachyarrhythmia. The Android application is the main communication channel between patients and healthcare providers. The user uploads their ECG and receives a preliminary diagnosis of their heart health via the application. The system notifies the user if it detects any abnormalities. The user can then make an appointment online for further examination at the hospital. The capability of the proposed system is evaluated using four databases from PhysioNet—MITBIH Normal Sinus Rhythm Database, MIT-BIH Arrhythmia Database, MIT-BIH Atrial Fibrillation Database, and CU Ventricular Tachyarrhythmia Database. It is found that the algorithm is able to detect abnormal ECG signals with an average accuracy of 82.1%.
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