首页> 外文期刊>International Journal of Pattern Recognition and Artificial Intelligence >Real-Time Mobile-Based Electrocardiogram System for Remote Monitoring of Patients with Cardiac Arrhythmias
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Real-Time Mobile-Based Electrocardiogram System for Remote Monitoring of Patients with Cardiac Arrhythmias

机译:基于实时移动的心电图系统,用于远程监测心律失常患者

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In this study, we propose an electrocardiogram (ECG) system for the simultaneous and remote monitoring of multiple heart patients. It consists of three main components: patient, sever, and monitoring units. The patient unit uses a wearable miniature sensor that continuously measures ECG signals and sends them to a smart mobile phone via a Bluetooth connection. In the mobile device, the ECG signals can be stored, displayed on screen, and automatically transmitted to a distant server unit over the internet; the server stores ECG data from several patients. Health care stakeholders use a monitoring unit to retrieve the ECG signals of multiple patients at any time from the server for display and real-time automatic analysis. The analysis includes segmentation of the ECG signal into separate heartbeats followed by arrhythmia detection and classification. When compared to existing real-time ECG systems, where the detection of abnormalities is usually performed using simple rules, the proposed system implements a real-time classification module that is based on a support vector machine (SVM) classifier. Extensive experimental results on ECG data obtained from a TechPatient (TM) simulator, a real person, and 20 records from the MIT arrhythmia database are reported and discussed.
机译:在这项研究中,我们提出了一种用于同时和远程监测多重心脏患者的心电图(ECG)系统。它由三个主要组成部分组成:患者,服务员,监控单位。患者单元使用可穿戴式微型传感器,可通过蓝牙连接连续测量ECG信号并将它们发送到智能手机。在移动设备中,可以存储在屏幕上的ECG信号,并在互联网上自动发送到远程服务器单元;服务器从几个患者存储ECG数据。医疗保健利益相关者使用监控单元随时从服务器随时检索多名患者的ECG信号,以显示和实时自动分析。该分析包括ECG信号的分割,以单独的心跳,然后是心律失常检测和分类。与现有实时ECG系统相比,在通常使用简单规则执行异常的检测时,所提出的系统实现了基于支持向量机(SVM)分类器的实时分类模块。报告并讨论了从TechPatient(TM)模拟器,真实的人员和MIT心律失常数据库中获得的20条记录的ECG数据的广泛实验结果。

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