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Smart ECG Holter Monitoring System Using Smartphone

机译:使用智能手机的智能心电动态心电图监测系统

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The Prevention of cardiovascular disease requires continuous monitoring of cross-clock ECG signals along with the activity status. Traditional ECG Holter has numerous electrodes connected to the chest, which is heavy, so it is very difficult to carry by the patient, so ECG monitoring usually requires the patient to stay in the hospital for a long time. This paper presented a small ECG Holter device that was developed to detect arrhythmias in real-time based on Android mobile application. The ECG signals are obtained directly through ECG's three-electrode sensor then transmitted through a Bluetooth module to Android smartphone. Prepossessing ECG signal algorithm is implemented on Arduino Device. Android mobile application analysis and classify patient's ECG data to detect abnormal signs. Data used in testing and training was 303 cases acquired from El-Monofia University, 162 cases were normal, and 141 cases were abnormally divided into 57 cases were Coronary Artery Disease, 36 cases were Old Anterior Myocardial Infarction, and 48 cases were Sinus tachycardia. The experimental results show that the presented system's performance has been improved in the accuracy of diagnosis of arrhythmias and the identification of the most widely recognized anomalies in various activities.
机译:预防心血管疾病需要连续监测全天候ECG信号以及活动状态。传统的ECG动态心电图的胸部连接有许多电极,很重,因此很难携带,因此ECG监视通常需要患者长时间住院。本文介绍了一种小型的ECG Holter设备,该设备是根据Android移动应用程序实时检测心律不齐而开发的。 ECG信号直接通过ECG的三电极传感器获取,然后通过蓝牙模块传输到Android智能手机。预设ECG信号算法在Arduino设备上实现。 Android移动应用程序分析并分类患者的ECG数据以检测异常征兆。用于测试和培训的数据是从莫诺菲亚大学获得的303例患者,正常162例,异常141例,分为冠状动脉疾病57例,陈旧性前部心肌梗塞36例,窦性心动过速48例。实验结果表明,该系统的性能在心律失常的诊断准确性和各种活动中最广泛认可的异常的识别方面得到了改善。

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