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Development of a triage engine enabling behavior recognition and lethal arrhythmia detection for remote health care system

机译:开发分类诊断引擎,实现行为识别和致命性心律失常检测,可用于远程医疗系统

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For ubiquitous health care systems which continuously monitor a person''s vital signs such as electrocardiogram (ECG), body surface temperature and three-dimensional (3D) acceleration by wireless, it is important to accurately detect the occurrence of an abnormal event in the data and immediately inform a medical doctor of its detail. In this paper, we introduce a remote health care system, which is composed of a wireless vital sensor, multiple receivers and a triage engine installed in a desktop personal computer (PC). The middleware installed in the receiver, which was developed in C++, supports reliable data handling of vital data to the ethernet port. On the other hand, the human interface of the triage engine, which was developed in JAVA, shows graphics on his/her ECG data, 3D acceleration data, body surface temperature data and behavior status in the display of the desktop PC and sends an urgent e-mail containing the display data to a pre-registered medical doctor when it detects the occurrence of an abnormal event. In the triage engine, the lethal arrhythmia detection algorithm based on short time Fourier transform (STFT) analysis can achieve 100 % sensitivity and 99.99 % specificity, and the behavior recognition algorithm based on the combination of the nearest neighbor method and the Naive Bayes method can achieve more than 71 % classification accuracy.
机译:对于无处不在的医疗系统,这些系统通过无线方式连续监控人的生命体征,例如心电图(ECG),体表温度和三维(3D)加速,因此重要的是准确地检测人体中异常事件的发生数据,并立即告知医生其详细信息。在本文中,我们介绍了一种远程医疗保健系统,该系统由无线生命传感器,多个接收器和安装在台式个人计算机(PC)中的分类引擎组成。接收器中安装的中间件是用C ++开发的,它支持重要数据到以太网端口的可靠数据处理。另一方面,用JAVA开发的分类引擎的人机界面在台式PC显示器上显示其心电图数据,3D加速度数据,体表温度数据和行为状态的图形,并发送紧急信息。包含显示数据的电子邮件会在检测到异常事件时发送给预先注册的医生。在分类诊断引擎中,基于短时傅立叶变换(STFT)分析的致死性心律失常检测算法可以达到100%的灵敏度和99.99%的特异性,而基于最近邻方法和朴素贝叶斯方法的行为识别算法可以实现达到71%以上的分类精度。

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