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Cloud-based dynamic electrocardiogram monitoring and analysis system

机译:基于云的动态心电图监测分析系统

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Dynamic electrocardiogram (ECG) monitoring is significantly superior to conventional static ECG inspection in application scope and clinical study. With the increasing number of guardianship and healthcare category, health surveillance platform will produce a large number of monitoring data. The traditional monitoring technology has been unable to effectively resolve the management and analysis of those generated large data. To solve these problems, this paper proposed a cloud-based dynamic ECG monitoring and analysis system. First of all, the use of acquisition sensors for acquisition, direct access to dynamic ECG signal and acceleration data; Secondly, these sensors send the gathered data to the terminal by Bluetooth for display and further process; then, the terminal will send the generated data to Cloud Storage platform for storage. The Cloud platform utilize generic hierarchical Service Modeling Framework and Cloud Storage which is consist of relational database storage (MySQL) and distributed file system storage (HDFS). Finally, utilizing MapReduce computing framework for data mining, medical statistics and similarity correlation analysis of diseases can help expert to make a health improvement plan and guide users to manage their own health. The proposed system can also allow users to better understand their own physical condition and achieve the purpose of disease monitoring and early warning.
机译:在应用范围和临床研究中,动态心电图(ECG)监测显着优于传统的静态心电图检查。随着监护和医疗类别的增加,健康监视平台将产生大量的监视数据。传统的监控技术一直无法有效地解决那些生成的大数据的管理和分析。为了解决这些问题,本文提出了一种基于云的动态心电图监测与分析系统。首先,使用采集传感器进行采集,直接获取动态心电信号和加速度数据;其次,这些传感器通过蓝牙将收集到的数据发送到终端进行显示和进一步处理。然后,终端会将生成的数据发送到Cloud Storage平台进行存储。云平台利用通用的分层服务建模框架和云存储,它由关系数据库存储(MySQL)和分布式文件系统存储(HDFS)组成。最后,利用MapReduce计算框架进行数据挖掘,医学统计和疾病相似性相关分析,可以帮助专家制定健康改善计划并指导用户管理自己的健康。提出的系统还可以使用户更好地了解自己的身体状况,并达到疾病监测和预警的目的。

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