一种云辅助的移动心电监测系统  

Research on Cloud-Assisted Mobile ECG Monitoring System

作　　者：胡建强[1] 曾智勇[2] 朱顺痣[1] 吴克寿[1] 

机构地区：[1]厦门理工学院计算机与信息工程学院,福建厦门361024 [2]福建师范大学软件学院,福建福州350108

出　　处：《厦门理工学院学报》2016年第3期61-65,共5页Journal of Xiamen University of Technology

基　　金：国家自然科学基金项目(61373147,61502405);厦门市高校科技创新项目(3502Z20143031,3502Z20133033);厦门理工学院人才引进项目(YKJ13004R)

摘　　要：连续监测心电对发现心血管疾病和判断人体健康状况具有重要意义.新一代心电监测系统能提高便携性、降低功耗和成本,但在心电数据提取、存储容量等方面还存在局限性.为此,提出一种云辅助的移动心电监测系统,利用智能手机接收心电数字信号,借助云平台(例如BAT云、厦门市健康云)实现ECG数据存储.该系统采用基于平均绝对差分阈值的心电波形提取算法、基于小波包分解的智能报警模型和基于HL7-a ECG标准的数据交换模型,提升心电数据提取质量、报警能力和数据存储能力.系统原型能支持5种心电病变类型判别,智能报警以及心电数据云管理,从而有利于降低心血管疾病的潜在威胁.Continuous monitoring of ECG signals is of great significance for detection of chronic cardiovascular disease and assessment of health status. The new generation ECG monitoring system has good portability,lowpower consumption and low-cost, but its data extraction and storage capacity has room to improve. A cloudassisted mobile ECG monitoring system is therefore designed using smart phones to receive ECG signals and cloud platforms（ such as BAT Cloud platform,Xiamen Municipal Health Cloud） to store ECG data. It adopts ECG extraction algorithm based on average-absolute difference threshold, intelligent alarm model based on wavelet packet decomposition and ECG data exchange model based on HL7-a ECG standard,to enhance quality of ECG data extraction,alarm accuracy and data storage capacity. Finally,a prototype system is implemented that supports the identification of five types of lesions, intelligent alarm and cloud ECG data management,which helps reduce the potential threat of cardiovascular diseases.

关 键 词：移动心电监测 心电波形 提取算法 智能报警模型 HL7-aECG标准 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置]