远程多生理参数实时监测云服务平台的构建与分析  

Construction and Analysis of a Monitoring System with Remote Real-time Multiple Physiological Parameters Based on Cloud Computing

作　　者：朱凌云[1] 李连杰[1] 孟春艳[1] 

机构地区：[1]重庆理工大学计算机科学与工程学院,重庆400054

出　　处：《生物医学工程学杂志》2014年第6期1377-1383,共7页Journal of Biomedical Engineering

基　　金：重庆市自然科学基金资助项目(cstc2011jjA1026);重庆市教委科学技术研究资助项目(KJ110813)

摘　　要：针对现有的多生理参数实时监测系统中,由于终端用户数量增加和上传数据加大所导致的服务后台数据一致性无法保证、生理参数存储与处理能力不足、实时性较差以及数据利用率低等问题,提出了基于云计算的多生理参数监测后台数据集群存储与并行处理新模式。通过对监测系统云平台的基础设施即服务层资源虚拟化、平台即服务层实时计算平台的构建、软件即服务层数据流的接收与分析,以及多生理参数流传输通路瓶颈问题等方面的研究,实现了生理信息大数据量的实时传输、存储与集群处理,并可利用批处理对患者的历史数据实现纵向分析。仿真测试结果表明:基于云平台的远程多生理参数监测系统在集群数据处理时间和负载平衡方面,比传统的服务器模式具有明显的优势。该平台解决了传统远程医疗服务中数据周转时间长、实时分析算法误差较大和架构拓展困难等问题,为多生理参数无线监测以专业的"穿戴式无线传感+移动终端无线传输+云计算服务"模式走向家庭健康监测提供了技术支撑。There have been problems in the existing multiple physiological parameter real-time monitoring system, such as insufficient server capacity for physiological data storage and analysis so that data consistency can not be guaranteed, poor performance in real-time, and other issues caused by the growing scale of data. We therefore pro- posed a new solution which was with multiple physiological parameters and could calculate clustered background data storage and processing based on cloud computing. Through our studies, a batch processing for longitudinal analysis of patients＇ historical data was introduced. The process included the resource virtualization of IaaS layer for cloud platform, the construction of real-time computing platform of PaaS layer, the reception and analysis of data stream of SaaS layer, and the bottleneck problem of multi-parameter data transmission, etc. The results were to achieve in re- al-time physiological information transmission, storage and analysis of a large amount of data. The simulation test results showed that the remote multiple physiological parameter monitoring system based on cloud platform had obvi- ous advantages in processing time and load balancing over the traditional server model. This architecture solved the problems including long turnaround time, poor performance of real-time analysis, lack of extensibility and other is- sues, which exist in the traditional remote medical services. Technical support was provided in order to facilitate a ＂wearable wireless sensor plus mobile wireless transmission plus cloud computing service＂ mode moving towards home health monitoring for multiple physiological parameter wireless monitoring.

关 键 词：多生理参数 云计算 平台即服务 软件即服务 实时分析 

分 类 号：TP393.09[自动化与计算机技术—计算机应用技术]