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

Authors：

 ZHULingyun , LILianjie , MENGChunyan

College of Computer Science and Engineering, Chongqing University of Technology, Chongqing 400054, China;

Corresponding author：

ZHULingyun, Email: zlycqu@163.com

Keywords：

multiple physiological parameters; cloud computing; Platform as a Service; Software as a Service; real-time analysis

DOI：

10.7507/1001-5515.20140261

Video：

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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 proposed 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 real-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 obvious 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 issues, 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.

Citation： ZHULingyun, LILianjie, MENGChunyan. Construction and Analysis of a Monitoring System with Remote Real-time Multiple Physiological Parameters Based on Cloud Computing. Journal of Biomedical Engineering, 2014, 31(6): 1377-1383. doi: 10.7507/1001-5515.20140261 Copy

1.	WU Jiyi, PING Lingdi, GE Xiaoping, et al. Cloud Storage as the infrastructure of Cloud Computing[C]//2010 International Conference on Intelligent Computing and Cognitive Informatics (ICICCI). Kuala Lumpur:2010:380-383.
2.	CUI Dong, WU Yunlong, ZHANG Qiang. Massive spatial data processing model based on cloud computing model[C]//2010 Third International Joint Conference on Computational Science and Optimization (CSO). Huangshan, Anhui:2010, 2:347-350.
3.	RAWAT D B, SHETTY S, RAZA K. Secure radio resource management in Cloud computing based cognitive radio networks[C]//201241st International Conference on Parallel Processing Workshops (ICPPW). Pittsburgh, PA:2012:288-295.
4.	HARRIGAN M, CUNNINGHAM P, COYLE L. Using storm to perform dynamic egocentric network motif analysis[C]//2012 IEEE 12th International Conference on Data Mining Workshops (ICDMW). Brussels:2012:408-415.
5.	LIU Yong, PIYAWONGWISAL P, HANDA S, et al. Going beyond citizen data collection with Mapster:A mobile+Cloud real-time citizen science experiment[C]//2011 IEEE Seventh International Conference on e-Science Workshops (eScienceW). Stockholm:2011:1-6.
6.	ZHANG Yuhua, ZHANG Jian, ZHANG Weihua. Discussion of intelligent cloud computing system[C]//2010 International Conference on Web Information Systems and Mining (WISM). Sanya:2010, 2:319-322.
7.	ZHANG Shufen, ZHANG Shuai, CHEN Xuebin, et al. Analysis and research of cloud computing system instance[C]//Second International Conference on Future Networks, 2010. ICFN'10. Sanya, Hainan:2010:88-92.
8.	WANG Yanzhi, LIN Xue, PEDRAM M. A nested two stage game-based optimization framework in mobile cloud computing system[C]//2013 IEEE 7th International Symposium on Service Oriented System Engineering (SOSE). Redwood City:2013:494-502.
9.	KANAGARAJ G, SUMATHI A C. Proposal of an open-source Cloud computing system for exchanging medical images of a Hospital Information System[C]//20113rd International Conference on Trendz in Information Sciences and Computing (TISC). Chennai:2011:144-149.
10.	NURMI D, WOLSKI R, GRZEGORCZYK, et al. The Eucalyptus open-source cloud-computing system[C]//9th IEEE/ACM International Symposium on Cluster Computing and the Grid, 2009. CCGRID'09. Shanghai:2009:124-131.
11.	SOBHY D, EL-SONBATY Y, ABOU ELNASR M. MedCloud:Healthcare cloud computing system[C]//2012 International Conferece for Internet Technology And Secured Transactions. London:2012:161-166.

1. WU Jiyi, PING Lingdi, GE Xiaoping, et al. Cloud Storage as the infrastructure of Cloud Computing[C]//2010 International Conference on Intelligent Computing and Cognitive Informatics (ICICCI). Kuala Lumpur:2010:380-383.
2. CUI Dong, WU Yunlong, ZHANG Qiang. Massive spatial data processing model based on cloud computing model[C]//2010 Third International Joint Conference on Computational Science and Optimization (CSO). Huangshan, Anhui:2010, 2:347-350.
3. RAWAT D B, SHETTY S, RAZA K. Secure radio resource management in Cloud computing based cognitive radio networks[C]//201241st International Conference on Parallel Processing Workshops (ICPPW). Pittsburgh, PA:2012:288-295.
4. HARRIGAN M, CUNNINGHAM P, COYLE L. Using storm to perform dynamic egocentric network motif analysis[C]//2012 IEEE 12th International Conference on Data Mining Workshops (ICDMW). Brussels:2012:408-415.
5. LIU Yong, PIYAWONGWISAL P, HANDA S, et al. Going beyond citizen data collection with Mapster:A mobile+Cloud real-time citizen science experiment[C]//2011 IEEE Seventh International Conference on e-Science Workshops (eScienceW). Stockholm:2011:1-6.
6. ZHANG Yuhua, ZHANG Jian, ZHANG Weihua. Discussion of intelligent cloud computing system[C]//2010 International Conference on Web Information Systems and Mining (WISM). Sanya:2010, 2:319-322.
7. ZHANG Shufen, ZHANG Shuai, CHEN Xuebin, et al. Analysis and research of cloud computing system instance[C]//Second International Conference on Future Networks, 2010. ICFN'10. Sanya, Hainan:2010:88-92.
8. WANG Yanzhi, LIN Xue, PEDRAM M. A nested two stage game-based optimization framework in mobile cloud computing system[C]//2013 IEEE 7th International Symposium on Service Oriented System Engineering (SOSE). Redwood City:2013:494-502.
9. KANAGARAJ G, SUMATHI A C. Proposal of an open-source Cloud computing system for exchanging medical images of a Hospital Information System[C]//20113rd International Conference on Trendz in Information Sciences and Computing (TISC). Chennai:2011:144-149.
10. NURMI D, WOLSKI R, GRZEGORCZYK, et al. The Eucalyptus open-source cloud-computing system[C]//9th IEEE/ACM International Symposium on Cluster Computing and the Grid, 2009. CCGRID'09. Shanghai:2009:124-131.
11. SOBHY D, EL-SONBATY Y, ABOU ELNASR M. MedCloud:Healthcare cloud computing system[C]//2012 International Conferece for Internet Technology And Secured Transactions. London:2012:161-166.

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