An IoT-Based early Warning System for Patients with Heart Disease

Xing Zhe Piao; Hai Yin Piao; Song Yang; Yu Shan Xue

doi:10.4028/www.scientific.net/AMM.321-324.2348

Paper Titles

Construction Scheme & Application of IaaS-Based Shared Server Farm
p.2331

Comparison of Déjà Vu X and Trados 7.0
p.2335

An Agent-Based Approach for Multi Performance Optimization in Grid Computing
p.2339

Transmission of Timing Sensitive Information Using Photonic Services
p.2343

An IoT-Based early Warning System for Patients with Heart Disease
p.2348

The Application Research on Improved Divide-and-Conquer Mixed Selection Algorithm for Arrangement of Examination Seat
p.2352

Research of Decision Support System Based on Knowledge Management and Web Technology
p.2357

Establishment Research on Industry Technology Roadmapping for Technology Innovation
p.2363

System Target Damage Assessment Based on FAHP
p.2367

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 321-324An IoT-Based early Warning System for Patients...

An IoT-Based early Warning System for Patients with Heart Disease

Abstract:

An IoT-based early warning system was proposed for patients with heart disease, and presented a two-stage early warning approach. Neural network was introduced to clinical data analysis. Monitoring data collected by IoT was taken as the feedback to neural network to personalize the prediction model in accordance with the individual physical difference. Based on the two-stage prediction method, the alarm is given according to several rules, aim to warn the patients with potential heart attack ahead of time, and accurately by this system.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 321-324)

Pages:

2348-2351

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.321-324.2348

Citation:

Cite this paper

Online since:

June 2013

Authors:

Xing Zhe Piao, Hai Yin Piao, Song Yang, Yu Shan Xue

Keywords:

Artificial Neural Network (ANN), Body Sensor Network, Heart Disease

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Benny, L., Thiemjarus, S., King, R. and G.Z. Yang, "Body Sensor Network – A Wireless Sensor Platform for Pervasive Healthcare Monitoring", In the Proceedings of the 3rd International Conference on Pervasive Computing.pp.77-80, May 2005.

Google Scholar

[2] Rocha, T., Paredes, S., Carvalho, P. and J. Henriques, "Prediction of Acute Hypotensive Episodes by Means of Neural Network Multi-models", Computers in Biology and Medicine, 2011. 41(10): pp.881-890.

DOI: 10.1016/j.compbiomed.2011.07.006

Google Scholar

[3] Kao, H., Kuo, Y.H., Chien, Y.K., Hung, Y.H., Chen, L.S. and C.K. Liu, "Evolving the Business Model to Improve Care Performance for Remote Patient Management: A Case Study", In proceedings of the 45th Hawaii International Conference on System Sciences, HICSS 2012, Maui, HI, 2012.

DOI: 10.1109/hicss.2012.260

Google Scholar

[4] Coye, M.J., Haselkorn, A. and DeMello, S., "Remote Patient Management: Technology-enabled Innovation and Evolving Business Models for Chronic Disease Care", Health Affairs, 2009, 28(1): pp.126-135.

DOI: 10.1377/hlthaff.28.1.126

Google Scholar

[5] Sampalli, T., Shepherd, M. and Duffy, J., "A Patient Profile Ontology in the Heterogeneous Domain of Complex and Chronic Health Conditions", In proceedings of the 44th Hawaii International Conference on System Science (HICSS), Kauai, HI, 2011.

DOI: 10.1109/hicss.2011.21

Google Scholar