Abstract
In aerospace, stress and excessive workload could lead to astronauts in the physical, mental or psychological tension or disorder. In order to keep the safety of the astronauts, sensor network has been deployed in space craft for monitoring the physiological data. Such data can also be used for scientific research. In this paper, we discuss the background and challenges of mining the health condition data of astronauts, and propose a data processing platform to monitor the changing of astronauts’ health conditions. We also briefly introduce the data processing methods we designed. In this paper, all the data processing units are implemented as portable services, and an interaction communication bus is introduced, which can support heterogeneous platforms simultaneously. We conduct the experiment on gathered data to verify the correctness of our processing solutions. The experimental results on real dataset indicated that our solutions are meaningful, and our methods are efficient in practice.
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References
Lo, B.P.L., Thiemjarus, S., King, R., Yang, G.-z.: Body Sensor Network - A Wireless Sensor Platform for Pervasive Healthcare Monitoring. In: 3rd International conference on Pervasive Computing, pp. 77–80 (2005)
Fayyad, U., Piatetsky-Shapiro, G., Smyth, P., et al.: Knowledge Discovery and Data Mining: Towards a Unifying Framework. In: Proc. 2nd Int. Conf. on Knowledge Discovery and Data Mining, Portland, OR, pp. 82–88 (1996)
Fayyad, U., Piatetsky-Shapiro, G., Smyth, P.: The KDD Process for Extracting Useful Knowledge from Volumes of Data Communications of the ACM. Magazine Communications of the ACM 39(11), 27–34 (1996)
Famili, A., Shen, W.M., Weber, R., Simoudis, E.: Data Pre-processing and Intelligent Data Analysis. International Journal on Intelligent Data Analysis 1(1), 499–502 (2010)
Kon, F., Costa, F., Blair, G., Campbell, R.H.: The Case for Reflective Middleware. Communications of the ACM 45(6), 33–38 (2002)
Schantz, R.E., Loyall, J.P., Rodrigues, C., Schmidt, D.C., Krishnamurthy, Y., Pyarali, I.: Flexible and Adaptive Qos Control for Distributed Real-Time and Embedded Middleware. In: ACM/IFIP/USENIX 2003 International Conference on Middleware, pp. 374–393 (2003)
Schmidt, D.C.: Middleware for Real-Time and Embedded Systems. Communications of the ACM 45(6), 43–48 (2002)
Vinoski, S.: CORBA: Integrating Diverse Applications Within Distributed Heterogeneous. IEEE Communications Magazine 35(2), 46–55 (1997)
Lenzerini, M.: Data Integration: A Theoretical Perspective. In: Proceedings of The Twenty-First ACM SIGMOD-SIGACT-SIGART Symposium On Principles Of Database Systems, pp. 233–246 (2002)
Bolstad, B.M., Irizarry, R.A., Astrand, M., Speed, T.P.: A Comparison of Normalization Methods for High Density Oligonucleotide Array Data Based on Variance and Bias Bioinformatics, vol. 19(2), pp. 185–193. Oxford University Press, Oxford (2003)
Chang, J., Remmen, H.V., Ward, W.F., Regnier, F.E., Richardson, A., Cornell, J.: Processing Of Data Generated By 2-Dimensional Gel Electrophoresis For Statistical Analysis: Missing Data, Normalization, And Statistics. J. Proteome Res. 3(6), 1210–1218 (2004)
Labrie, K., Allen, C., Hirst, P., Holt, J., Allen, R., Dement, K.: The Gemini Recipe System: A Dynamic Workflow for Automated Data Reduction. In: Proceedings of SPIE - The International Society for Optical Engineering, vol. 7737, pp. 7737–7738 (2010)
Griffin, M.P., Moorman, J.R.: Toward The Early Diagnosis Of Neonatal Sepsis and Sepsis-Like Inllness Using Noval Heart Rate Analysis. Pediatrics 107(1), 97–104 (2001)
Yan, S.: Application Research of Data Mining Technology to Teaching Evaluation of Higher Education. Journal of Guizhou University of Technology 10(5), 164–166 (2008)
Ouyang, J.Q., Ding, B., Wang, H.M., Shi, D.X.: Component Based Context Model. In: The Ninth International Conference on Web-Age Information Management, pp. 569–574 (2008)
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Han, Y., Zhao, Y., Jia, Y., Li, D. (2011). Mining the Astronauts’ Health Condition Data: Challenges, Techniques and a Platform. In: Yu, Y., Yu, Z., Zhao, J. (eds) Computer Science for Environmental Engineering and EcoInformatics. CSEEE 2011. Communications in Computer and Information Science, vol 159. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22691-5_43
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DOI: https://doi.org/10.1007/978-3-642-22691-5_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22690-8
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