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Improved Particle Swarm Optimization Algorithm for Android Medical Care IOT using Modified Parameters

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Abstract

This study examines wireless sensor network with real-time remote identification using the Android study of things (HCIOT) platform in community healthcare. An improved particle swarm optimization (PSO) method is proposed to efficiently enhance physiological multi-sensors data fusion measurement precision in the Internet of Things (IOT) system. Improved PSO (IPSO) includes: inertia weight factor design, shrinkage factor adjustment to allow improved PSO algorithm data fusion performance. The Android platform is employed to build multi-physiological signal processing and timely medical care of things analysis. Wireless sensor network signal transmission and Internet links allow community or family members to have timely medical care network services.

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References

  1. van den Bergh, F., and Engelbrecht, A. P., A cooperative approach to particle swarm optimization. IEEE Trans Evol Comput 8(3):225–239, 2004.

    Article  Google Scholar 

  2. P.K. Tripathi, S. Bandyopadhyay, S.K. Pal, Multi-objective particle swarm optimization with time variant inertia and acceleration coefficients, Information Sciences 177 (22) (2007) 5033–5049.

    Article  MathSciNet  MATH  Google Scholar 

  3. R. Mendes, J. Kennedy, J. Neves, The fully informed particle swarm: simpler, maybe better, IEEE Transactions on Evolutionary Computation 8 (3) (2004)204–210.

    Article  Google Scholar 

  4. C.C. Lai, C.H. Wu, M.C. Tsai, Feature selection using particle swarm optimization with application in spam filtering, International Journal of Innovative Computing, Information and Control 5 (2) (2009) 423–432.

    Google Scholar 

  5. N.K. Khalid, Z. Ibrahim, T.B. Kurniawan, M. Khalid, N.H. Sarmin, Function minimization in DNA sequence design based on continuous particle swarm optimization, ICIC Express Letters 3 (1) (2009) 27–32.

    Google Scholar 

  6. A. Carlisle, G. Dozier, An off-the-shelf PSO, in: Proceedings of the Workshop on Particle Swarm Optimization, Indianapolis, IN: Purdue School of Eng. Technol., IUPUI, April 2001.

  7. H. Wang, H. Li, Y. Liu, et al., Opposition-based particle swarm algorithm with Cauchy mutation, in: Proceedings of the 2007 IEEE Congress on Evolutionary Computation, September 2007, pp. 4750–4756.

  8. D. Bratton, T. Blackwell, A Simplified Recombinant PSO, Journal of Artificial Evolution and Applications, 2008.

  9. Richer, T. J., Blackwell, T. M, The Levy particle swarm, in: Proceedings of 2006 IEEE Congress on Evolutionary Computation, Vancouver, Canada, 2006, pp.808–815.

  10. Kennedy, J., In search of the essential particle swarm, in: Proceedings of 2006 IEEE Congress on Evolutionary Computation, Vancouver, BC Canada, July 2006, pp. 1694–1701

  11. A. Ratnaweera, S.K. Halgamuge, H.C. Watson, Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients, IEEE Transactions on Energy Conversion 8 (2004) 240–255.

    Google Scholar 

  12. Ni, Q. J., Xing, H. C., An improved Gaussian dynamic particle swarm optimization algorithm, in: Proceedings of 2006 International Conference on Computational Intelligence and Security, Guangzhou, PR China, November 2006, pp. 316–319

  13. Bratton, D., Kennedy, J., Defining a standard for particle swarm optimization, in: proceedings of 2007 IEEE Swarm Intelligence Symposium, 2007, pp.120–127.

  14. Sung, W.-T., Chung, H.-Y., Design an Innovative Localization Engines into WSN via ZigBee and SOC”, 2008 CACS International Automatic Control Conference,Nov.21 ~ 23 2008

  15. Sung, W.-T., Determine Global Energy Minimum Solution via Lyapunov Stability Theorem”, International Journal of Innovative Computing, Information and Control (IJICIC), Vol.5, No.7,pp.1-08-22.July 2009

  16. Higashi, N., Iba, H., Particle swarm optimization with Gaussian mutation, Proceedings of the IEEE Swarm Intelligence Symposium 2003, Indianapolis, Indiana, USA (2003) 72–79.

  17. X. Zhao, A perturbed particle swarm algorithm for numerical optimization, Applied Soft Computing 10 (1) (2010) 119–124.

    Article  Google Scholar 

  18. Y. Liu, Z. Qin, Z. Shi, J. Lu, Center particle swarm optimization, Neurocomputing 70 (4–6) (2007) 672–679.

    Article  Google Scholar 

  19. Shi, X., Lu, Y., Zhou, C., Lee, H., Lin, W., Liang, Y., Hybrid evolutionary algorithms based on PSO and GA, Proceedings of IEEE Congress on Evolutionary Computation 2003, Canbella, Australia (2003) 2393–2399.

  20. O. Montiel, O. Castillo, P. Melin, A.R. Daz, R. Seplveda, Human evolutionary model: a new approach to optimization, Information Sciences 177 (October) (2006) 2075–2098.

    Article  Google Scholar 

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Acknowledgment

This research was supported by the National Science Council of Taiwan under grant NSC 99-2220-E-167-001. The authors would like to thank the National Chin-Yi University of Technology, Taiwan for financially supporting this research.

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  1. Department of Electrical Engineering, National Chin-Yi University of Technology, Taiwan, No.57, Sec. 2, Zhongshan Rd., Taiping Dist., Taichung, 41170, Taiwan

    Wen-Tsai Sung & Yen-Chun Chiang

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  1. Wen-Tsai Sung
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Correspondence to Wen-Tsai Sung.

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Sung, WT., Chiang, YC. Improved Particle Swarm Optimization Algorithm for Android Medical Care IOT using Modified Parameters. J Med Syst 36, 3755–3763 (2012). https://doi.org/10.1007/s10916-012-9848-9

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  • DOI: https://doi.org/10.1007/s10916-012-9848-9

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