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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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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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  2. Yen-Chun Chiang
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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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