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Improved particle swarm optimization algorithm for android medical care IOT using modified parameters.

Wen-Tsai Sung¹, Yen-Chun Chiang

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

Journal of Medical Systems

|April 12, 2012

Summary

This study enhances remote healthcare using wireless sensor networks and an Android platform. An improved particle swarm optimization method boosts data fusion precision for real-time patient monitoring.

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Area of Science:

Computer Science
Biomedical Engineering
Healthcare Technology

Background:

Wireless Sensor Networks (WSNs) are crucial for remote healthcare.
Integrating Internet of Things (IoT) platforms enhances medical data accessibility.
Real-time physiological monitoring requires precise data fusion techniques.

Purpose of the Study:

To investigate the use of an Android platform for real-time remote identification in community healthcare.
To propose an improved Particle Swarm Optimization (PSO) algorithm for precise physiological multi-sensor data fusion.
To enhance the performance of data fusion within IoT systems for healthcare applications.

Main Methods:

Development of an improved PSO (IPSO) algorithm with optimized inertia weight and shrinkage factors.

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Implementation of the Android platform for multi-physiological signal processing and analysis.

Utilizing WSNs for signal transmission and internet connectivity for remote access to healthcare services.

Main Results:

The improved PSO algorithm demonstrated enhanced data fusion performance.
The Android-based system facilitated timely medical care analysis and services.
Effective real-time remote identification and monitoring were achieved.

Conclusions:

The proposed IPSO method significantly improves data fusion precision in IoT healthcare systems.
The Android platform effectively supports real-time physiological signal processing for community healthcare.
WSNs and IoT integration enable accessible and timely remote medical care services.