An Extended Kalman Filter-Based Data Fusion Method for Wireless Sensor Networks

Conference paper
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Abstract

For the requirement of physiological signal monitoring in the prevention of disease and in early diagnosis, the wireless sensor network plays an important role both for the physiological signal collection and the communication between the user and the remote medical service station. However, most of its energy is wasted during the transmission which shortens the network lifetime. This chapter focuses on the data fusion method with an extended Kalman filter by saving the waste of energy at the source. The expected result is to reduce the waste of energy during the transmission and lengthen the network lifetime. The simulation experiment demonstrates that the proposed method obtains the satisfactory result. It should have a good practical value in the application of physiological signal monitoring embedded in intelligent garment.

Keywords

Extended Kalman filter Wireless sensor network Data fusion Physiological signals 
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Notes

Acknowledgments

This work was supported by the National Nature Science Foundation of China (No. 60975059), the Specialized Research Fund for the Doctoral Program of Higher Education from Ministry of Education of China (No. 20090075110002), and the Project of the Shanghai Committee of Science and Technology (Nos. 10JC1400200, 10DZ0506500).

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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  1. 1.Engineering Research Center of Digitized Textile & Fashion TechnologyMinistry of Education, Donghua UniversityShanghaiChina
  2. 2.College of Information Sciences and TechnologyDonghua UniversityShanghaiChina

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