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Electronics and Telecommunications Research Institute (한국전자통신연구원)
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A precise sensor fault detection technique using statistical techniques for wireless body area networks

  • Received : 2019.05.22
  • Accepted : 2020.07.10
  • Published : 2021.02.01
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Abstract

One of the major challenges in wireless body area networks (WBANs) is sensor fault detection. This paper reports a method for the precise identification of faulty sensors, which should help users identify true medical conditions and reduce the rate of false alarms, thereby improving the quality of services offered by WBANs. The proposed sensor fault detection (SFD) algorithm is based on Pearson correlation coefficients and simple statistical methods. The proposed method identifies strongly correlated parameters using Pearson correlation coefficients, and the proposed SFD algorithm detects faulty sensors. We validated the proposed SFD algorithm using two datasets from the Multiparameter Intelligent Monitoring in Intensive Care database and compared the results to those of existing methods. The time complexity of the proposed algorithm was also compared to that of existing methods. The proposed algorithm achieved high detection rates and low false alarm rates with accuracies of 97.23% and 93.99% for Dataset 1 and Dataset 2, respectively.

Keywords

Acknowledgement

This work was supported by the Department of Electronics & Information Technology (DeitY), which is a division of Ministry of Communications and IT of the Government of India, under the Visvesvaraya PhD scheme for Electronics & IT.

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