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Reliability modeling of anomaly detection algorithms for wireless body area networks

Zare Dehabadi, M. S ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1109/IranianCEE.2017.7985142
  3. Abstract:
  4. Research on Wireless Body Area Networks (WBAN) has witnessed constant advances in small and low power integrated electronic circuits as well as wireless communication schemes for remote monitoring of patients. As such, high reliability anomaly detection has emerged as an important characteristic especially in detection of system faults and abnormal physiological measurements. This work studies the reliability of WBANs by utilizing a Markov-based chain model and considering hardware failure rate, patient health status, and accuracy of anomaly detection algorithms containing Detection Rate (DR), False Positive Rate (FPR), and accuracy of transient fault correction measures. The proposed approach is shown as a powerful evaluation metric in analyzing the reliability and Mean Time to Failure (MTTF) in anomaly detection and specification for WBANs. © 2017 IEEE
  5. Keywords:
  6. Failure analysis ; Fault detection ; Low power electronics ; Markov processes ; Outages ; Reliability ; Remote patient monitoring ; Signal detection ; Wireless networks ; Wireless telecommunication systems ; Anomaly detection ; Anomaly-detection algorithms ; Integrated electronics ; Markov model ; Physiological measurement ; WBAN ; Wireless body area network ; Wireless communications ; Wireless local area networks (WLAN)
  7. Source: 2017 25th Iranian Conference on Electrical Engineering, ICEE 2017, 2 May 2017 through 4 May 2017 ; 2017 , Pages 70-75 ; 9781509059638 (ISBN)
  8. URL: https://ieeexplore.ieee.org/document/7985142