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Bayesian-based localization of wireless capsule endoscope using received signal strength.

Publication ,  Journal Article
Nadimi, ES; Blanes-Vidal, V; Tarokh, V; Johansen, PM
Published in: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
January 2014

In wireless body area sensor networking (WBASN) applications such as gastrointestinal (GI) tract monitoring using wireless video capsule endoscopy (WCE), the performance of out-of-body wireless link propagating through different body media (i.e. blood, fat, muscle and bone) is still under investigation. Most of the localization algorithms are vulnerable to the variations of path-loss coefficient resulting in unreliable location estimation. In this paper, we propose a novel robust probabilistic Bayesian-based approach using received-signal-strength (RSS) measurements that accounts for Rayleigh fading, variable path-loss exponent and uncertainty in location information received from the neighboring nodes and anchors. The results of this study showed that the localization root mean square error of our Bayesian-based method was 1.6 mm which was very close to the optimum Cramer-Rao lower bound (CRLB) and significantly smaller than that of other existing localization approaches (i.e. classical MDS (64.2mm), dwMDS (32.2mm), MLE (36.3mm) and POCS (2.3mm)).

Duke Scholars

Published In

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

DOI

EISSN

2694-0604

ISSN

2375-7477

Publication Date

January 2014

Volume

2014

Start / End Page

5988 / 5991

Related Subject Headings

  • Wireless Technology
  • Humans
  • Capsule Endoscopy
  • Bayes Theorem
  • Algorithms
 

Citation

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Nadimi, E. S., Blanes-Vidal, V., Tarokh, V., & Johansen, P. M. (2014). Bayesian-based localization of wireless capsule endoscope using received signal strength. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2014, 5988–5991. https://doi.org/10.1109/embc.2014.6944993
Nadimi, Esmaeil S., Victoria Blanes-Vidal, Vahid Tarokh, and Per Michael Johansen. “Bayesian-based localization of wireless capsule endoscope using received signal strength.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 2014 (January 2014): 5988–91. https://doi.org/10.1109/embc.2014.6944993.
Nadimi ES, Blanes-Vidal V, Tarokh V, Johansen PM. Bayesian-based localization of wireless capsule endoscope using received signal strength. Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE Engineering in Medicine and Biology Society Annual International Conference. 2014 Jan;2014:5988–91.
Nadimi, Esmaeil S., et al. “Bayesian-based localization of wireless capsule endoscope using received signal strength.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, vol. 2014, Jan. 2014, pp. 5988–91. Epmc, doi:10.1109/embc.2014.6944993.
Nadimi ES, Blanes-Vidal V, Tarokh V, Johansen PM. Bayesian-based localization of wireless capsule endoscope using received signal strength. Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE Engineering in Medicine and Biology Society Annual International Conference. 2014 Jan;2014:5988–5991.

Published In

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

DOI

EISSN

2694-0604

ISSN

2375-7477

Publication Date

January 2014

Volume

2014

Start / End Page

5988 / 5991

Related Subject Headings

  • Wireless Technology
  • Humans
  • Capsule Endoscopy
  • Bayes Theorem
  • Algorithms