title: Bayesian-based localization of wireless capsule endoscope using received signal strength.
abstract: 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)).
authors.forename: Esmaeil S
authors.initials: ES
authors.lastname: Nadimi
authors.forename: Victoria
authors.initials: V
authors.lastname: Blanes-Vidal
authors.forename: Vahid
authors.initials: V
authors.lastname: Tarokh
authors.forename: Per Michael
authors.initials: PM
authors.lastname: Johansen
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D053704:Capsule Endoscopy / Q000295:instrumentation / Q000379:methods*; D006801:Humans; D059015:Wireless Technology