Analysis of the Localization Error for Capsule Endoscopy Applications at UWB Frequencies

Localization for Wireless Capsule Endoscopy (WCE) in the Ultra-Wideband frequency band is a very active field of investigation due to its potential advantages in future endoscopy applications. Received Signal Strength (RSS) based localization is commonly preferred due to its simplicity. Previous studies on Ultra-Wideband (UWB) RSS-based localization showed that the localization accuracy depends on the average ranging error related to the selected combination of receivers, which not always is the one experiencing the highest level of received power. In this paper the tendency of the localization error is further investigated through supplementary software simulations and previously conducted laboratory measurements. Two-dimensional (2D) and three-dimensional (3D) positioning are performed and the trend of the localization error compared in both cases. Results shows that the distribution of the selected path loss values, corresponding to the receivers used for localization, around the in-body position to estimate also affects the localization accuracy.This work was supported by the H2020:MSCA:ITN program for the “Wireless In-body Environment Communication- WiBEC” project under the grant agreement no. 675353. This work was also supported by the European Union’s H2020:MSCA:ITN program for the ”mmWave Communications in the Built Environments - WaveComBE” project under the grant agreement no. 766231.Barbi, M.; Pérez-Simbor, S.; Garcia-Pardo, C.; Cardona Marcet, N. (2019). Analysis of the Localization Error for Capsule Endoscopy Applications at UWB Frequencies. IEEE. https://doi.org/10.1109/ISMICT.2019.8743813

An adaptive localization technique for wireless capsule endoscopy

Wireless capsule endoscopy (WCE) is an emerging technique to enhance Gastroenterologists information about the patient\u27s gastrointestinal (G.I.) tract. Localization of capsule inside human body in this case is an active area of research. This can be thought of as a sub-domain of micro and bio-robotics fields. If capsule and micro-robot localization problem in human body is solved, then it may potentially lead to less invasive treatments for G.I. diseases and other micro-robot assisted medical procedures. Several approaches have been investigated by the researchers to estimate capsule location. The proposed solutions are mainly static and thus prone to the changes in the propagation medium. We propose an adaptive algorithm based on expectation maximization technique for capsule localization. The proposed algorithm adaptively updates the estimated location based on the received radio frequency (RF) signal measurements