ArticleSensors (Basel, Switzerland)2022
Wireless Capsule Endoscope Localization with Phase Detection Algorithm and Adaptive Body Model.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 9 citations in OpenAlex.
- Recent Advancements in Localization Technologies for Wireless Capsule Endoscopy: A Technical Review.Sensors (Basel, Switzerland) · 2025Review
- Location estimation of UWB-based wireless capsule endoscopy using TDoA in various gastrointestinal simulation models.PloS one · 2025Article
- Revealing the Boundaries of Selected Gastro-Intestinal (GI) Organs by Implementing CNNs in Endoscopic Capsule Images.Diagnostics (Basel, Switzerland) · 2023Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Wireless capsule endoscopes take and send photos of the human digestive tract, which are used for medical diagnosis. The capsule's location enables exact identification of the regions with lesions. This can be carried out by analyzing the parameters of the electromagnetic wave received from the capsule. Because the human body is a complex heterogeneous environment that impacts the propagation of wireless signals, determining the distance between the transmitter and the receiver based on the received power level is challenging. An enhanced approach of identifying the location of endoscope capsules using a wireless signal phase detection algorithm is presented in this paper. For each capsule position, this technique uses adaptive estimation of human body model permittivity. This approach was tested using computer simulations in Remcom XFdtd software using a numerical, heterogeneous human body model, as well as measurements with physical phantom. The type of transmitting antenna employed in the capsule also has a significant impact on the suggested localization method's accuracy. As a result, the helical antenna, which is smaller than the dipole, was chosen as the signal's source. For both the numerical and physical phantom studies, the proposed technique with adaptive body model enhances localization accuracy by roughly 30%.
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