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Design and In-Vivo Validation of Clinically Wireless Localization System for Magnetic Robots: A Reconfigurable Sensor Array Approach

Yichong Sun, Yehui Li, Yisen Huang, Xuyang Ren, Wai Shing Chan, Hon Chi Yip, Philip Wai Yan Chiu, Zheng Li

Year
2025
Citations
2

Abstract

In this article, we propose a novel wireless localization system to locate magnetic robots or devices for clinical applications. The primary challenge here is to precisely locate the robots in a human body workspace while confirming systematic feasibility and reliability in clinical settings. Precisely, by co-developing a cable-driven mechanism and flexible magnetic sensor printed circuits, a sensor array scheme with active reconfigurability is presented, which has regard for both sides about accuracy and practical viability. The sensor array configuration can be adjusted to accommodate different patient's body. Moreover, key technical issues, such as the configuration modeling approach of the cable-driven backbones and the sensors' coordinate transformation paradigm, are analyzed for the further construction of the magnetic modeling and the localization algorithm. Afterward, the effectiveness of the developed system and methods are validated in the robotic arm platform and, notably, in-vivo animal environment. Results reveal that the localization accuracy can achieve 0.0088 m and 1.5081<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula> in static cases, and 0.0126∼0.0165 m and 3.4655°∼4.3316° with promotions of 42.73%∼55.65% and 29.80%∼63.54% in dynamic cases compared to the planar sensor arrays. Besides, in-vivo animal tests indicate the applicability of the proposed system, which realizes repetition accuracies with mm-level by 0.0059 and 0.0054 m, and localization accuracies by 0.00685 and 0.0419 m (two moving processes in the animal esophagus). These results verify the feasibility and superiority of the proposed system, holding practical significance in addressing the challenge associated with magnetic localization tasks toward clinical scenarios.

Keywords

RobotWirelessIn vivoComputer scienceEmbedded systemArtificial intelligenceBiologyTelecommunications

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