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Model-Aided real-time localization and parameter identification of a magnetic endoscopic capsule using extended kalman filter

Sadeghi Boroujeni, P ; Sharif University of Technology | 2021

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  1. Type of Document: Article
  2. DOI: 10.1109/JSEN.2021.3071432
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2021
  4. Abstract:
  5. Capsule endoscopy is a minimally invasive diagnostic technology for gastrointestinal diseases providing images from the human's digestion system. Developing a robust and real-time localization algorithm to determine the orientation and position of the endoscopic capsule is a crucial step toward medical diagnostics. In this paper, we propose a novel model-aided real-time localization approach to estimate the position and orientation of a magnetic endoscopic capsule swimming inside the stomach. In the proposed method, the governing equations of the motion of an ellipsoidal capsule inside the fluid, considering different hydrodynamics interactions, are derived. Then, based on the dynamic model, an Extended Kalman Filter (EKF) driven by the noisy measurements of the multiple magnetic sensors is developed. According to the simulations, the proposed method not only can accurately localize the endoscopic capsule but also can identify the unknown parameters of the dynamic model. The results confirm the superiority of our proposed method compared to the conventional localization technique in the presence of dynamic model uncertainties and corrupted sensor data. Experimental realization of the proposed technique proves the achievement of high accuracy in the trajectory estimation of the magnetic endoscopic capsule. © 2001-2012 IEEE
  6. Keywords:
  7. Dynamic models ; Endoscopy ; Equations of motion ; Magnetism ; Uncertainty analysis ; Diagnostic technologies ; Experimental realizations ; Gastrointestinal Disease ; Localization technique ; Medical diagnostics ; Position and orientations ; Real-time localization ; Trajectory estimation ; Extended Kalman filters
  8. Source: IEEE Sensors Journal ; Volume 21, Issue 12 , 2021 , Pages 13667-13675 ; 1530437X (ISSN)
  9. URL: https://ieeexplore.ieee.org/document/9395627