Development of a Real-Time Position Tracking System for Remote-Controlled Drug-Delivery Capsules Using Dual Magnetic Vector Detection

Yazarlar

  • Aviad Iddan
  • Azer Zamir
  • Sabah Moren
  • Mooshe Natanail

Anahtar Kelimeler:

Drug-Delivery Capsule, Position Tracking System, Gastrointestinal Tract, Magnetic Vector Detection, Quaternion Rotation Theory, Artificial Bee Colony Algorithm

Özet

This study presents a theoretical basis for the construction of a real-time position tracking system designed for remote-controlled drug-delivery capsules, allowing precise drug delivery to specific locations within the gastrointestinal tract. The tracking system utilizes dual magnetic vector detection, employing two distinct sets of magnetic field sensing devices. One set detects the externally excited alternating magnetic field with specific frequencies, while the other measures the geomagnetic field. A mathematical model is developed based on the Biot–Savart law, incorporating the earth's magnetic field and quaternion rotation theory to compensate for the dynamic spatial orientation of the capsule during traversal through the gastrointestinal tract. The proposed model employs an improved artificial bee colony algorithm to solve the inverse magnetic field problem. The algorithm incorporates chaotic sequencing to enhance initial solution diversity and implements a ranked selection strategy. To expedite convergence, the Levenberg-Marquardt algorithm is introduced in later stages. A prototype of the tracking system is constructed and verified, yielding a convergence rate of 100% with an average of 179 iterations. Prototype testing demonstrates that the dual magnetic vector detection method simplifies the solution of the inverse magnetic field problem, reduces tracking time for each data round, and enhances solution accuracy.

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Yayınlanmış

2023-02-15

Nasıl Atıf Yapılır

Iddan, A., Zamir , A., Moren , S., & Natanail , M. (2023). Development of a Real-Time Position Tracking System for Remote-Controlled Drug-Delivery Capsules Using Dual Magnetic Vector Detection. Journal of Data-Driven Engineering Systems, 6(1). Geliş tarihi gönderen https://esajournals.com/index.php/JDDES/article/view/22