Design and development of spatial data acquisition system for magnetic endocapsule location tracking applications

Abstract Direct data-based magnetic location tracking is feasible because the magnetic sensor measurement patterns are functions of the magnetic endocapsule's spatial coordinates. These tracking problems can be effectively addressed through machine/deep learning approaches, which can learn and interpret these patterns in the measurement data. The machine/deep learning approaches require extensive data. `Extensive data' refers to magnetic sensor measurements collected by systematically altering the magnetic endocapsule's spatial coordinates with finer step sizes over a given region of interest. This study developed a spatial data acquisition system to collect sufficient magnetic endocapsule spatial coordinate-driven magnetic sensor measurement data. The system includes a magnetic sensor array, a data processing unit, a motorised spatial frame, and magnet holders. The magnetic sensor array consists of sixteen MLX90393 magnetic sensors. The magnetic sensors are integrated with TCA9548A multiplexers and an Arduino Mega microcontroller via the I2C communication protocol to control, process, and communicate the data with the computer. To house the magnetic sensors, a frame of dimensions 200 mm× 200 mm with sixteen slots was designed in AutoCAD 2025 software and 3D printed. A spatial frame and magnet holders were also designed in AutoCAD 2025, 3D printed, and combined with a linear actuator to effectively adjust the magnetic endocapsule's spatial coordinates. The spatial frame has dimensions of 200 mm× 200 mm with 49 slots, and the six magnet holders are designed for 24 angular variations. Arduino IDE 2.3.3 and MATLAB 2024b software were used to programme and collect data from the spatial data acquisition system. Two hundred magnetic sensor data samples, collected at intervals of 1.5 seconds, were used to compute offsets. After offset correction, magnetic endocapsule spatial coordinate-driven measurement data were collected at four spatial points to demonstrate the spatial data acquisition system. The measurement data pattern highlights the impact of the magnetic endocapsule's spatial coordinates on the magnetic sensor measurements.

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Publication Details

Journal
Journal of Instrumentation
Published
2025-05-01
DOI
https://doi.org/10.1088/1748-0221/20/05/p05003
Primary Topic
Characterization and Applications of Magnetic Nanoparticles
Type
article
Field-Weighted Citation Impact
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article

Design and development of spatial data acquisition system for magnetic endocapsule location tracking applications

Sujatha Narayanan Unni, Brahmaiah Nallabothula
Journal of Instrumentation
Characterization and Applications of Magnetic Nanoparticles
article

Design and development of spatial data acquisition system for magnetic endocapsule location tracking applications

Sujatha Narayanan Unni, Brahmaiah Nallabothula
article en

Abstract

Abstract Direct data-based magnetic location tracking is feasible because the magnetic sensor measurement patterns are functions of the magnetic endocapsule's spatial coordinates. These tracking problems can be effectively addressed through machine/deep learning approaches, which can learn and interpret these patterns in the measurement data. The machine/deep learning approaches require extensive data. `Extensive data' refers to magnetic sensor measurements collected by systematically altering the magnetic endocapsule's spatial coordinates with finer step sizes over a given region of interest. This study developed a spatial data acquisition system to collect sufficient magnetic endocapsule spatial coordinate-driven magnetic sensor measurement data. The system includes a magnetic sensor array, a data processing unit, a motorised spatial frame, and magnet holders. The magnetic sensor array consists of sixteen MLX90393 magnetic sensors. The magnetic sensors are integrated with TCA9548A multiplexers and an Arduino Mega microcontroller via the I2C communication protocol to control, process, and communicate the data with the computer. To house the magnetic sensors, a frame of dimensions 200 mm× 200 mm with sixteen slots was designed in AutoCAD 2025 software and 3D printed. A spatial frame and magnet holders were also designed in AutoCAD 2025, 3D printed, and combined with a linear actuator to effectively adjust the magnetic endocapsule's spatial coordinates. The spatial frame has dimensions of 200 mm× 200 mm with 49 slots, and the six magnet holders are designed for 24 angular variations. Arduino IDE 2.3.3 and MATLAB 2024b software were used to programme and collect data from the spatial data acquisition system. Two hundred magnetic sensor data samples, collected at intervals of 1.5 seconds, were used to compute offsets. After offset correction, magnetic endocapsule spatial coordinate-driven measurement data were collected at four spatial points to demonstrate the spatial data acquisition system. The measurement data pattern highlights the impact of the magnetic endocapsule's spatial coordinates on the magnetic sensor measurements.

Journal of InstrumentationVol. 20(05)
Indian Institute of Technology Madras (IN)
Openalex Percentile: Top 91%
Characterization and Applications of Magnetic Nanoparticles
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