This paper will introduce a simple locating system to track a stent when it is deployed into a human artery. The stent is proposed to achieve hemostasis for bleeding soldiers on the battlefield, where common surgical imaging equipment such as fluoroscopy systems are not available. In the application of interest, the stent must be guided to the right location to avoid serious complications. The most important features are its relative accuracy and the ease by which it may be quickly set up and used in a trauma situation. The locating approach in this paper utilizes a magnet outside the human body as the reference and a magnetometer that will be deployed inside the artery with the stent. The sensor can detect its location in a coordinate system centered with the reference magnet. In practice, the main challenge is that the locating accuracy will be deteriorated by external magnetic interference, rotation of the sensor, and random noise. These causes of error are addressed in the paper to improve the locating accuracy and repeatability under various conditions. Finally, the system’s locating performance will be validated in benchtop experiments, where the effects of the disturbance-eliminating procedures will be addressed.

This paper will introduce a location tracking system targeted on a stent when it is deployed into the human artery to achieve hemostasis. This system is proposed to be applied in emergent conditions such as treating injured soldiers on the battlefield where common surgical devices such as fluoroscopy systems are not available. The locating algorithm is based on both magnetic measurements and inertial measurements. The magnetic locating approach detects the sensor’s location in a coordinate system centered with the reference magnet source. The inertial locating approach integrates the linear acceleration and angular velocity measured by the sensor to obtain the angular and linear displacement during a time period. Measurements from all sensors are deeply fused to remove disturbances and noise that degrade the locating accuracy. The focus of this research is to identify all potential error-increasing factors and then provide solutions to correct them to enhance the location measurement reliability. Validation experiments for each improvement approach and the overall locating performance will be introduced.

This paper will introduce a radio frequency system to track the location of a stent designed to work inside a human artery. The stent is designed as a hemostasis aid tool for emergency situations where common surgical equipment, such as fluoroscopy systems, is not available, such as on the battlefield. In the application of interest, the stent must be guided to the correct location to achieve effective hemostasis and prevent complications. The locating approach uses the radiation pattern from the transmitter as the reference. When the transmitting frequency changes over a certain range, the measurement amplitude from a receiver depends on its relative location with respect to the transmitter. However, when the input frequency is unequal to the resonance frequency, the radiation pattern varies in an unpredictable way. To solve this problem, a deep learning model was trained to recognize variations in the radiation pattern and predict the receiver’s location as one of the classes in the reference grid. The deep learning model also reduces the impact of noise and disturbing signals, which effectively improves the system’s robustness.