DocumentCode :
1832262
Title :
Using heterogeneous sensory measurements in a compliant magnetic localization system for medical intervention
Author :
Zhenglong Sun ; Shaohui Foong ; Marechal, Luc ; Tee Hui Teo ; U-Xuan Tan ; Shabbir, Asim
Author_Institution :
Pillar of Eng. Product Dev., Singapore Univ. of Technol. & Design, Singapore, Singapore
fYear :
2015
fDate :
7-11 July 2015
Firstpage :
133
Lastpage :
138
Abstract :
In many medical intervention procedures, passive magnetic tracking technology has found favor in continuous localization of medical instruments and tools inside the human body. By utilizing a small permanent magnet as a passive source, it requires no dedicated power supply or wire connection into the body. Past researches usually adopt rigid structures to restrict the movement of sensors, as the precise positional information of the homogeneous magnetic sensors play an important role in the accuracy of traditional inverse optimization algorithms. In this paper, we investigate methods to enable the sensing system to be used for the nasogastric (NG) tube localization in a compliant setting, such that the device can conform around the patient for improved ergonomics and comfort. Such a system, which now contains additional sensors required to sense the active compliance, will contain a non-homogeneous sensor assembly producing heterogeneous sensory information. Two methods are proposed and evaluated: one is a modified inverse optimization method using a deformation model in series with the magnetic field model; the other is a direct forward Artificial Neural Network (ANN) method. The efficacy of both methods were evaluated and compared by numerical simulation and experiments. Advantages and disadvantages of both methods were discussed at the end.
Keywords :
biomedical equipment; biomedical measurement; magnetic field measurement; magnetic sensors; medical computing; neural nets; numerical analysis; optimisation; ANN; compliant magnetic localization system; deformation model; direct forward artificial neural network method; ergonomics; heterogeneous sensory measurements; human body; magnetic field model; medical instruments; medical intervention; medical tools; modified inverse optimization method; nasogastric tube localization; nonhomogeneous sensor assembly; numerical simulation; passive magnetic tracking technology; passive source; permanent magnet; Artificial neural networks; Deformable models; Magnetic sensors; Magnetometers; Optimization methods; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Intelligent Mechatronics (AIM), 2015 IEEE International Conference on
Conference_Location :
Busan
Type :
conf
DOI :
10.1109/AIM.2015.7222521
Filename :
7222521
Link To Document :
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