Logo image
Design optimization of the sensor spatial arrangement in a direct magnetic field-based localization system for medical applications
Conference proceeding

Design optimization of the sensor spatial arrangement in a direct magnetic field-based localization system for medical applications

Luc Marechal, Shaohui Foong, Zhenglong Sun and Kristin L Wood
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Conference Proceedings, p.897
01/08/2015

Abstract

Localization Neural networks Optimization Sensors
Conference Title: 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Conference Start Date: 2015, Aug. 25 Conference End Date: 2015, Aug. 29 Conference Location: Milan, Italy Motivated by the need for developing a neuronavigation system to improve efficacy of intracranial surgical procedures, a localization system using passive magnetic fields for real-time monitoring of the insertion process of an external ventricular drain (EVD) catheter is conceived and developed. This system operates on the principle of measuring the static magnetic field of a magnetic marker using an array of magnetic sensors. An artificial neural network (ANN) is directly used for solving the inverse problem of magnetic dipole localization for improved efficiency and precision. As the accuracy of localization system is highly dependent on the sensor spatial location, an optimization framework, based on understanding and classification of experimental sensor characteristics as well as prior knowledge of the general trajectory of the localization pathway, for design of such sensing assemblies is described and investigated in this paper. Both optimized and non-optimized sensor configurations were experimentally evaluated and results show superior performance from the optimized configuration. While the approach presented here utilizes ventriculostomy as an illustrative platform, it can be extended to other medical applications that require localization inside the body.

Metrics

1 Record Views

Details

Logo image