Implantable Device Positioning based on Magnetic Field Detection using Genetic Algorithm in Body Area Biosensor Networks
Shigeaki Ogose1, *, Shintaro Mori2, Takahiro Sekii1
Identifiers and Pagination:Year: 2019
First Page: 11
Last Page: 20
Publisher ID: TOBEJ-13-11
Article History:Received Date: 5/11/2018
Revision Received Date: 18/1/2019
Acceptance Date: 20/01/2019
Electronic publication date: 31/01/2019
Collection year: 2019
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Minimally invasive medical care by the aid of Information Communication Technology (ICT) has attracted considerable attention. Sensor nodes including implantable devices within the bio-sensor network or Body Area Network (BAN) have been utilized to reduce the burden on patients. To control the operation of devices properly or collect vital data effectively, it is important to obtain accurate information on their position.
This paper provides an effective positioning method based on the detection of magnetic fields generated from implantable devices using the Genetic Algorithm (GA). After providing the principle of the proposed method, some laboratory test measurement results are given to confirm its effectiveness.
Magnetic field detection using multiple magnetic field sensors was achieved. From the results of multiple point measurements on the three-dimensional components of the magnetic field strength, the position of the target was obtained with a smaller error. Laboratory test measurement results are in good agreement with the theoretical values.
The proposed positioning method is an effective and an economical approach. It is also effective for detecting moving devices such as a capsule endoscope in a human body. With the aid of the GA, high-speed detection is obtained with a low calculation costs. The compressed sensing method reduces the number of measurement points.