Processing Chain for Localization of Magnetoelectric Sensors in Real Time

Abstract

The knowledge of the exact position and orientation of a sensor with respect to a source (distribution) is essential for the correct solution of inverse problems. Especially when measuring with magnetic field sensors, the positions and orientations of the sensors are not always fixed during measurements. In this study, we present a processing chain for the localization of magnetic field sensors in real time. This includes preprocessing steps, such as equalizing and matched filtering, an iterative localization approach, and postprocessing steps for smoothing the localization outcomes over time. We show the efficiency of this localization pipeline using an exchange bias magnetoelectric sensor. For the proof of principle, the potential of the proposed algorithm performing the localization in the two-dimensional space is investigated. Nevertheless, the algorithm can be easily extended to the three-dimensional space. Using the proposed pipeline, we achieve average localization errors between 1.12 cm and 6.90 cm in a localization area of size 50cm×50cm.

High Resolution Magnetoelectric Sensor and Low-frequency Measurement using Frequency up-conversion Technique

“…The resonance peak shift can be attributed to the influence of magnetic field on the Young's modulus, i.e. the delta-E effect [38][39][40]. Comparing Figure 2a and 2b, it is interesting to note that the at =2.5 Oe is dramatically enhanced by twice than that at zero field.…”

High-Resolution Magnetoelectric Sensor and Low-Frequency Measurement Using Frequency Up-Conversion Technique

“…However, when the AC field frequency was scanned under a DC bias field of 2.5 Oe, the peak frequency shifted from 60.041 kHz to 60.101 kHz ( Figure 2 b). The resonance peak shift can be attributed to the influence of the magnetic field on Young’s modulus, i.e., the delta-E effect [ 39 , 40 , 41 ]. When comparing Figure 2 a,b, it is interesting to note that at = 2.5 Oe was dramatically enhanced to twice that under the zero field.…”

Quantitative Evaluation for Magnetoelectric Sensor Systems in Biomagnetic Diagnostics

“…By exemplary, applying the introduced evaluation methods, it can be concluded that especially the electrically modulated ME sensor system has the potential to measure a magnetic heart signal, at least by applying advanced averaging techniques [ 52 ]. The other presented ME sensor type is better suited for applications where only a small frequency range is necessary, such as active magnetoelectric motion sensing [ 13 ] or ME sensor localization [ 12 ]. Nevertheless, cardiovascular medicine requires an unaveraged MCG morphology (QRS complex, P-wave, and T-wave) in the time domain, especially as cardiac arrhythmias manifest from beat to beat [ 7 , 54 ].…”

“…The exchange bias magnetoelectric sensor is used to demonstrate a typical resonant ME sensor system. This sensor type is especially applicable for detecting narrowband signals, for example, coil signals utilized in novel ME localization [ 12 ] and ME movement detection applications [ 13 ]. In contrast to this, the electrically modulated ME sensor is potentially better suited for broadband biomedical signals due to a much higher bandwidth.…”

“…In particular, the ongoing research of thin-film magnetoelectric (ME) sensors enables new areas of signal acquisition in medicine since they do not require cryogenic cooling or thermal heating for sensor operation [ 9 , 10 , 11 ]. These sensors are easy to use, provide unprecedented flexibility and are operational in the presence of interference fields such as the Earth’s magnetic field [ 12 , 13 ]. Magnetic recording techniques have the potential to support and replace traditional electrode-based (electrical) methods by default [ 14 ].…”