Active Magnetoelectric Motion Sensing: Examining Performance Metrics with an Experimental Setup

Magnetoelectric (ME) sensors with a form factor of a few millimeters offer a comparatively low magnetic noise density of a few pT/Hz−−−√ in a narrow frequency band near the first bending mode. While a high resonance frequency (kHz range) and limited bandwidth present a challenge to biomagnetic measurements, they can potentially be exploited in indirect sensing of non-magnetic quantities, where artificial magnetic sources are applicable. In this paper, we present the novel concept of an active magnetic motion sensing system optimized for ME sensors. Based on the signal chain, we investigated and quantified key drivers of the signal-to-noise ratio (SNR), which is closely related to sensor noise and bandwidth. These considerations were demonstrated by corresponding measurements in a simplified one-dimensional motion setup. Accordingly, we introduced a customized filter structure that enables a flexible bandwidth selection as well as a frequency-based separation of multiple artificial sources. Both design goals target the prospective application of ME sensors in medical movement analysis, where a multitude of distributed sensors and sources might be applied

Processing Chain for Localization of Magnetoelectric Sensors in Real Time

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

Exchange biased delta-E effect enables the detection of low frequency pT magnetic fields with simultaneous localization

Delta-E effect sensors are based on magnetoelectric resonators that detune in a magnetic field due to the delta-E effect of the magnetostrictive material. In recent years, such sensors have shown the potential to detect small amplitude and low-frequency magnetic fields. Yet, they all require external magnetic bias fields for optimal operation, which is highly detrimental to their application. Here, we solve this problem by combining the delta-E effect with exchange biased multilayers and operate the resonator in a low-loss torsion mode. It is comprehensively analyzed experimentally and theoretically using various kinds of models. Due to the exchange bias, no external magnetic bias fields are required, but still low detection limits down to [Formula: see text] at 25 Hz are achieved. The potential of this concept is demonstrated with a new operating scheme that permits simultaneous measurement and localization, which is especially desirable for typical biomedical inverse solution problems. The sensor is localized with a minimum spatial resolution of 1 cm while measuring a low-frequency magnetic test signal that can be well reconstructed. Overall, we demonstrate that this class of magnetic field sensors is a significant step towards first biomedical applications and compact large number sensor arrays

Magnetoelectric Sensor Systems and Applications

In the field of magnetic sensing, a wide variety of different magnetometer and gradiometer sensor types, as well as the corresponding read-out concepts, are available. Well-established sensor concepts such as Hall sensors and magnetoresistive sensors based on giant magnetoresistances (and many more) have been researched for decades. The development of these types of sensors has reached maturity in many aspects (e.g., performance metrics, reliability, and physical understanding), and these types of sensors are established in a large variety of industrial applications. Magnetic sensors based on the magnetoelectric effect are a relatively new type of magnetic sensor. The potential of magnetoelectric sensors has not yet been fully investigated. Especially in biomedical applications, magnetoelectric sensors show several advantages compared to other concepts for their ability, for example, to operate in magnetically unshielded environments and the absence of required cooling or heating systems. In recent years, research has focused on understanding the different aspects influencing the performance of magnetoelectric sensors. At Kiel University, Germany, the Collaborative Research Center 1261 “Magnetoelectric Sensors: From Composite Materials to Biomagnetic Diagnostics”, funded by the German Research Foundation, has dedicated its work to establishing a fundamental understanding of magnetoelectric sensors and their performance parameters, pushing the performance of magnetoelectric sensors to the limits and establishing full magnetoelectric sensor systems in biological and clinical practice

ΔE-Effect Magnetic Field Sensors

Many conceivable biomedical and diagnostic applications require the detection of small-amplitude and low-frequency magnetic fields. Against this background, a magnetometer concept is investigated in this work based on the magnetoelastic ΔE effect. The ΔE effect causes the resonance frequency of a magnetoelastic resonator to detune in the presence of a magnetic field, which can be read-out electrically with an additional piezoelectric phase. Various microelectromechanical resonators are experimentally analyzed in terms of the ΔE effect and signal-and-noise response. This response is highly complex because of the anisotropic and nonlinear coupled magnetic, mechanical, and electrical properties. Models are developed and extended where necessary to gain insights into the potentials and limits accompanying sensor design and operating parameters. Beyond the material and geometry parameters, we analyze the effect of different resonance modes, spatial property variations, and operating frequencies on sensitivity. Although a large ΔE effect is confirmed in the shear modulus, the sensitivity of classical cantilever resonators does not benefit from this effect. An approach utilizing surface acoustic shear-waves provides a solution and can detect small signals over a large bandwidth. Comprehensive analyses of the quality factor and piezoelectric material parameters indicate methods to increase sensitivity and signal-to-noise ratio significantly. First exchange-biased ΔE-effect sensors pave the way for compact setups and arrays with a large number of sensor elements. With an extended signal-and-noise model, specific requirements are identified that could improve the signal-to-noise ratio. The insights gained lead to a new concept that can circumvent previous limitations. With the results and models, important contributions are made to the understanding and development of ΔE-effect sensors with prospects for improvements in the future