Performance Analysis of Resonantly Driven Piezoelectric Sensors Operating in Amplitude Mode and Phase Mode.

Piezoelectric layers coupled to micromechanical resonators serve as the basis for sensors to detect a variety of different physical quantities. In contrast to passive sensors, actively operated sensors exploit a detuning of the resonance frequency caused by the signal to be measured. To detect the time-varying resonance frequency, the piezoelectric resonator is resonantly excited by a voltage, with this signal being modulated in both amplitude and phase by the signal to be measured. At the same time, the sensor signal is impaired by amplitude noise and phase noise caused by sensor-intrinsic noise sources that limit the reachable detectivities. This leads to the question of the optimum excitation frequency and the optimum readout type for such sensors. In this article, based on the fundamental properties of micromechanical resonators, a detailed analysis of the performance of piezoelectric resonators in amplitude mode and phase mode is presented. In particular, the sensitivities, the noise behavior, and the resulting limits of detection (LOD) are considered and analytical expressions are derived. For the first time, not only the influence of a static measurand is analyzed, but also the dynamic operation, i.e., physical quantities to be detected that quickly change over time. Accordingly, frequency-dependent limits of detection can be derived in the form of amplitude spectral densities. It is shown that the low-frequency LOD in phase mode is always about 6 dB better than the LOD in amplitude mode. In addition, the bandwidth, in terms of detectivity, is generally significantly larger in phase mode and never worse compared with the amplitude mode.

Quantitative Evaluation for Magnetoelectric Sensor Systems in Biomagnetic Diagnostics.

Dedicated research is currently being conducted on novel thin film magnetoelectric (ME) sensor concepts for medical applications. These concepts enable a contactless magnetic signal acquisition in the presence of large interference fields such as the magnetic field of the Earth and are operational at room temperature. As more and more different ME sensor concepts are accessible to medical applications, the need for comparative quality metrics significantly arises. For a medical application, both the specification of the sensor itself and the specification of the readout scheme must be considered. Therefore, from a medical user's perspective, a system consideration is better suited to specific quantitative measures that consider the sensor readout scheme as well. The corresponding sensor system evaluation should be performed in reproducible measurement conditions (e.g., magnetically, electrically and acoustically shielded environment). Within this contribution, an ME sensor system evaluation scheme will be described and discussed. The quantitative measures will be determined exemplarily for two ME sensors: a resonant ME sensor and an electrically modulated ME sensor. In addition, an application-related signal evaluation scheme will be introduced and exemplified for cardiovascular application. The utilized prototype signal is based on a magnetocardiogram (MCG), which was recorded with a superconducting quantum-interference device. As a potential figure of merit for a quantitative signal assessment, an application specific capacity (ASC) is introduced. In conclusion, this contribution highlights metrics for the quantitative characterization of ME sensor systems and their resulting output signals in biomagnetism. Finally, different ASC values and signal-to-noise ratios (SNRs) could be clearly presented for the resonant ME sensor (SNR: -90 dB, ASC: 9.8×10-7 dB Hz) and also the electrically modulated ME sensor (SNR: -11 dB, ASC: 23 dB Hz), showing that the electrically modulated ME sensor is better suited for a possible MCG application under ideal conditions. The presented approach is transferable to other magnetic sensors and applications.

MaDoPO: Magnetic Detection of Positions and Orientations of Segmented Deep Brain Stimulation Electrodes: A Radiation-Free Method Based on Magnetoencephalography.

BACKGROUND: Current approaches to detect the positions and orientations of directional deep brain stimulation (DBS) electrodes rely on radiative imaging data. In this study, we aim to present an improved version of a radiation-free method for magnetic detection of the position and the orientation (MaDoPO) of directional electrodes based on a series of magnetoencephalography (MEG) measurements and a possible future solution for optimized results using emerging on-scalp MEG systems. METHODS: A directional DBS system was positioned into a realistic head-torso phantom and placed in the MEG scanner. A total of 24 measurements of 180 s each were performed with different predefined electrode configurations. Finite element modeling and model fitting were used to determine the position and orientation of the electrode in the phantom. Related measurements were fitted simultaneously, constraining solutions to the a priori known geometry of the electrode. Results were compared with the results of the high-quality CT imaging of the phantom. RESULTS: The accuracy in electrode localization and orientation detection depended on the number of combined measurements. The localization error was minimized to 2.02 mm by considering six measurements with different non-directional bipolar electrode configurations. Another six measurements with directional bipolar stimulations minimized the orientation error to 4°. These values are mainly limited due to the spatial resolution of the MEG. Moreover, accuracies were investigated as a function of measurement time, number of sensors, and measurement direction of the sensors in order to define an optimized MEG device for this application. CONCLUSION: Although MEG introduces inaccuracies in the detection of the position and orientation of the electrode, these can be accepted when evaluating the benefits of a radiation-free method. Inaccuracies can be further reduced by the use of on-scalp MEG sensor arrays, which may find their way into clinics in the foreseeable future.

Modeling and Parallel Operation of Exchange-Biased Delta-E Effect Magnetometers for Sensor Arrays.

Recently, Delta-E effect magnetic field sensors based on exchange-biased magnetic multilayers have shown the potential of detecting low-frequency and small-amplitude magnetic fields. Their design is compatible with microelectromechanical system technology, potentially small, and therefore, suitable for arrays with a large number N of sensor elements. In this study, we explore the prospects and limitations for improving the detection limit by averaging the output of N sensor elements operated in parallel with a single oscillator and a single amplifier to avoid additional electronics and keep the setup compact. Measurements are performed on a two-element array of exchange-biased sensor elements to validate a signal and noise model. With the model, we estimate requirements and tolerances for sensor elements using larger N. It is found that the intrinsic noise of the sensor elements can be considered uncorrelated, and the signal amplitude is improved if the resonance frequencies differ by less than approximately half the bandwidth of the resonators. Under these conditions, the averaging results in a maximum improvement in the detection limit by a factor of N. A maximum N≈200 exists, which depends on the read-out electronics and the sensor intrinsic noise. Overall, the results indicate that significant improvement in the limit of detection is possible, and a model is presented for optimizing the design of delta-E effect sensor arrays in the future.

Determining the rotational orientation of directional deep brain stimulation electrodes using magnetoencephalography.

Objective.The aim of the present study was to evaluate the effect of different electrode configurations on the accuracy of determining the rotational orientation of the directional deep brain stimulation (DBS) electrode with our previously published magnetoencephalography (MEG)-based method.Approach.A directional DBS electrode, along with its implantable pulse generator, was integrated into a head phantom and placed within the MEG sensor array. Predefined bipolar electrode configurations, based on activation of different directional and omnidirectional contacts of the electrode, were set to generate a defined magnetic field during stimulation. This magnetic field was then measured with MEG. Finite element modeling and model fitting approach were used to calculate electrode orientation.Main results.The accuracy of electrode orientation detection depended on the electrode configuration: the vertical configuration (activation of two directional contacts arranged one above the other) achieved an average accuracy of only about 41 ∘. The diagonal configuration (activation of the electrode tip and a single directional contact at the next higher level of the electrode) achieved an accuracy of 13∘, while the horizontal electrode configuration (activation of two adjacent directional contacts at the same electrode level) achieved the best accuracy of 6∘. The accuracy of orientation detection of the DBS electrode depends on the change in spatial distribution of the magnetic field with the rotation of the electrode along its own axis. In the vertical configuration, rotation of the electrode has a small effect on the magnetic field distribution, while in the diagonal or horizontal configuration, electrode rotation has a significant effect on the magnetic field distribution.Significance.Our work suggests that in order to determine rotational orientation of a DBS electrode using MEG, horizontal configuration should be used as it provides the most accurate results compared to other possible configurations.

Phase Noise of SAW Delay Line Magnetic Field Sensors.

Surface acoustic wave (SAW) sensors for the detection of magnetic fields are currently being studied scientifically in many ways, especially since both their sensitivity as well as their detectivity could be significantly improved by the utilization of shear horizontal surface acoustic waves, i.e., Love waves, instead of Rayleigh waves. By now, low-frequency limits of detection (LOD) below 100 pT/Hz can be achieved. However, the LOD can only be further improved by gaining a deep understanding of the existing sensor-intrinsic noise sources and their impact on the sensor's overall performance. This paper reports on a comprehensive study of the inherent noise of SAW delay line magnetic field sensors. In addition to the noise, however, the sensitivity is of importance, since both quantities are equally important for the LOD. Following the necessary explanations of the electrical and magnetic sensor properties, a further focus is on the losses within the sensor, since these are closely linked to the noise. The considered parameters are in particular the ambient magnetic bias field and the input power of the sensor. Depending on the sensor's operating point, various noise mechanisms contribute to f0 white phase noise, f-1 flicker phase noise, and f-2 random walk of phase. Flicker phase noise due to magnetic hysteresis losses, i.e. random fluctuations of the magnetization, is usually dominant under typical operating conditions. Noise characteristics are related to the overall magnetic and magnetic domain behavior. Both calculations and measurements show that the LOD cannot be further improved by increasing the sensitivity. Instead, the losses occurring in the magnetic material need to be decreased.

Investigation of Magnetoelectric Sensor Requirements for Deep Brain Stimulation Electrode Localization and Rotational Orientation Detection.

Correct position and orientation of a directional deep brain stimulation (DBS) electrode in the patient's brain must be known to fully exploit its benefit in guiding stimulation programming. Magnetoelectric (ME) sensors can play a critical role here. The aim of this study was to determine the minimum required limit of detection (LOD) of a ME sensor that can be used for this application by measuring the magnetic field induced by DBS. For this experiment, a commercial DBS system was integrated into a head phantom and placed inside of a state-of-the-art Superconducting Quantum Interference Device (SQUID)-based magnetoencephalography system. Measurements were performed and analyzed with digital signal processing. Investigations have shown that the minimum required detection limit depends on various factors such as: measurement distance to electrode, bandwidth of magnetic sensor, stimulation amplitude, stimulation pulse width, and measurement duration. For a sensor that detects only a single DBS frequency (stimulation frequency or its harmonics), a LOD of at least 0.04 pT/Hz0.5 is required for 3 mA stimulation amplitude and 60 µµs pulse width. This LOD value increases by an order of magnitude to 0.4 pT/Hz0.5 for a 1 kHz, and by approximately two orders to 3 pT/Hz0.5 for a 10 kHz sensor bandwidth. By averaging, the LOD can be reduced by at least another 2 orders of magnitude with a measurement duration of a few minutes.

DBS electrode localization and rotational orientation detection using SQUID-based magnetoencephalography.

Objective.The aim of the present study was to investigate the accuracy of localization and rotational orientation detection of a directional deep brain stimulation (DBS) electrode using a state-of-the-art magnetoencephalography (MEG) scanner.Approach.A directional DBS electrode along with its stimulator was integrated into a head phantom and placed inside the MEG sensor array. The electrode was comprised of six directional and two omnidirectional contacts. Measurements were performed while stimulating with different contacts and parameters in the phantom. Finite element modeling and fitting approach were used to compute electrode position and orientation.Main results.The electrode was localized with a mean accuracy of 2.2 mm while orientation was determined with a mean accuracy of 11∘. The limitation in detection accuracy was due to the lower measurement precision of the MEG system. Considering an ideal measurement condition, these values represent the lower bound of accuracy that can be achieved in patients.Significance.However, a future magnetic measuring system with higher precision will potentially detect location and orientation of a DBS electrode with an even greater accuracy.

Multi-Mode Love-Wave SAW Magnetic-Field Sensors.

A surface-acoustic-wave (SAW) magnetic-field sensor utilizing fundamental, first- and second-order Love-wave modes is investigated. A 4.5   µ m SiO2 guiding layer on an ST-cut quartz substrate is coated with a 200 n m (Fe90Co10)78Si12B10 magnetostrictive layer in a delay-line configuration. Love-waves are excited and detected by two interdigital transducers (IDT). The delta-E effect in the magnetostrictive layer causes a phase change with applied magnetic field. A sensitivity of 1250 ° / m T is measured for the fundamental Love mode at 263 M Hz . For the first-order Love mode a value of 45 ° / m T is obtained at 352 M Hz . This result is compared to finite-element-method (FEM) simulations using one-dimensional (1D) and two-and-a-half-dimensional (2.5 D) models. The FEM simulations confirm the large drop in sensitivity as the first-order mode is close to cut-off. For multi-mode operation, we identify as a suitable geometry a guiding layer to wavelength ratio of h GL / λ ≈ 1.5 for an IDT pitch of p = 12   µ m . For this layer configuration, the first three modes are sufficiently far away from cut-off and show good sensitivity.

Equivalence of Open-Loop and Closed-Loop Operation of SAW Resonators and Delay Lines.

Surface acoustic wave (SAW) sensors in the form of two-port resonators or delay lines are widely used in various fields of application. The readout of such sensors is achieved by electronic systems operating either in an open-loop or in a closed-loop configuration. The mode of operation of the sensor system is usually chosen based on requirements like, e.g., bandwidth, dynamic range, linearity, costs, and immunity against environmental influences. Because the limit of detection (LOD) at the output of a sensor system is often one of the most important figures of merit, both readout structures, i.e., open-loop and closed-loop systems, are analyzed in terms of the minimum achievable LOD. Based on a comprehensive phase noise analysis of these structures for both resonant sensors and delay line sensors, expressions for the various limits of detection are derived. Under generally valid conditions, the equivalence of open-loop and closed-loop operation is shown for both types of sensors. These results are not only valid for SAW devices, but are also applicable to all kinds of phase-sensitive sensors.

Moisture Monitoring in Fluid-Bed Granulation by Multi-Resonance Microwave Sensor: Applicability on Crystal-Water Containing Donepezil Granules.

Multi-resonance microwave sensors have recently been introduced for moisture monitoring of pharmaceutical particulates up to > 20% residual moisture. The extended measuring range compared to previous systems as well as the microwave moisture values independent of other physical attributes make them promising process analytical technology (PAT) tools for various pharmaceutical production processes. However, so far, research focused on measurements on raw materials or drug-free model granulates and has neither evaluated the applicability for materials with crystal water containing excipients nor for active ingredients. In this study, possible influence of crystal water was evaluated using lactose monohydrate and donepezil hydrochloride, an active pharmaceutical ingredient (API) against dementia. The study clearly showed that the contained hydrate does not cause interferences and is not monitored by the applied frequencies. Material-related limits measuring lactose monohydrate were only observed above typical granulation moistures and could be explained using raw resonance curves. Furthermore, the inclusion of donepezil hydrochloride into the monitored formulations and varied process parameters demonstrated the versatility of the microwave resonance sensor system. Inlet air temperature, spraying rate, and air flow were varied according to a 23 full factorial experimental design. A predictive model (R2 = 0.9699, RMSEC = 0.33%) could be established using samples produced with different process parameter settings adjusted according to the corner points of the full factorial design and validated on the center point granulation processes (RMSEV = 0.38%). Thereby, performance on actual formulations and conditions faced during process development could be thoroughly assessed, and hence, another key requirement for applicability in formulation development could be met.

Wide Band Low Noise Love Wave Magnetic Field Sensor System.

We present a comprehensive study of a magnetic sensor system that benefits from a new technique to substantially increase the magnetoelastic coupling of surface acoustic waves (SAW). The device uses shear horizontal acoustic surface waves that are guided by a fused silica layer with an amorphous magnetostrictive FeCoSiB thin film on top. The velocity of these so-called Love waves follows the magnetoelastically-induced changes of the shear modulus according to the magnetic field present. The SAW sensor is operated in a delay line configuration at approximately 150 MHz and translates the magnetic field to a time delay and a related phase shift. The fundamentals of this sensor concept are motivated by magnetic and mechanical simulations. They are experimentally verified using customized low-noise readout electronics. With an extremely low magnetic noise level of ≈100 pT/[Formula: see text], a bandwidth of 50 kHz and a dynamic range of 120 dB, this magnetic field sensor system shows outstanding characteristics. A range of additional measures to further increase the sensitivity are investigated with simulations.

From laboratory- to pilot-scale: moisture monitoring in fluidized bed granulation by a novel microwave sensor using multivariate calibration approaches.

Recently, microwave resonance technology (MRT) sensor systems operating at four resonances instead of a single resonance frequency were established as a process analytical technology (PAT) tool for moisture monitoring. The additional resonance frequencies extend the technologies' possible application range in pharmaceutical production processes remarkably towards higher moisture contents. In the present study, a novel multi-resonance MRT sensor was installed in a bottom-tangential-spray fluidized bed granulator in order to provide a proof-of-concept of the recently introduced technology in industrial pilot-scale equipment. The mounting position within the granulator was optimized to allow faster measurements and thereby even tighter process control. As the amount of data provided by using novel MRT sensor systems has increased manifold by the additional resonance frequencies and the accelerated measurement rate, it permitted to investigate the benefit of more sophisticated evaluation methods instead of the simple linear regression which is used in established single-resonance systems. Therefore, models for moisture prediction based on multiple linear regression (MLR), principal component regression (PCR), and partial least squares regression (PLS) were built and assessed. Correlation was strong (all R2 > 0.988) and predictive abilities were rather acceptable (all RMSE ≤0.5%) for all models over the whole granulation process up to 16% residual moisture. While PCR provided best predictive abilities, MLR proofed as a simple and valuable alternative without the need of chemometric data evaluation.

Real-time process monitoring in a semi-continuous fluid-bed dryer - microwave resonance technology versus near-infrared spectroscopy.

The trend towards continuous manufacturing in the pharmaceutical industry is associated with an increasing demand for advanced control strategies. It is a mandatory requirement to obtain reliable real-time information on critical quality attributes (CQA) during every process step as the decision on diversion of material needs to be performed fast and automatically. Where possible, production equipment should provide redundant systems for in-process control (IPC) measurements to ensure continuous process monitoring even if one of the systems is not available. In this paper, two methods for real-time monitoring of granule moisture in a semi-continuous fluid-bed drying unit are compared. While near-infrared (NIR) spectroscopy has already proven to be a suitable process analytical technology (PAT) tool for moisture measurements in fluid-bed applications, microwave resonance technology (MRT) showed difficulties to monitor moistures above 8% until recently. The results indicate, that the newly developed MRT sensor operating at four resonances is capable to compete with NIR spectroscopy. While NIR spectra were preprocessed by mean centering and first derivative before application of partial least squares (PLS) regression to build predictive models (RMSEP = 0.20%), microwave moisture values of two resonances sufficed to build a statistically close multiple linear regression (MLR) model (RMSEP = 0.07%) for moisture prediction. Thereby, it could be verified that moisture monitoring by MRT sensor systems could be a valuable alternative to NIR spectroscopy or could be used as a redundant system providing great ease of application.

In-line moisture monitoring in fluidized bed granulation using a novel multi-resonance microwave sensor.

Microwave resonance technology (MRT) is known as a process analytical technology (PAT) tool for moisture measurements in fluid-bed granulation. It offers a great potential for wet granulation processes even where the suitability of near-infrared (NIR) spectroscopy is limited, e.g. colored granules, large variations in bulk density. However, previous sensor systems operating around a single resonance frequency showed limitations above approx. 7.5% granule moisture. This paper describes the application of a novel sensor working with four resonance frequencies. In-line data of all four resonance frequencies were collected and further processed. Based on calculation of density-independent microwave moisture values multiple linear regression (MLR) models using Karl-Fischer titration (KF) as well as loss on drying (LOD) as reference methods were build. Rapid, reliable in-process moisture control (RMSEP≤0.5%) even at higher moisture contents was achieved.

Design, development and method validation of a novel multi-resonance microwave sensor for moisture measurement.

Microwave sensor systems using resonance technology at a single resonance in the range of 2-3 GHz have been shown to be a rapid and reliable tool for moisture determination in solid materials including pharmaceutical granules. So far, their application is limited to lower moisture ranges or limitations above certain moisture contents had to be accepted. Aim of the present study was to develop a novel multi-resonance sensor system in order to expand the measurement range. Therefore, a novel sensor using additional resonances over a wide frequency band was designed and used to investigate inherent limitations of first generation sensor systems and material-related limits. Using granule samples with different moisture contents, an experimental protocol for calibration and validation of the method was established. Pursuant to this protocol, a multiple linear regression (MLR) prediction model built by correlating microwave moisture values to the moisture determined by Karl Fischer titration was chosen and rated using conventional criteria such as coefficient of determination (R2) and root mean square error of calibration (RMSEC). Using different operators, different analysis dates and different ambient conditions the method was fully validated following the guidance of ICH Q2(R1). The study clearly showed explanations for measurement uncertainties of first generation sensor systems which confirmed the approach to overcome these by using additional resonances. The established prediction model could be validated in the range of 7.6-19.6%, demonstrating its fit for its future purpose, the moisture content determination during wet granulations.