Project B2 - Digital Signal Processing

This project focuses on digital signal processing approaches for enhanced readout of magnetoelectric sensors. The algorithms will be implemented for real-time applications to be prepared for closed-loop operation of entire sensor/actuator systems. The aim is to connect the sensor development and the biomedical analyses by digitally enhancing the sensor signals and providing additional information needed by the biomedical projects.

It starts with extending the existing noise cancellation and noise suppression techniques implemented so far by means of developing non-linear filter structures to resist the non-linear behavior of the ME sensors arising at high signal amplitudes (created by disturbing fields). Furthermore, we will focus on blind source separation techniques for multichannel measurements as well as empirical mode decomposition for single channel measurements to enhance the signal of the sensor. Moreover, the blind source separation approaches can be used in the “classical sense” for the separation of mixed signals.

In addition to the enhanced sensor signals, further information about the sensor is of great interest. Especially the exact position and orientation of the sensor are essential for the solution of inverse problems during medical analyses. Therefore, the sensor will be localized using additional coils transmitting orthogonal signals simultaneous to the biomagnetic measurement.

Moreover, the algorithms developed during the first funding period will be adapted to the new and improved sensor principles developed during the runtime of the Collaborative Research Centre and will be extended towards multichannel measurements with respect to the cross-channel sensitivity between adjacent ME sensors.

This project is closely related to project B1 due to the hardware-close digital signal processing approaches. In cooperation, an optimal sensor system can be provided for the biomedical application projects. This indicates a trong cooperation with virtually all biomedical application projects (B7, B9, B10, and T1). In addition, strong cooperation is planned with the sensor-producing projects (especially with A4, A7, and A9) due to the adjustment of the digital signal processing algorithms and sensor read-out schemes to the individual sensor principles. The project A8 provides further information about the sensor transfer functions for a more precise simulation of the sensor. The central project Z2 supports this project by means of hardware development and passing the real-time system to the medical projects.

 

Involved Researchers

Person Role
M.Sc. Christin Bald
Electrical Engineering
Digital Signal Processig and System Theory
Doctoral researcher
Prof. Dr. Gerhard Schmidt
Electrical Engineering
Digital Signal Processig and System Theory
Principal investigator

 

Role within the Collaborative Research Centre

The project B2 is first of all strongly linked with the analogue signal processing project B1 and the sensor producing projects (e.g. A4), since a digitally controlled analogue cancellation approach and specifically tailored readout scheme for ΔE-effect and other sensor principles are the main focus of the project. However, aside from these collaborations, strong interaction is planned with several other projects. The following table shows details about the planned cooperation of the project B2 within the CRC 1261:

Collaborations
A2, A3, A4, A7, A9 Setup of specifically tailored read-out schemes for the sensor principles investigated in these projects.
A8 (Modelling of Magnetoelectric Sensors) The sensor models that are investigated in A8 will be incorporated in the forward models used in the project (WP 4). A first sensor model version available in 2021 will be replaced with extended versions in 2023.
B1 (Sensor Noise Performance and Analogue System Design) This project will cooperate strongly with B1 in terms of improving the ME sensor frontends.
B9, B10 Cooperation in the design and implementation of the real-time framework for medical applications (heart and movement jacket).
B7, B9, B10, T1 Utilization of the closed-loop real-time framework for measurement purposes.
Z1 (MEMS Magnetoelectric Sensor Fabrication) Production of ME sensors, feedback regarding sensor performance.
Z2 (Magnetoelectric Sensor Characterization) Passing the real-time system to this project for enhanced measurements.

 

Project-related Publications

E. Elzenheimer, C. Bald, E. Engelhardt, J. Hoffmann, P. Hayes, J. Arbustini, A. Bahr, E. Quandt, M. Höft, G. Schmidt: Quantitative Evaluation for Magnetoelectric Sensor Systems in Biomagnetic Diagnostics, MDPI Sensors, vol. 22, no. 3, 1018, 2022.
C. Bald, G. Schmidt: Processing Chain for Localization of Magnetoelectric Sensors in Real Time, Sensors, vol. 21, issue 16, 5675, 2021.
B. Spetzler, C. Bald, P. Durdaut, J. Reermann, C. Kirchhof, A. Teplyuk, D. Meyners, E. Quandt, M. Höft, G. Schmidt, F. Faupel: Exchange Biased Delta-E Effect Enables the Detection of Low Frequency pT Magnetic Fields with Simultaneous Localization, Scientific Reports 11, Article no. 5269, 2021.
B. Spetzler, C. Kirchhof, J. Reermann, P. Durdaut, M. Höft, G. Schmidt, E. Quandt, F. Faupel: Influence of the Quality Factor on the Signal to Noise Ratio of Magnetoelectric Sensors Based on the Delta-E Effect, Applied Physics Letters, vol. 114, issue 18, 183504, 2019.
C. Bald, E. Elzenheimer, J. Reermann, T. Sander-Thömmes, G. Schmidt: Amplitudenverlauf des Herzmagnetfeldes als Funktion des Abstandes, Biosignale Workshop, Erfurt, Germany, 2018.
S. Salzer, V. Röbisch, M. Klug, P. Durdaut, J. McCord, D. Meyners, J. Reermann, M. Höft, R. Knöchel: Noise Limits in Thin-Film Magnetoelectric Sensors With Magnetic Frequency Conversion, IEEE Sensors Journal, vol. 18, no. 2, pp. 596-604, 2018.
A. Kittmann, P. Durdaut, S. Zabel, J. Reermann, J. Schmalz, B. Spetzler, D. Meyners, N. X. Sun, J. McCord, M. Gerken, G. Schmidt, M. Höft, R. Knöchel, F. Faupel, E. Quandt: Wide Band Low Noise Love Wave Magnetic Field Sensor System, Scientific Reports, vol. 8, no. 278, 2018.
P. Durdaut, J. Reermann, S. Zabel, C. Kirchhof, E. Quandt, F. Faupel, G. Schmidt, R. Knöchel, M. Höft: Modeling and Analysis of Noise Sources for Thin-Film Magnetoelectric Sensors Based on the Delta-E Effect, IEEE Transactions on Instrumentation and Measurement, vol. 66, no. 10, pp. 2771-2779, 2017.
J. Reermann, C. Bald, P. Durdaut, A.Piorra, D. Meyners, E. Quandt, M. Höft, G. Schmidt: Adaptive Mehrkanalige Geräuschkompensation für Magnetoelektrische Sensoren, Proc. DAGA, Kiel, Germany, 2017.
P. Durdaut, S. Salzer, J. Reermann, V. Röbisch, J. McCord, D. Meyners, E. Quandt, G. Schmidt, R. Knöchel, M. Höft: Improved Magnetic Frequency Conversion Approach for Magnetoelectric Sensors, IEEE Sensors Letters, vol. 1, no. 3 , 2017.
P. Durdaut, S. Salzer, J. Reermann, V. Röbisch, P. Hayes, A. Piorra, D. Meyners, E. Quandt, G. Schmidt, R. Knöchel, M. Höft: Thermal-Mechanical Noise in Resonant Thin-Film Magnetoelectric Sensors, IEEE Sensors Journal, vol. 17, no. 8, pp. 2338-2348, 2017.
L. Hamid, A. Dalaf, I. Merlet, N. Japaridze, U. Heute, U. Stephani, A Galka, F. Wendling, M. Siniatchkin: Source Reconstruction Via the Spatiotemporal Kalman Filter and LORETA from EEG Time Series with 32 or Fewer Electrodes, Engineering in Medicine and Biology Society (EMBC), 2017 39th Annual International Conference of the IEEE, Seogwipo, South Korea, pp. 2218-2222, 2017.
J. Reermann, C. Bald, S. Salzer, P. Durdaut, A. Piorra, D. Meyners, E. Quandt, M. Höft, Gerhard Schmidt: Comparison of Reference Sensors for Noise Cancellation of Magnetoelectric Sensors, IEEE Sensors, Orlando, 2016.