PACK Fellowship Seminar on December 14th, 2020

 

Abstract:

When measuring small magnetic fields as they appear in medical or biological applications, both, very small and very large signal amplitudes are observed at the same time. Small amplitudes stem, e.g., from human sources such as the human heart (magnetocardiography) or brain (magnetoencephalography). Low frequency signals (0.5 to 40 Hz) can be measured here with peak amplitudes of about 100 pT (heart) or even less than 1 pT (brain). Superposed to these small signals are usually large signal components that stem either from artificial sources, such as excitation signals utilized for modulation techniques, or from natural sources such as the magnetic field of the earth. Creating digital signals that can be used for detailed (medical) analyses is an interesting challenge for both, material scientists and engineers. Methods for improving the signal quality (mainly in terms of signal-to-noise ratio) can be grouped into analog and digital approaches, indicating whether they are performed prior or after the analog-to-digital (AD) conversion.

If sensors with a limited dynamical range are used in unshielded environments, additional coils can be used for creating a so-called anti field that cancels the magnetic field of the earth or other disturbing components. The driving (analog) currents of such coils can be generated adaptively using (digital) hardware. In the same manner, operation points can be stabilized. Furthermore, voltage adders can be used to cancel typical power supply distortions (50 or 60 Hz) or excitation signals that are required for modulation-based sensor read-out principles.

After the AD conversion so-called reference sensors can be used for recording signals that show a strong correlation with the disturbing but not with the desired signal component. Again, adaptive filtering techniques can be used to enhance the signal quality. However, such approaches are only successful if the analog amplifier followed by the AD converter are not saturated. Furthermore, often magnetoelectic sensors can be read out in a multitude of modes. This allows for adaptive combination of the individual signals, leading to improved robustness and better signal-to-noise ratio. In addition, several sensors can be combined and postprocessing such as digital noise suppression can be applied finally.

As a consequence, more “ingredients” than just the sensor are required for an entire sensor system. This leads to very interesting multidisciplinary research approaches. From sensors to sensor systems: it’s a rocky road.

Short CV of Gerhard Schmidt:

Gerhard Schmidt received the Dipl.Ing. degree in 1996 and the Dr.Ing. degree in 2001, both from Darmstadt, University of Technology, Germany. After his Ph.D., he worked in the research groups of the acoustic signal processing departments at Harman/Becker Automotive Systems and at SVOX, both in Ulm, Germany. Parallel to his time at SVOX he was a part-time professor at Darmstadt, University of Technology. Since 2010 he has been a full professor at Kiel University, Germany. His main research interests include adaptive methods for audio, SONAR, and medical signal processing. 

Please note that the details are in EST and this meeting will take place at 4:00 pm CET on December 14, 2020 for Kiel University attendees.
 
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Contact

gus@tf.uni-kiel.de

Chairman:

Prof. Dr. Gerhard Schmidt

Kiel University
Institute for Electrical Engineering and Information Engineering

 

Internal server

 

CAU

Christian-Albrechts-Universität zu Kiel (CAU)

Christ.-Albrechts-Platz 4
D-24118 Kiel

UKSH

University Hospital Schleswig-Holstein, Campus Kiel (UKSH)

Arnold-Heller-Straße 3
D-24105 Kiel

ISIT

Fraunhofer Institute for Silicon Technology, Itzehoe (ISIT)

Fraunhoferstrasse 1
D-25524 Itzehoe  

IPN

IPN - Leibniz-Institut für die Pädagogik der Naturwissenschaften und Mathematik 

Olshausenstraße 62 
D-24118 Kiel

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