Frequency-modulated magnetoelectric sensor systems for the measurement of broadband, low-frequency biomagnetic fields

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The objective of the project is to measure with new magnetoelectric sensors first biomagnetic signals and therewith validate the performance of the sensors. The focus is on low-frequency (below 100 Hz), wide-band (more than 20 Hz) signals originating from the human heart, the skeletal muscle and the brain, which can be utilized diagnostically by magnetocardiography (MCG), magnetomyography (MMG) and magnetoencephalography (MEG). To measure these signals the signal-to-noise ratio of the sensors will be improved and the cross-sensitivity will be reduced. For this purpose we propose and investigate new surface micromachined MEMS ME sensor concepts which are based on coupled resonators operated in anti-phase mode which promise high sensitivity and low acoustic cross-sensitivity. With the integration of a low-noise amplifier close to the sensor the coupling of parasitic noise signals will be suppressed. For the noise reduction also a modified frequency-conversion approach will be explored which transfers the low-frequency biomagnetic signals to the sensor resonance in the kHz-range.At first, the MEMS sensors realized in this project along with suitable sensors from projects P4, P5 and P6 will be characterized by measuring artificial magnetic signals generated in phantoms of the human head and chest. In order to acquire reliable data for evaluating possible applications and the diagnostic significance of ME sensor based MCG a realistic thorax model including compartments like mediastinum, pleural cavity and thoracic wall will be realized.In the next phase, ME sensor measurements with probands are planned, starting with large biomagnetic signals, as from evoked muscle activities at about 100 pT. Subsequently, measurements of continuously reduced biomagnetic signal strength are conducted. This includes triggered heart signals, signals from spontaneously active skeletal and eye muscles (ca. 20 pT) and finally the alpha rhythms of the human brain (ca. 1 pT). The focus of the investigations will be on the measurement of periodic signals in order to achieve a high signal-to-noise ratio by sampling.