Project P9: Resonant magnetoelectric sensor systems for the measurement of deep brain stimulation

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The project targets on the fabrication and investigation of resonant magnetoelectric (ME) sensors and the realization of 3D-sensors and sensor arrays including analog signal conditioning circuits. The sensor performance will be validated by experiments using a realistic phantom of the human head and by the measurement of biomagnetic signals from patients with deep brain stimulators.The focus is on high frequency (above 100 Hz), narrow bandwidth (less than 2 Hz) periodic signals originating for instance from deep brain stimulation or specific sensory evoked potentials. For the measurement of these high frequency signals or their harmonics resonant surface micromachined ME sensors will be developed which reach high mechanical quality factors by vacuum encapsulation. The resonant frequency of the sensors is adjusted by design or in operation by integrated tuning mechanisms to the specific signal frequency. These MEMS ME sensors will be hybrid-integrated with low-noise amplifiers and analog-digital-converters to sensor systems. Using precision assembly technologies 3D-sensor modules and sensor arrays will be built. For the fabrication of these multi-sensor modules exchange-bias layer stacks as magnetostrictive component are investigated which do not have a need on external bias fields. For the measurement of sensitivity, resolution and directivity of the ME sensor modules a dedicated measurement set-up with three orthogonal magnetic field coils and a realistic head phantom with regions of different electrical conductivities is developed and applied. Subsequently, the MEMS sensors from this project along with suitable sensors from projects P4, P5 and P6 will be evaluated in relevant neuro-medical applications. At first, we measure high frequency harmonics of a brain pacemaker positioned in the head phantom. Then the artefact signal originating from a patient`s brain pace maker is measured and the quality of signal reconstruction algorithms is evaluated. By simultaneous registration of EEG and MEG we compare the signal quality and validity on the scalp and quantify their mutual influence. Further on, the differences in the field distribution of commercial stimulation electrodes with 32 contacts for different wiring configurations are investigated.