M. Sc. Erik Engelhardt

Room: C-01.021 (ZEVS)
Kaiserstraße 2, 24143 Kiel, Germany
Phone: +49 431 880-6132
E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

ORCID: 0000-0002-7012-7707
Google scholar: Link

 

Research: Magnetoelectric Sensor Systems for Cardiologic Applications

Current standard electrocardiography is a useful and easily applicable method that has been in clinical use for more than hundred years. However, it is hampered by low spatial resolution. Thus, precise electro-anatomical mapping of arrhythmias still has to be conducted by invasive catheterization. The main long-term objective of this project is to answer the question whether invasive mapping of arrhythmic substrates (current standard) can be replaced by a non-invasive alternative, namely analyses using signals obtained from ME sensors combined with electric measurements.

We will thus investigate if a multi-channel combined ECG/MCG (electrocardiogram/magnetocardiogram) approach allows for reliable non-invasive localization of the origin of cardiac arrhythmias. This is becoming even more important, as recently stereotactic body radiation therapy was successfully applied for ablation of ventricular tachycardia, promising a completely non-invasive way to cure arrhythmias in the future.

To perform the required measurements with a multitude of magnetic (both ME sensors originating from this CRC and already established systems) as well as electric sensors, individual real-time signal-to-noise ratio estimations of all involved sensors will be investigated that permit optimal sensor placement, sensor signal combination, and parameter extraction. An appropriate automatic signal quality analysis should guarantee a minimum recording time for patients. To answer these research questions, forward modelling and a solution of the inverse problem is necessary. To evaluate the accuracy and clinical utility of this approach, we plan to compare it with results from electrophysiological studies (current standard) in 3 different groups of patients:

  • premature ventricular contractions,
  • idiopathic ventricular tachycardia,
  • ischemic ventricular tachycardia.

For each patient, magnetic resonance imaging (MRI) and computed tomography (CT) for anatomy and electric and magnetic measurements will be performed.

Related topics:

  • Kalman Filter
  • Machine learning
  • Sensor fusion
  • Biomagnetic modelling
  • Biomagnetic measurements

 

Further interests:

  • Software Engineering
  • Real-time digital signal processing
  • Supervised machine learning
  • Reinforcement learning

 

Short CV

Time span Details
2020 - current Research assistant at the Christian-Albrechts-Universität zu Kiel, Kiel, Germany
2020 - 2020 Working Student at Basler AG, Ahrensburg, Germany
2019 - 2020 M.Sc. in Microelectronic Systems at the Hamburg University for Applied Sciences, Hamburg, Germany
2019 - 2020 Embedded Engineer at Siemens AG, Hamburg, Germany
2017 - 2019 Working Student at Siemens AG, Hamburg, Germany
2014 - 2019 B.Sc. in Electrical Engineering at the Hamburg University for Applied Sciences, Hamburg, Germany
2014 - 2017 Vocational Training: Electronics Technician for Automation Technology at Siemens Professional Education, Hamburg, Germany

 

Publications

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