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M. Sc. Erik EngelhardtRoom: C-01.021 (ZEVS)Kaiserstraße 2, 24143 Kiel, Germany Phone: +49 431 880-6132 E-mail: ORCID: |
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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 |
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| 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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In March 2026, the DSS Chair attended the annual DAGA conference in Dresden. Thanks to the support of the GaS-Club, the student Aylin Kösker was given the opportunity to accompany the chair and participate in the conference from March 23rd to March 26th. As part of the daily poster sessions, she presented the results of her bachelor’s thesis “Machine Learning for the Analysis of Hydrographic Data to Assess the Waterside Accessibility of Port Waters” in the field of Underwater Acoustics. The thesis forms an important basis for an ongoing university research project on the acoustic analysis of sediment properties in harbor areas. The poster session enabled valuable discussions with researchers and conference participants from related research fields.