Seminar "Selected Topics in Medical Signal Processing"


Basic Information
Lecturers: Gerhard Schmidt and group
Semester: Winter term
Language: English or German
Target group: Master students in electrical engineering and computer engineering
Prerequisites: Fundamentals in digital signal processing

If you want to sign up for this seminar, you need to register with the following information in the registration form

  • surname, first name,
  • e-mail address,
  • matriculation number,

Please note that the registration period starts 16.10.2023 at 10:00 h and ends 29.10.2023 at 23:59 h. All applications before and after this registration period will not be taken into account.

Registration will be possible within the before mentioned time under the following subsite - Seminar Registration.

During the registration process you will also choose your seminar topic. Only one student per topic is permitted (first come - first serve).

The registration is binding. A deregistration is only possible by sending an e-mail with your name and matriculation number to This email address is being protected from spambots. You need JavaScript enabled to view it. until Sunday, 29.10.2023 at 23:59 h. All later cancellations of registration will be considered as having failed the seminar.

Time: Preliminary meeting per arrangement with individual supervisor
Written report due on 04.02.2023
Final presentations, XX.XX.2023 at XX:XX h

Students write a scientific report on a topic closely related to the current research of the DSS group. Potential topics, therefore, deal with digital signal processing related to medical signal processing.

Students will also present their findings in front of the other participants and the DSS group.


Topics for WS 23/24

Topic title Description
Electrocardiographic Imaging

Electrocardiographic imaging (ECGi) is a non-invasive measurement that provides a 3D visualization of the geometry of the human heart as well as activation maps. For this purpose, numerous electrodes are placed on the body surface. In combination with CT or MRI scans, the body surface potential is used to solve an inverse problem for the intracardiac potential. Since small errors in the measured body surface potential can lead to large errors in the intracardiac potential, various mechanisms are used to regularize the inverse problem. You will review multiple ECGi algorithms and compare their accuracy, validation schemes, measurement setups, and technology readiness levels.

Magnetic Localization Algorithms for Medical Applications

Different medical interventions and examinations either rely on or might be enhanced by the precise knowledge of the used instruments' pose (position and orientation). One example would be ultrasound examinations, in which the pose of the probe is important for the correct interpretation of the produced images and the possibility to reconstruct 3D volumes from the two dimensional data. Another application lies in endoscopic interventions, in which the pose information may enable more reliable diagnostics and result in overall better patient care. Magnetic approaches for such a localization are under active investigation, working with sensors, active actuators or permanent magnets at the medical devices. In this seminar, you will perform a literature review researching different magnetic localization algorithms, e.g., based on gradient descent or particle swarm optimizers. Your goal will be a comparison of multiple approaches, highlighting advantages and disadvantages as well as general preliminary assumptions and current limitations.

Overview: Magnetic Sensors for Movement Sensing

Active magnetic motion sensing describes a movement feature reconstruction based on a combination of magnetic sensors and actuators. This approach is also called magnetic localization, magnetic motion tracking or indoor navigation. Size, bandwidth and magnetic noise are three common characteristics of magnetic sensors that are crucial for this type of application. In this seminar, you will do a literature review on suitable sensor types by finding at least nine further papers on the topic. You will first look for the abovement characteristics and than identify at least three more characteristics that are relevant for the application. Afterwards you will do a comparison of all identified sensor types regarding these six characteristics.