Seminar: Machine Learning and Artificial Neural Networks in Biomedical Applications

Lehrstuhl Technische Informatik
Dozent Dr. SpĂŒler
Betreuer Peter
Vorbesprechung         24.04.2017, 10:00 (c.t.), F122 Hörsaal 2 (Sand)
Umfang 2 SWS / 4 LP
Eintrag im LSF Machine Learning and Artificial Neural Networks in Biomedical Applications


The Seminar "Machine Learning and Artificial Neural Networks in Biomedical Applications" covers current topics of signal processing on neural signals (e.g. fMRI, EEG or MEG) for their use in biomedical applications (e.g. neuroprosthetics or brain-computer interfaces, BCIs) and related topics; as well as methods and algorithms applied in those fields.


 Exemplary topics from the last years (current topics will be different):

  • Decision Making in the ICU with Rbf-Based Fuzzy Logic
  • Improvement of Patient Monitoring Alarms by Using Machine-Learning Techniques
  • Sensitivity Analysis
  • Classification of emotional states from electrocardiogram signals
  • Gaze Guidance and Driving
  • Transcranial Magnetic Stimulation: A New Diagnostic and Therapeutic Tool for Tinnitus Patients?
  • Gaussian Processes in Brain Computer Interfaces
  • Optical Illusions
  • Ultrasonic imaging of the central nervous system to detect pathologies
  • Error Related Potentials to Predict Learning Success


Please pre-register for this course. Send a mail with your name, student id ("Matrikelnummer"), branch of study (CS / bioinformatics / ...) and how far you've progressed in your studies to

The topics will be assigned at the kickoff-meeting at april 24th, 10:00 (c.t.) in room F122 Hörsaal 2 (Sand).

Slides from the kick-off meeting can be found here


  • outlines of presentation and written report: June 16th
  • written report: July 7th
  • presentations: July (14th, 21th)
  • rehearsal presentation: about 1 week before presentation

The written report should be 15-20 pages long and the Latex-Tempalte (Link to Latex-Template) must be used.

The presentation should be 20 minutes plus 10 minutes for discussion. Slides can be made with Powerpoint or Latex.

Additional literature to the topic should be researched independently. All sources used should be properly cited.