Alexander Blöck

Photo of Blöck, Alexander

Alexander Blöck
University of Tübingen
Department of Computer Science
Computer Engineering
Sand 13
72076 Tübingen

Neural Interfaces and Brain Signal Decoding
PhD student
+49 - (0) 70 71 - 29 - 70490
+49 - (0) 70 71 - 29 - 50 62
Sand 14, C203
Office hours
By appointment

Profile on ResearchGate

Research Interests

  • Brain-Computer Interface (BCI)
  • Analysis of EEG data
  • Machine Learning
  • Neural Networks

Research projects

Brain-Computer Interface for home-use application

Home-use BCI Logo

There are several diseases, such as amyotrophic lateral sclerosis (ALS), which can lead to a loss of the ability to communicate. As a healthy person one cannot imagine what it feels like to be trapped in one’s own body - mentally present, but unable to communicate with relatives, this is called locked-in syndrome. However, a distinction must be made between locked-in and complete locked-in syndrome (CLIS). For the former, those affected can still voluntarily control certain muscles, above all the eye muscles, which in turn can be used for communication. Brain-computer interfaces (BCIs), i.e. systems that allow to control a computer by pure brain activity, have proven to be a helpful method for restoring the ability to communicate. However, all recent BCI systems are almost exclusively used in research, since all previous methods are not suitable for real-world applications. This is mainly due to the fact that for a meaningful and independent use, the recognition of the user’s intention (to control the system or not) must be highly accurate. Otherwise, this leads to random classifications/commands, which can be dangerous depending on the application, for example when controlling an electric wheelchair.


Brain-Games: associated programming project for the lecture Software Engineering Winter 2021
Seminar: Machine Learning and Artificial Neural Networks in Biomedical Applications Winter 2018 Summer 2020 Winter 2020 Summer 2021