We have a pair of special J!NS glasses equipped with electrodes positioned between the eyebrows and on the nasal wings for electrooculography-based (EOG) sensing. EOG is super cool because it allows eye tracking without cameras, relying only on the electrical signals the eyes produce while moving! You will explore how electrical signals captured at the face can detect eye movements, blinks, and nose-rubbing.

A thesis should explore how EOG signals captured at the face can detect eye movements, blinks, and nose-related behaviours. There are many ideas what to do in a thesis, from comparing these EOG glasses with in-ear EOG systems, to coming up with creative user input through eye gestures.

If you're interested in this technology, just send me an email and let's explore possible topics!

We'd have to talk about what exactly you would do, but possible tasks are:

• Design and conduct a data-collection study using the J!NS glasses to record EOG signals during controlled eye movements (e.g., saccades, smooth pursuits, fixation tasks).
• Develop and train classification or regression models to detect specific behaviors such as gaze direction, smooth pursuit patterns, blinks, or nose-related events.
• Compare facial EOG signals from the glasses with in-ear EOG system like OpenEarable ExG, in terms of signal quality, robustness, and task performance.
• Analyze spontaneous behaviors such as frequency of nose rubbing or face touching under naturalistic conditions.
• Explore feature extraction, filtering, and artifact handling techniques for this type of electrode placement.

• Background knowledge in signal processing, biomedical sensing, or machine learning would be great
• Desire/ability to design and conduct empirical user studies, including data collection and annotation.
• Proficiency with Python or MATLAB for signal analysis and model development.
• Familiarity with classification, regression, or deep-learning pipelines.
• Capability to document results clearly and interpret findings in the context of human-computer interaction and physiological sensing.

• A paragraph explaining your motivation.
• Your study program (Bachelor/Master), current semester, and field of study.
• A transcript of records (courses and grades).
• Your programming experience.
• Any areas of interest relevant to the topic.
• Your CV (if available)