ID 2326: EmpkinS D03 – Contactless Measurement of Acute Stress from Micro Movements
Bachelor’s / Master’s Thesis / Research Internship / Project
Acute stress reliably activates, among other pathways, the sympathetic nervous system, leading to changes in heart rate (variability) (HR and HRV), respiration, pre-ejection period (PEP), and electrodermal activity (EDA). So far, these parameters have primarily been assessed using traditional methods, which require attaching electrodes to participants and might limit them in their typical behavior.
In this project, we explore how the assessment of micro movements using contactless sensor technologies, such as radar, can be used to measure the established markers during acute psychosocial stress. Thus, we investigate micro movements on the skin, such as vibrations and movements induced by respiration and heart beats, but also by fasciculations or sweat processes.
We always have open topics for various types of theses in this project! If you are interested in working with us, please use the application form to apply for the topic. We will then get in contact with you and together, we can identify a suitable topic for you. You can have a look at our group page to get an overview of previous student topics in this area.
- You will work in an interdisciplinary team with psychologists and engineers
- You have the opportunity to apply your data science knowledge to practical applications in stress research
- Depending on the topic and scope of your project, you will:
- Support in data collection
- Implement different algorithms into an existing data analysis framework
- Perform statistical and machine learning-based data analysis
- Document your code in a clear and structured manner
Requirements (depending on the topic and type of project)
- Interest in diving into the field of acute stress responses and psychology (especially biopsychology, psychophysiology, and psychoneuroendocrinology)
- Knowledge in data processing, data analysis, and data visualization using Python (or willingness to learn such!)
- Further skills:
- Knowledge of machine and deep learning, (Bayesian) statistics, etc.
- German skills for supporting in data collection
Robert Richer, M. Sc.
PhD Candidate & Group Head
Luca Abel, M. Sc.
Researcher & PhD Candidate
Prof. Dr. Nicolas Rohleder
Chair of Health Psychology
Please use the application form to apply for the topic. We will then get in contact with you.