Vital parameters such as pulse and respiration are important indicators of various diseases and the general state of health of a person. The gold standard methods, such as electrocardiography for monitoring the heart, usually require contact with the patient, e.g. in the form of adhesive electrodes. We are researching ways to replace these with cameras where possible.

Possible topics include

• Machine Learning & Interpretability
• Multiphysics simulations and rendering of synthetic video data
• Methods for sensor fusion (cameras, wearables, …)
• Photoplethymography imaging
• Robust estimation of heart rate variability

Knowledge of Python (or alternatively Matlab) and signal processing is recommended. Knowledge of Blender or Unreal Engine may be an advantage for some topics.

Maurice Rohr (Contact)

Stress is a common cause of sleep problems, concentration disorders, depression or even cardiovascular disease. While stress is often assessed purely subjectively, we are working on recording vital signs in order to make a quantitative statement about a person's well-being. The vital signs are primarily to be recorded non-invasively in order to enable the end user to be as comfortable as possible. In addition, stress can also be recorded in people who are unable to articulate this independently, such as newborn babies or people with disabilities.

While research is mainly focussed on the development of stress caused by acoustic stimuli such as noise, it is not limited to this. Possible areas of application include contactless parameter recording at the workplace, in the car or in bed. The parameters are to be analysed primarily with the help of machine learning algorithms.

Possible topics:

• Non-invasive vital parameter estimation based on cECG, thermographic camera and PPGI
• Sensor fusion for robust parameter estimation
• Quantitative analysis of stress
• Application of machine learning with a focus on computer vision and signal processing
• Implementation of virtual reality environments for test setups

Programming skills in Python or Matlab are recommended. If you are looking for a topic in the field of VR, it is recommended that you have knowledge of C# and Unity programming.

Tizian Dege (Contact)

Physiotherapy is an important part of the treatment of many injuries and illnesses. Ideally, physiotherapy is carried out under the supervision of a healthcare professional who can provide personalised and immediate feedback. But even without direct supervision, exercises at home can be beneficial to the healing process. At the same time, incorrect execution, misjudgement of your own fitness level and overexertion can also lead to inefficient training or, worse still, serious injury.

To mitigate these problems, an automated scoring system can be used to assess the quality of exercise execution and reduce the need for human supervision. Building on advances in the field of computer vision, we are researching the development of such support systems using video-based estimation of human posture.

Possible topics include

• Natural language processing for the automated generation of training data from videos with subtitles
• Analysis of sensor data (EMG, force plates, IMUs) and relation to camera recordings
• Development of biomechanical models of human movement
• Development of methods for the quantitative evaluation of human movement
• Machine learning & computer vision
• Transfer learning & domain adaptation (transfer to infrared cameras)

Knowledge of Python (or alternatively Matlab) and signal processing is recommended. Knowledge of Blender can be an advantage for some topics.

Sebastian Dill (Contact)

Video-based Human State Analysis refers to the use of video footage to assess and interpret the physical, emotional, or psychological states of individuals. This involves analyzing visual data captured by cameras to derive insights about a person's behavior, emotions, actions, or overall well-being.

Possible topics:

• Methods for detecting/tracking human limb movements to correlate with the individual's current state
• Methods for human reflex analyses
• Quantitative analysis of human emotional state
• Machine learning and computer vision

Using tools such as Python, Matlab, classical signal, and image processing

Gökhan Güney (Contact)