Prof. Dr. Bernhard Egger

Im Teilprojekt B04 werden innovatiive Verfahren zur Visualisierung von Bewegungsabläufen, die mit verschiedenen empathokinästhetischen Sensoren erfasst und/oder für die eine biomechanische Simulation durchgeführt wurde, erforscht. Der Fokus liegt dabei auf Visualisierungen und der Extraktion von Merkmalen, die bei der medizinischen Interpretation und Diagnose unterstützen.

The aim of the D02 project is the establishment of empathokinesthetic sensor technology and methods of machine learning as a means for the automatic detection and modification of depression-associated facial expressions, posture, and movement. The aim is to clarify to what extent, with the help of kinesthetic-related modifications influence depressogenic information processing and/or depressive symptoms. First, we will record facial expressions, body posture, and movement relevant to depression with the help of currently available technologies (e.g., RGB and depth cameras, wired EMG, established emotion recognition software) and use them as input parameters for new machine learning models to automatically detect depression-associated affect expressions. Secondly, a fully automated biofeedback paradigm is to be implemented and validated using the project results available up to that point. More ways of real-time feedback of depression-relevant kinaesthesia are investigated. Thirdly, we will research possibilities of mobile use of the biofeedback approach developed up to then.