Chair of Health Informatics

CHI - Chair of Health Informatics   

The Chair of Health Informatics at the Technical University of Munich combines computer science with modern medicine. The research field is the sensor and knowledge-based monitoring and monitoring of all health-relevant parameters during sports and other activities.

The main interest lies in the recording, analysis and interpretation of biosignals, such as those that arise when monitoring heart activity, metabolism or neuronal activity. In addition, acoustic parameters (speech and other acoustic events) and visual parameters (face, gestures, body motor skills) are also processed in a realistic scenario (everyday life).


Silent Paralinguistics

DFG (German Research Foundation) Project

Runtime: 36 Months

Partner: University of Bremen

We propose to combine Silent Speech Interfaces with Computational Paralinguistics to form Silent Paralinguistics (SP). To reach the envisioned project goal of inferring paralinguistic information from silently produced speech for natural spoken communication, we will investigate three major questions: (1) How well can speaker states and traits be predicted from EMG signals of silently produced speech, using the direct and indirect silent paralinguistics approach? (2) How to integrate the paralinguistic predictions into the Silent Speech Interface to generate appropriate acoustic speech from EMG signals (EMG-to-speech)? and (3) Does the resulting paralinguistically enriched acoustic speech signal improve the usability of spoken communication with regards to naturalness and user acceptance?


We are offering supervision for bachelor and master theses, as well as research practise. If you are interested in finding a topic with us, please contact directly one of our researchers mentioned above. Exemplary topics are listed below. Please note that topics in research and thus for thesis topics can change rapidly; it is thus best to get directly in contact with us to find a suitable topic.

Exploring optimisation algorithms for deep learning (Manuel Milling)

Object detection and classification of pollen on microscope images (Manuel Milling)