Extraction of features from multisensory data to assess balance and gait stability

Relevant for Research Area

B - Core Technologies

C - Applications

The project builds on



Prof. Thomas Stieglitz

Prof. Wolfram Burgard

Prof. Tonio Ball

Jun.-Prof. Joschka Boedecker


Balance and gait stability mandatory for safe walking with a prosthesis after lower limb amputation. Limb position data with camera based marker systems as well as motion suits together center of pressure data, muscle (EMG) signals and brain (EEG) data will be recorded in volunteers as well as subjects after unilateral limb amputation. Methods of on-linear data analysis (e.g. entropic half-life) and artificial intelligence (e.g. Convolutional Neural Networks) will be applied to identify activation and compensation mechanism after unilateral amputation and extract features that describe and predict balance stability on the level of position, muscle activation and brain signals.