Development of a Person Centered Measuring System for Detecting Torsion and Rotation of Human Trunk or Head

Author: Christoph Schiefer

Summary: For the improvement and further development of the current CUELA system, an algorithm has been developed that detects torsion and rotation of human trunk or head at real workplaces. The algorithm uses the sensor data (acceleration and angular rate) of two inertial measurement units that are mounted to head and back of a person. The data are used to calculate the orientation in 3D space of the units with respect to each other that leads to the torsion and rotation angle of human trunk or head.
Within the master thesis, a calibration procedure for the inertial measurement units has been set up, the sensors have been calibrated, and the algorithm to determine orientation in 3D space has been developed and optimized using assumptions on human movement characteristics. Finally, the algorithm has been positively evaluated.