Increasing the Robustness of the automatic IMU calibration for lower Extremity Motion Analysis

With the advances of IMU-based human motion tracking, joint angle tracking in an home environment has become a realistic goal. Achieving it, could enable novel applications in rehabilitation and sports medicine. However, in existing systems the process of aligning the mounted sensors with the body coordinate system is either not robust enough or to complicated for fully unsupervised usage. In this publication the performance of a promising existing algorithm is evaluated with a range of different calibration motions. Further, an extension to this implementation is proposed, aiming to improve its stability when only non-ideal calibration data is available. It could be validated that the modification of the algorithm can increase the stability and reduce the dependency of the calibration on specific calibration motions. Based on these results, we recommend the proposed extension of the algorithm as a drop-in replacement for the existing implementation.