Synthesising motion sensor data from biomechanical simulations to investigate motion sensor placement and orientation variations - Derungs, Adrian; Amft, Oliver (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, 2019)
We propose a motion sensor data synthesis approach to investigate the performance effect of sensor placement and orientation variation on health marker estimation. Using OpenSim, we simulate walking motion of patients after stroke and synthesise inertial sensor data. We analyse 384 sensor positions with 192 sensors simulated at each leg's thigh. To demonstrate how synthesised sensor data could be used to analyse the performance of functional ability estimation, we estimated scores from the Lower-Extremity Fugl-Meyer-Assessment (LE-FMA) using regression methods. We evaluated our approach using a public dataset, including 8 stroke patients and showed that LE-FMA scores could be estimated with an error below 0.12 score points on average, compared to manually derived scores. We further show that sensors should be preferably placed at the thigh front. Our approach demonstrates the potential of combining biomechanical simulations and motion sensor data synthesis with algorithms for health marker estimation, thus providing rapid insight into sensor positioning and orientation variation.
CRIS-Team Scopus Importer:2020-02-21