Co-simulation of human digital twins and wearable inertial sensors to analyse gait event estimation.

ABSTRACT: We propose a co-simulation framework comprising biomechanical human body models and wearable inertial sensor models to analyse gait events dynamically, depending on inertial sensor type, sensor positioning, and processing algorithms. A total of 960 inertial sensors were virtually attached to the lower extremities of a validated biomechanical model and shoe model. Walking of hemiparetic patients was simulated using motion capture data (kinematic simulation). Accelerations and angular velocities were synthesised according to the inertial sensor models. A comprehensive error analysis of detected gait events versus reference gait events of each simulated sensor position across all segments was performed. For gait event detection, we considered 1-, 2-, and 4-phase gait models. Results of

SUBMITTER: Uhlenberg L 

PROVIDER: S-EPMC10132030 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature