Subject-exoskeleton contact model calibration leads to accurate interaction force predictions.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society(2019)
摘要
Knowledge of human-exoskeleton interaction forces is crucial to assess user comfort and effectiveness of the interaction. The subject-exoskeleton collaborative movement and its interaction forces can be predicted in-silico using computational modelling techniques. We developed an optimal control framework that consisted of three phases. First, the foot-ground (Phase A) and the subject-exoskeleton (Phase B) contact models were calibrated using three experimental sit-to-stand trials. Then, the collaborative movement and the subject-exoskeleton interaction forces, of six different sit-to-stand trials were predicted (Phase C). The results show that the contact models were able to reproduce experimental kinematics of calibration trials (mean RMSD coordinates. 1.1 degrees, and velocities. 6.8 degrees/s), ground reaction forces (mean RMSD. 22.9 N), as well as the interaction forces at the pelvis, thigh and shank (mean RMSD. 5.4 N). Phase C could predict the collaborative movements of prediction trials (mean RMSD coordinates. 3.5 degrees, and velocities. 15.0 degrees/s), and their subject-exoskeleton interaction forces (mean RMSD. 13.1 N). In conclusion, this optimal control framework could be used while designing exoskeletons to have in silico knowledge of new optimal movements and their interaction forces.
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关键词
Exoskeletons,Computational modeling,Collaboration,Pelvis,Predictive models,Kinematics,Sensors
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