Subject-Exoskeleton Contact Model Calibration Leads to Accurate Interaction Force Predictions

• Published in: IEEE transactions on neural systems and rehabilitation engineering Vol. 27; no. 8; pp. 1597 - 1605
• Main Authors: Serrancoli, Gil, Falisse, Antoine, Dembia, Christopher, Vantilt, Jonas, Tanghe, Kevin, Lefeber, Dirk, Jonkers, Ilse, De Schutter, Joris, De Groote, Friedl
• Format: Journal Article Publication
• Language: English
• Published: United States IEEE 01.08.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adult; Biomechanical Phenomena; Biomechanics; Biomecànica; Calibration; Collaboration; Computational modeling; Computer applications; Computer Simulation; con-25tact forces; contact forces; dynamic optimization; Electromyography; Enginyeria mecànica; Exoskeleton; Exoskeleton Device; Exoskeletons; Foot - physiology; Gravitation; Humans; Kinematics; Leg - physiology; Male; Movement prediction; Optimal control; Pelvis; Pelvis - physiology; Predictive control; Predictive models; Prosthesis Design; Reproducibility of Results; Sensors; Simulation; Thigh; Thigh - physiology; Àrees temàtiques de la UPC
• ISSN: 1534-4320; 1558-0210; 1558-0210
• DOI: 10.1109/TNSRE.2019.2924536

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 modeling 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 root mean square differences - RMSD - coordinates ≤ 1.1° and velocities ≤ 6.8°/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° and velocities ≤ 15.0°/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.