TY - JOUR
T1 - Whole Body Center of Mass Feedback in a Reflex-Based Neuromuscular Model Predicts Ankle Strategy during Perturbed Walking
AU - Keemink, A.Q.L.
AU - Brug, T.J.H.
AU - van Asseldonk, E.H.F.
AU - Wu, A.R.
AU - van der Kooij, H.
N1 - Funding Information:
This work was supported in part by the EU Research Program FP7, FET-Proactive initiative Symbiotic human-machine interaction (ICT-2013-10) through the Project SYMBITRON under Project 611626, in part by the VICI Flexible Robotic Suit Project, and in part by the Netherlands Organisation for Scientific Research (NWO) under Grant 14429
Publisher Copyright:
© 2001-2011 IEEE.
Financial transaction number:
342160814
PY - 2021/11/30
Y1 - 2021/11/30
N2 - Active prosthetic and orthotic devices have the potential to increase quality of life for individuals with impaired mobility. However, more research into human-like control methods is needed to create seamless interaction between device and user. In forward simulations the reflex-based neuromuscular model (RNM) by Song and Geyer shows promising similarities with real human gait in unperturbed conditions. The goal of this work was to validate and, if needed, extend the RNM to reproduce human kinematics and kinetics during walking in unperturbed and perturbed conditions. The RNM was optimized to reproduce joint torque, calculated with inverse dynamics, from kinematic and force data of unperturbed and perturbed treadmill walking of able-bodied human subjects. Torques generated by the RNM matched closely with torques found from inverse dynamics analysis on human data for unperturbed walking. However, for perturbed walking the modulation of the ankle torque in the RNM was opposite to the modulation observed in humans. Therefore, the RNM was extended with a control module that activates and inhibits muscles around the ankle of the stance leg, based on changes in whole body center of mass velocity. The added module improves the ability of the RNM to replicate human ankle torque response in response to perturbations. This reflex-based neuromuscular model with whole body center of mass velocity feedback can reproduce gait kinetics of unperturbed and perturbed gait, and as such holds promise as a basis for advanced controllers of prosthetic and orthotic devices.
AB - Active prosthetic and orthotic devices have the potential to increase quality of life for individuals with impaired mobility. However, more research into human-like control methods is needed to create seamless interaction between device and user. In forward simulations the reflex-based neuromuscular model (RNM) by Song and Geyer shows promising similarities with real human gait in unperturbed conditions. The goal of this work was to validate and, if needed, extend the RNM to reproduce human kinematics and kinetics during walking in unperturbed and perturbed conditions. The RNM was optimized to reproduce joint torque, calculated with inverse dynamics, from kinematic and force data of unperturbed and perturbed treadmill walking of able-bodied human subjects. Torques generated by the RNM matched closely with torques found from inverse dynamics analysis on human data for unperturbed walking. However, for perturbed walking the modulation of the ankle torque in the RNM was opposite to the modulation observed in humans. Therefore, the RNM was extended with a control module that activates and inhibits muscles around the ankle of the stance leg, based on changes in whole body center of mass velocity. The added module improves the ability of the RNM to replicate human ankle torque response in response to perturbations. This reflex-based neuromuscular model with whole body center of mass velocity feedback can reproduce gait kinetics of unperturbed and perturbed gait, and as such holds promise as a basis for advanced controllers of prosthetic and orthotic devices.
KW - Human gait
KW - Neuromuscular control
KW - Orthotics
KW - Prosthetics
KW - Reflex modeling
UR - http://www.scopus.com/inward/record.url?scp=85121842458&partnerID=8YFLogxK
U2 - 10.1109/TNSRE.2021.3131366
DO - 10.1109/TNSRE.2021.3131366
M3 - Article
AN - SCOPUS:85121842458
SN - 1534-4320
VL - 29
SP - 2521
EP - 2529
JO - IEEE transactions on neural systems and rehabilitation engineering
JF - IEEE transactions on neural systems and rehabilitation engineering
ER -