Musculoskeletal Model for Path Generation and Modification of an Ankle Rehabilitation Robot

Abstract

While newer designs and control approaches are being proposed for rehabilitation robots, vital information from the human musculoskeletal system should also be considered. Incorporating knowledge about joint biomechanics during the development of robot controllers can enhance the safety and performance of robot-aided treatments. In the present work, the optimal path or trajectories of a parallel ankle rehabilitation robot were generated by minimizing joint reaction moments and the tension along ligaments and muscle-tendon units. The simulations showed that using optimized robot paths, user efforts could be reduced to 80%, thereby ensuring less strain on weaker or stiffer ligaments, etc. Additionally, to limit the moments applied by the robot in stiff or constrained directions, the intended robot path was modified to move the commanded position in the direction opposite to that of the position error. Such online modification of the robot path can lead to a reduction in forces applied by a robot to the subject. Simulation results and experimental findings with healthy subjects using an ankle rehabilitation robot prototype and subsequent statistical analysis further validated that path modification based on ankle joint biomechanics results in a reduction in undesired forces experienced by human users during treatment. Index Terms-ankle joint musculoskeletal modeling, optimization of muscle forces, parallel ankle rehabilitation robot, robot path generation and modification I.

Uncertainty in Muscle–Tendon Parameters can Greatly Influence the Accuracy of Knee Contact Force Estimates of Musculoskeletal Models

“…Musculoskeletal models have been widely used to estimate in vivo loading conditions within the knee (Richards and Higginson, 2010;Worsley et al, 2011;Trepczynski et al, 2012;Gerus et al, 2013;Stylianou et al, 2013;Chen et al, 2016;Trepczynski et al, 2018;van Rossom et al, 2018;Imani Nejad et al, 2020). Outputs of musculoskeletal simulations can be used to predict postoperative functional outcomes of different surgeries (Barry et al, 2010;Chen et al, 2016), optimize rehabilitation protocols (Barry et al, 2010;Jamwal et al, 2020;Li et al, 2020), and enhance athletic performance (Heron, 2015;Langholz et al, 2016;Ataei et al, 2020;Seow et al, 2020). However, when musculoskeletal predictions of knee loads are compared against in vivo measurements, substantial errors are common (Lundberg et al, 2012;Valente et al, 2014;Charles et al, 2020;Koller et al, 2021), especially when generic models are used (e.g., errors of up to 150% for body-weight squat (Schellenberg et al, 2018;Imani Nejad et al, 2020)).…”

State of the art in parallel ankle rehabilitation robot: a systematic review

“…On this basis, a fuzzy-based disturbance observer (FBDO) was proposed to address the nonlinear characteristics of the PMA, and an adaptive fuzzy logic controller based on the Mamdani inference was developed and appended with the FBDO to compensate for the transient nature of the PMA, achieving very good trajectory tracking performance [ 49 ]. In addition, the optimal path of a PARR was calculated by minimizing the joint reaction moments and the tension along ligaments and muscle-tendon units, to help generate more reasonable rehabilitation training trajectories [ 50 ]. Using the CARR as the platform, Meng et al proposed a robust normalized iterative feedback tuning (NIFT) technique for its repetitive training control and proposed a multi-DOF normalized IFT technique to increase the controller robustness by obtaining an optimal value for the weighting factor and offering a method with learning capacity to determine optimal controller parameters [ 51 ].…”

Research on 4-UPUS Parallel Mechanism Ankle Joint Rehabilitation Training Robot

“…The survey shows that ankle joint injuries account for 7% to 10% of the total number of patients admitted to the emergency department every day [1][2][3][4]. Ankle fracture patients are more common clinically, and the incidence accounts for 4% to 5% of systemic fracture injuries [5][6].For the elderly, as the age increases, the flexibility of the limbs gradually decreases, and severe patients may have foot circulation disorders [7][8][9].Ankle sprains are also a common sports injury. It is difficult to conduct timely and standardized rehabilitation after ankle joint injury, and it is difficult to guarantee the duration of rehabilitation training.…”