A planar neuromuscular controller to simulate age-related adaptation strategies in the sit-to-walk movement

Abstract

Standing up from a chair is a key daily life activity that is sensitive to functional limitations as we age and therefore associated with falls, frailty, and institutional living. Predictive neuromusculoskeletal models can potentially shed light on the interconnectivity and interdependency of age-related changes in neuromuscular capacity, reinforcement schemes, sensory integration, and adaptation strategies during stand up. Most stand-up movements transfer directly into walking (sit-to-walk). The aim of this study was to develop and validate a neuromusculoskeletal model with reflex-based muscle control that enables simulation of the sit-to-walk movement, under various conditions (seat height, foot placement), reduced muscular capacity, reduced neural capacity, and altered movement objectives. We developed a planar sit-to-walk musculoskeletal model (11 degrees-of-freedom, 20 muscles) and neuromuscular controller, consisting of a two-phase stand-up controller and a reflex-based gait controller. The stand-up controller contains generic neural pathways of delayed proprioceptive feedback from muscle length, force, velocity, and upper-body orientation (vestibular feedback) and includes both monosynaptic an antagonistic feedback pathways. The control parameters where optimized using a shooting-based optimization method. Simulations were compared to recorded kinematics, ground reaction forces, and muscle activation from young and older adults. The simulated kinematics closely resemble the measured kinematics and muscle activations, and the adaptation strategies, that resulted from alterations in seat height, are comparable to those observed in adults. The simulation framework and model are publicly available.Author SummaryAgeing affects the human neuromusculoskeletal system, which consists of that is muscles, bones, joints, nerves, and associated tissues. Since the human body had physiological and functional redundancy, humans will adopt their movement to compensate for these initial losses. Adaptation strategies affect joint loading, stability, and may lead to structural underuse of specific muscles, which especially in older adults leads to an accelerated decline of the underused part of their muscular system. Early detection can mitigate development of permanent movement impairments, but clinicians and scientists do not yet understand the course of compensatory muscle recruitment, and it is unclear how much decline can be tolerated before movement limitations begin. In experimental studies it is not possible to identify the effects of specific intrinsic properties; we therefore developed a generic neuromusculoskeletal model that can realistically simulate the effect of age-related changes in the neuromuscular system on daily life activity. Since standing up is a key daily life movement, we have focused on this movement, specifically sit-to-walk. We formulated a planar neuromuscular model driven by muscle reflexes and used optimization to design realistic controllers. We validated the simulations against experimental data.

Is increased trunk flexion in standing up related to muscle weakness or pain avoidance in individuals with unilateral knee pain?; a simulation study

“…Our simulations reveal increased trunk flexion in response to a decrease in maximum isometric force in VAS (representing reduced muscular capacity). This result aligns with the notion that an increased task demand, such as reduced seat height, leads to greater trunk flexion before seat-off [12], [14]. Pain avoidance, simulated with the objective of reducing knee load, resulted in altered muscle recruitments, characterized by reduced ipsilateral activation of VAS and HAM, and slower movement speeds.…”

“…In the neutral condition, the peak knee loads (stance leg: 6.8 BW, stepping leg: 5.6 BW) and hip loads (stance leg: 3.6 BW, stepping leg: 3.4 BW) manifest just after seat-off. The peak ankle load in the stepping leg occurs during the double stance (rising) phase (stepping leg: 1.3 BW), and for stance leg, it arises at the end of the single stance phase (stance leg: 2.4 BW), consistent with experimental data [14].…”

“…The design and validation of the musculoskeletal model and controller have been previously published [14]. We employed the H1120 model, featuring 11 degrees of freedom and 20 Hill-type muscles, which was initially developed as an OpenSim3 model and translated into Hyfydy (Fig.…”

“…Contact forces between the feet and the ground and between the buttocks and the chair were modelled with a Hunt Crossley force spheres and box, respectively. The simulation of the sit-to-walk movement involved the utilization of a standing-up controller [14] followed by a gait controller [17].…”

“…To simulate reduced muscular capacity in knee extension, we systematically bilaterally decreased the vasti (VAS) maximum isometric force by 20%, 30%, 40%, 50%, and 60%. We initiated the model with the optimized sit-to-walk controller for the standard seat [14] (neutral condition). The best set of the reduced model was then employed as the starting point for the subsequent optimization, replicating a progressive capacity decline scenario.…”