# Are Torque-Driven Simulation Models of Human Movement Limited by an Assumption of Monoarticularity?
## 4 Discussion  
The aim of this study was to investigate whether the incorporation of TJ torque generators in addition to SJ torque generators in a computer simulation model improves accuracy when simulating maximal squat jumps and countermovement jumps. It was found that the use of subject-specific TJ representations of lower-limb joint torques rather than SJ representations resulted in smaller differences between the simulation model and measured performances for both squat and countermovement jumps. The magnitude of the differences was small for the submaximal descent of the countermovement and large for movements requiring larger joint torques and a requirement for large joint velocities (e.g., Figures 6 and 7). The SJ model was unable to match closely the work or maximal joint velocities of measured squat or countermovement jumps, something achieved with better accuracy by a TJ model. It has been proposed that the monoarticular assumption might result in a model with insufficient ability to generate work when it must achieve this throughout the simulation [31]. In this study, the TJ model increased the mechanical energy throughout the simulation by 659 J (squat) and 457 J (countermovement), while the SJ model increased the mechanical energy by 557 J (squat) and 372 J (countermovement). This highlights the dual insufficiency of an SJ model to perform sufficient work compared to a TJ model, along with an inability to match high velocity joint kinematics. The results of this investigation have demonstrated performance differences for the squat and countermovement jump simulations, when employing SJ or TJ torque generators. The differences were associated with the ascent phase of both jumps, but not with the submaximal descent phase of the countermovement jump (Table 7). The overall difference between simulation and matched performances were smaller for SJ (10%) and TJ (6%) simulations of squat jumping than for the ascent phase of the countermovement jump (SJ 24% and TJ 10%). The predominant contributors to these differences were joint kinematics and vertical velocity at take-off. Previous torque and individual muscle-driven simulations of jumping, with and without a countermovement, have placed less emphasis on matching the kinematics throughout the jump. Instead, they have adopted objective functions which require the simulation to achieve specific kinematic values at critical instants, e.g., specific joint configurations such as greatest drop depth, and take-off characteristics [31]. As a consequence, the joint velocity characteristics of the model and coordination between joints has been included very simplistically in the overall evaluation. The present study offers some wider insight into the capacity of each joint to match the technical requirements for jumping. Submaximal activities such as the descent phase of a countermovement jump may be modelled with similar accuracy by SJ and TJ simulation models, with large differences only arising for maximal jumping activity in the ascent phase. When simulating the submaximal descent phase of a countermovement jump, both simulation approaches achieved comparable agreement with measured kinematics and kinetics. The agreement was very good, and it is likely that the capacity of both models to generate work and provide adequate degrees of freedom to provide fine control of slow movements is good. However, the maximal effort of the squat jump and ascent phase of the countermovement jump highlighted much larger differences in the capacity of an SJ or TJ model to match measured kinematics. Overall a TJ approach better matched the performance outcome, in terms of the height attained by the mass centre, and the technique employed. A clear advantage for the TJ model was found