Are Joint Torque Models Limited by an Assumption of Monoarticularity?

Lewis, Martin; King, Mark A.; Yeadon, Maurice R.; Conceição, Filipe

doi:10.1123/jab.28.5.520

Cited by 8 publications

(16 citation statements)

References 43 publications

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“… Subject-specific parameters: inertia parameters calculated from anthropometric measurements on the participant (Yeadon, 1990); joint torque parameters determined from strength measurements on the participant (King, Lewis and Yeadon, 2012;Lewis, King, Yeadon, and Conceicao, 2012).  Model input: initial kinematic conditions at the start of the upward motion of the mass centre; torque activation profiles for each of the torque generators.…”

Section: Vertical Jumpingmentioning

confidence: 99%

Advances in the development of whole body computer simulation modelling of sports technique

King¹,

Yeadon²

2015

Movement &Amp; Sport Sciences

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Computer simulation models have been used to address a range of research questions in sports biomechanics related to understanding the mechanics of sports movements, contributions to performance, optimisation of sports technique and control of sports movements. This paper will describe how theoretical models used in sports biomechanics have been developed at Loughborough University over the last 20 years, detailing their various components, subject-specific parameters, model evaluation, key findings and the strengths / limitations and how models could be further progressed in the future. With each model a four stage methodology has been used to answer specific research questions: development of the simulation model, determination of subjectspecific parameters, evaluation of the model, and application of the model. These computer simulation models have provided insight into the mechanics behind sports movements that would not be possible through observing performance and have established the factors that limit optimal performance. In the future computer simulation models of sports movements will continue to develop in terms of sophistication to include elements such as joint compression and will provide further insight into the mechanics underlying sports movements.

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Section: Vertical Jumpingmentioning

confidence: 99%

Advances in the development of whole body computer simulation modelling of sports technique

King¹,

Yeadon²

2015

Movement &Amp; Sport Sciences

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“…The contribution from monoarticular muscles was calculated by subtracting the active biarticular torque contribution from the measured total joint torque for both hip flexion and hip extension (Appendix B). (rad), minimum muscle activation, amin, activation rate, m and point of inflexion ω1 (rad.s -1 ), and moment arm ratio R. All were derived from isokinetic dynamometer measurements made on the same participant as in this study (see King et al (2012) and Lewis et al (2012)). …”

Section: Methodsmentioning

confidence: 99%

The effect of accounting for biarticularity in hip flexor and hip extensor joint torque representations

Lewis

Yeadon

King

2018

Human Movement Science

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Subject-specific torque-driven models have ignored biarticular effects at the hip. The aim of this study was to establish the contribution of monoarticular hip flexors and hip extensors to total hip flexor and total hip extensor joint torques for an individual and to investigate whether torque-driven simulation models should consider incorporating biarticular effects at the hip joint. Maximum voluntary isometric and isovelocity hip flexion and hip extension joint torques were measured for a single participant together with surface electromyography. Single-joint and two-joint representations were fitted to the collected torque data and used to determine the maximum voluntary joint torque capacity. When comparing two-joint and single-joint representations, the single-joint representation had the capacity to produce larger maximum voluntary hip flexion torque (larger by around 9% of maximum torque) and smaller maximum voluntary hip extension torque (smaller by around 33% of maximum torque) with the knee extended. Considering the range of kinematics found for jumping movements, the single-joint hip flexors had the capacity to produce around 10% additional torque, while the single joint hip extensors had about 70% of the capacity of the two-joint representation. Two-joint representations may overcome an over-simplification of single-joint representations by accounting for biarticular effects, while building on the strength of determining subject-specific parameters from measurements on the participant.

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“…Again the function was only implicitly shown to be successful through scaling of voluntary EMG signals (Pain & Forrester, 2009). Therefore, although now used repeatedly (Lewis et al 2012;Forrester et al, 2011;Tillin et al, 2012;Pain et al, 2013) in the literature the DIFACT function has yet to be verified in an explicit way. The aims of this study were (i) to establish experimentally how well the DIFACT function follows the in vivo voluntary neural activation-angular velocity profiles in a group of subjects; and (ii) to test the robustness of the exponential DIFACT function to perturbed upper levels of maximal activation.…”

Section: Introductionmentioning

confidence: 99%

Modelling suppressed muscle activation by means of an exponential sigmoid function: Validation and bounds

Voukelatos

Pain

2015

Journal of Biomechanics

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The aim of this study was to establish how well a three-parameter sigmoid exponential function, DIFACT, follows experimentally obtained voluntary neural activation-angular velocity profiles and how robust it is to perturbed levels of maximal activation. Six male volunteers (age 26.3 ± 2.73 years) were tested before and after an 8-session, 3-week training protocol. Torque-angular velocity (T-ω) and experimental voluntary neural drive-angular velocity (%VA-ω) datasets, obtained via the interpolated twitch technique, were determined from pre-and post-training testing sessions. Non-linear regression fits of the product of DIFACT and a Hill type tetanic toque function and of the DIFACT function only were performed on the pre-and post-training T-ω and %VA-ω datasets for three different values of the DIFACT upper bound, α max , 100%, 95% & 90%. The determination coefficients, R 2 , and the RMS of the fits were compared using a two way mixed ANOVA and results showed that there was no significant difference (p < 0.05) due to changing α max values indicating the DIFACT remains robust to changes in maximal activation. Mean R 2 values of 0.95 and 0.96 for pre-and post-training sessions show that the maximal voluntary torque function successfully reproduces the T-ω raw dataset.

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Are Joint Torque Models Limited by an Assumption of Monoarticularity?

Cited by 8 publications

References 43 publications

Advances in the development of whole body computer simulation modelling of sports technique

Advances in the development of whole body computer simulation modelling of sports technique

The effect of accounting for biarticularity in hip flexor and hip extensor joint torque representations

Modelling suppressed muscle activation by means of an exponential sigmoid function: Validation and bounds

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