Evaluation of musculoskeletal modelling parameters of the shoulder complex during humeral abduction above 90°

Aurbach, Maximilian; Špička, Jan; Süß, Franz; Dendorfer, Sebastian

doi:10.1016/j.jbiomech.2020.109817

Cited by 7 publications

(4 citation statements)

References 26 publications

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“…This shifts the bulk of non-linearities in the transformation from the monosynaptic Ia feedback to EMG toward other synaptic inputs, such as spinal interneuronal and descending inputs discussed above. Moreover, the non-linearities in the transformation from the activity of a motoneuron pool to EMG are likely to be minimal in the low range of ~ 5-10% of maximal voluntary contraction during reaching 38,39 examined here. At that range, the rate coding of recruited motor units is likely to drive linearly the EMG amplitude and, thus, muscle force 36 .…”

Section: Discussionmentioning

confidence: 88%

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Computational evidence for nonlinear feedforward modulation of fusimotor drive to antagonistic co-contracting muscles

Hardesty

Boots

Yakovenko

et al. 2020

Sci Rep

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the sensorimotor integration during unconstrained reaching movements in the presence of variable environmental forces remains poorly understood. the objective of this study was to quantify how much the primary afferent activity of muscle spindles can contribute to shaping muscle coactivation patterns during reaching movements with complex dynamics. to achieve this objective, we designed a virtual reality task that guided healthy human participants through a set of planar reaching movements with controlled kinematic and dynamic conditions that were accompanied by variable muscle co-contraction. Next, we approximated the Ia afferent activity using a phenomenological model of the muscle spindle and muscle lengths derived from a musculoskeletal model. the parameters of the spindle model were altered systematically to evaluate the effect of fusimotor drive on the shape of the temporal profile of afferent activity during movement. The experimental and simulated data were analyzed with hierarchical clustering. We found that the pattern of co-activation of agonistic and antagonistic muscles changed based on whether passive forces in each movement played assistive or resistive roles in limb dynamics. the reaching task with assistive limb dynamics was associated with the most muscle co-contraction. In contrast, the simulated Ia afferent profiles were not changing between tasks and they were largely reciprocal with homonymous muscle activity. Simulated physiological changes to the fusimotor drive were not sufficient to reproduce muscle co-contraction. These results largely rule out the static set and α-γ coactivation as the main types of fusimotor drive that transform the monosynaptic Ia afferent feedback into task-dependent co-contraction of antagonistic muscles. We speculate that another type of nonlinear transformation of Ia afferent signals that is independent of signals modulating the activity of α motoneurons is required for Ia afferent-based co-contraction. This transformation could either be applied through a complex nonlinear profile of fusimotor drive that is not yet experimentally observed or through presynaptic inhibition. Movement is the product of interactions between neural signals and the musculoskeletal dynamics that depends on limb anatomy 1-4. The motor control problem is then solved within a system with coupled neural and mechanical dynamical elements 5-7. Therefore, the relationship between neural signals driving muscle contraction and the resulting motion is nonlinear. Muscle contractions generate forces that sum into active moments defined by the agonistic or antagonistic relationships between the muscle's moment arms around a given axis of rotation of the joint. The components of these forces that sum to zero moment, such as forces produced by balanced

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Section: Discussionmentioning

confidence: 88%

“…We used electromyography (EMG) to estimate the ensemble activity of the motoneuron pool [35][36][37] . During reaching without heavy objects, the maximal EMG in arm muscles is estimated to be low, 5-10% of maximal voluntary contraction 38,39 . At that range, the relationship between EMG and the recruitment of motoneuron pool is largely linear 36 .…”

mentioning

confidence: 99%

Computational evidence for nonlinear feedforward modulation of fusimotor drive to antagonistic co-contracting muscles

Hardesty

Boots

Yakovenko

et al. 2020

Sci Rep

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“…The muscle model, which includes these forces, is the Hill-type model. Aurbach et al [29] recently showed that using the Hill-type model could be one key modeling parameter for simulation of the joint reaction forces within the shoulder. Particularly for the extrinsic muscles with long tendons, using the Hill-type model could be an essential part, which, however, offers significant possibilities for additional uncertainties within the model.…”

Section: Discussionmentioning

confidence: 99%

Electromyography-Based Validation of a Musculoskeletal Hand Model

Melzner

Engelhardt

Simon

et al. 2021

Journal of Biomechanical Engineering

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Regarding the prevention of injuries and rehabilitation of the human hand, musculoskeletal simulations using an inverse dynamics approach allow for insights of the muscle recruitment and thus acting forces on the hand. Currently, several hand models from various research groups are in use, which are mainly validated by the comparison of numerical and anatomical moment arms. In contrast to this validation and model-building technique by cadaver studies, the aim of the present study is to further validate a recently published hand model [1] by analyzing numerically calculated muscle activities in comparison to experimentally measured electromyographical signals of the muscles. Therefore, the electromyographical signals of 10 hand muscles of five test subjects performing seven different hand movements were measured. The kinematics of these tasks were used as input for the hand model, and the numerical muscle activities were computed. To analyze the relationship between simulated and measured activities, the time difference of the muscle on- and off-set points were calculated, which resulted in a mean on- and off-set time difference of 0.58 s between the experimental data and the model. The largest differences were detected for movements that mainly addressed the wrist. One major issue comparing simulated and measured muscle activities of the hand is cross-talk. Nevertheless, the results show that the hand model fits the experiment quite accurately despite some limitations and is a further step towards patient-specific modelling of the upper extremity.

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“…To provide a more realistic representation of shoulder forces, Hill-type muscles were used as muscle models in the simulation. Based on [ 19 ], not only the active muscle components but also passive components are thus considered. Furthermore, a predefined shoulder rhythm (_RHYTHM_SOFT_) for the arms was used, which contains a movement of the scapula and clavicle depending on the motion of the humerus [ 20 ].…”

Section: Methodsmentioning

confidence: 99%

Biomechanical analysis of the right elevated glenohumeral joint in violinists during legato-playing

Saffert

Melzner

Dendorfer

2021

THC

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BACKGROUND: Many statistics reveal that violin players suffer most often from musculoskeletal disorders compared to musicians of other instrument groups. A common phenomenon, especially observed in violin beginners, is the tendency to elevate the right shoulder during playing the violin. This can probably lead to serious disorders in long-term practice with repetitive movements. OBJECTIVE: For this reason, this study investigated the relationship between the right shoulder elevation and the force in the right glenohumeral joint during violin playing. It was hypothesized that the forces in the right glenohumeral joint are higher during playing with the right shoulder raised compared to playing in normal posture. METHODS: Motion capture data from four experienced violinists was recorded and processed by means of musculoskeletal simulation to get the force and elevation angle while playing with raised shoulder and in normal position. RESULTS: The results indicate that the absolute values of the resulting force, as well as the forces in the mediolateral, inferosuperior, and anteroposterior directions, are higher in playing the violin with the shoulder raised than in a normal posture. CONCLUSIONS: Elevating the right shoulder while playing the violin may pose a potential problem.

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Evaluation of musculoskeletal modelling parameters of the shoulder complex during humeral abduction above 90°

Cited by 7 publications

References 26 publications

Computational evidence for nonlinear feedforward modulation of fusimotor drive to antagonistic co-contracting muscles

Computational evidence for nonlinear feedforward modulation of fusimotor drive to antagonistic co-contracting muscles

Electromyography-Based Validation of a Musculoskeletal Hand Model

Biomechanical analysis of the right elevated glenohumeral joint in violinists during legato-playing

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