Skeletal muscle models composed of motor units: A review

Raikova, Rositsa; Krutki, Piotr; Celichowski, Jan

doi:10.1016/j.jelekin.2023.102774

Cited by 9 publications

(6 citation statements)

References 72 publications

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“…While this study presents novel techniques to develop state-of-the-art neuromuscular models as MN-driven pools of MU Hill-type actuators, it remains to assess the performance of these more physiological and complex models compared to the more common phenomenological single-input single-actuator approaches, like the standard bEMG-driven Hill-type models (Pizzolato et al, 2015). Almost no studies that proposed models of MU pools performed this comparative assessment, which was therefore never reviewed (Raikova et al, 2023). Only two studies compared, for limited contraction tasks, the force outputs of a model of MU pool and of a single muscle-scale model, using Hill-type (Hatze, 1978) and twitch-type (Thompson et al, 2018) approaches.…”

Section: Discussionmentioning

confidence: 99%

Motoneuron-driven computational muscle modelling with motor unit resolution and subject-specific musculoskeletal anatomy

Caillet

Phillips

Farina

et al. 2023

Preprint

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The computational simulation of human voluntary muscle contraction is possible with EMG-driven Hill-type models of whole muscles. Despite impactful applications in numerous fields, the neuromechanical information and the physiological accuracy such models provide remain limited because of multiscale simplifications that limit comprehensive description of muscle internal dynamics during contraction. We addressed this limitation by developing a novel motoneuron-driven neuromuscular model, that describes the force-generating dynamics of a population of individual motor units, each of which was described with a Hill-type actuator and controlled by a dedicated experimentally derived motoneuronal control. In forward simulation of human voluntary muscle contraction, the model transforms a vector of motoneuron spike trains decoded from high-density EMG signals into a vector of motor unit forces that sum into the predicted whole muscle force. The control of motoneurons provides comprehensive and separate descriptions of the dynamics of motor unit recruitment and discharge and decode the subject's intention. The neuromuscular model is subject-specific, muscle-specific, includes an advanced and physiological description of motor unit activation dynamics, and is validated against an experimental muscle force. Accurate force predictions were obtained when the vector of experimental neural controls was representative of the discharge activity of the complete motor unit pool. This was achieved with large and dense grids of EMG electrodes during medium-force contractions or with computational methods that physiologically estimate the discharge activity of the motor units that were not identified experimentally. This neuromuscular model advances the state-of-the-art of neuromuscular modelling, bringing together the fields of motor control and musculoskeletal modelling, and finding applications in neuromuscular control and human-machine interfacing research.

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Section: Discussionmentioning

confidence: 99%

Motoneuron-driven computational muscle modelling with motor unit resolution and subject-specific musculoskeletal anatomy

Caillet

Phillips

Farina

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…While this study presents novel techniques to develop state-of-the-art neuromuscular models as MN-driven pools of MU Hill-type actuators, it remains to assess the performance of these more physiological and complex models compared to the more common phenomenological single-input single-actuator approaches, like the standard bEMG-driven Hill-type models [ 21 ]. Almost no studies that proposed models of MU pools performed this comparative assessment, which was therefore never reviewed [ 99 ]. Only three studies compared, for limited contraction tasks, the force outputs of a model of MU pool and of a single muscle-scale model, using Hill-type [ 100 ] and twitch-type [ 91 , 96 ] approaches.…”

Section: Discussionmentioning

confidence: 99%

Motoneuron-driven computational muscle modelling with motor unit resolution and subject-specific musculoskeletal anatomy

Caillet,

Phillips,

Farina

et al. 2023

PLoS Comput Biol

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The computational simulation of human voluntary muscle contraction is possible with EMG-driven Hill-type models of whole muscles. Despite impactful applications in numerous fields, the neuromechanical information and the physiological accuracy such models provide remain limited because of multiscale simplifications that limit comprehensive description of muscle internal dynamics during contraction. We addressed this limitation by developing a novel motoneuron-driven neuromuscular model, that describes the force-generating dynamics of a population of individual motor units, each of which was described with a Hill-type actuator and controlled by a dedicated experimentally derived motoneuronal control. In forward simulation of human voluntary muscle contraction, the model transforms a vector of motoneuron spike trains decoded from high-density EMG signals into a vector of motor unit forces that sum into the predicted whole muscle force. The motoneuronal control provides comprehensive and separate descriptions of the dynamics of motor unit recruitment and discharge and decodes the subject’s intention. The neuromuscular model is subject-specific, muscle-specific, includes an advanced and physiological description of motor unit activation dynamics, and is validated against an experimental muscle force. Accurate force predictions were obtained when the vector of experimental neural controls was representative of the discharge activity of the complete motor unit pool. This was achieved with large and dense grids of EMG electrodes during medium-force contractions or with computational methods that physiologically estimate the discharge activity of the motor units that were not identified experimentally. This neuromuscular model advances the state-of-the-art of neuromuscular modelling, bringing together the fields of motor control and musculoskeletal modelling, and finding applications in neuromuscular control and human-machine interfacing research.

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“…A sum of many surface MUAPs from different discharging motor units results in signals with stochastic characteristics, which are referred to as surface EMG interference pattern signals [ 4 ]. Morphologies of MUAP waveforms and their patterns of discharge determine stochastic properties of surface EMG interference pattern signals [ 4 , 16 , 17 ], and thus should be carefully modeled [ 12 , 18 ]. Specifically, De Luca and colleagues have demonstrated that the surface EMG power spectrum at frequencies higher than 20 Hz is mostly determined by the morphologies of MUAPs [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

Spectral characterization of human leg EMG signals from an open access dataset for the development of computational models

de Freitas,

Kohn

2024

PLoS ONE

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Large-scale neuromusculoskeletal models have been used for predicting mechanisms underlying neuromuscular functions in humans. Simulations of such models provide several types of signals of practical interest, such as surface electromyographic signals (EMG), which are compared with experimental data for interpretations of neurophysiological phenomena under study. Specifically, realistic characterization of spectral properties of simulated EMG signals is important for achieving powerful inferences, whereas considerations should be taken for myoelectric signals of different muscles. In this study, we characterized spectral properties of surface interference pattern EMG signals and motor unit action potentials (MUAP) acquired from three plantar flexor muscles: Soleus (SO), Medial Gastrocnemius (MG), and Lateral Gastrocnemius (LG); and one dorsiflexor muscle: Tibialis Anterior (TA). Surface EMG signals were acquired from 20 participants using the same convention for electrode placement. Specifically, interference pattern EMG signals were obtained during isometric constant force contractions at 5%, 10% and 20% of maximum voluntary contraction (MVC), whereas surface MUAPs were decomposed from surface EMG signals obtained at low contraction forces. We compared the spectrum median frequency (MDF) estimated from interference pattern EMG signals across muscles and contraction intensities. Additionally, we compared MDF and durations of MUAPs between muscles. Our results showed that MDF of interference pattern EMG signals acquired from TA were higher compared to SO, MG, and LG for all contraction intensities i.e., 5%, 10%, and 20% MVC. Consistently, MUAPs acquired from TA also had higher MDF values and shorter durations compared to the other leg muscles. We provide herein a dataset with the surface MUAPs waveforms and interference pattern EMG signals obtained for this study, which should be useful for implementing and validating the simulation of myoelectrical signals of leg muscles. Importantly, these results indicate that spectral properties of myoelectrical signals should be considered for improving EMG modeling in large-scale neuromusculoskeletal models.

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Skeletal muscle models composed of motor units: A review

Cited by 9 publications

References 72 publications

Motoneuron-driven computational muscle modelling with motor unit resolution and subject-specific musculoskeletal anatomy

Motoneuron-driven computational muscle modelling with motor unit resolution and subject-specific musculoskeletal anatomy

Motoneuron-driven computational muscle modelling with motor unit resolution and subject-specific musculoskeletal anatomy

Spectral characterization of human leg EMG signals from an open access dataset for the development of computational models

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