Electromyography-driven musculoskeletal models with time-varying fatigue dynamics improve lumbosacral joint moments during lifting

Mohamed Refai, Mohamed Irfan; Moya-Esteban, Alejandro; Sartori, Massimo

doi:10.1016/j.jbiomech.2024.111987

Cited by 3 publications

(1 citation statement)

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“…Over the past decade, there has been a growing interest in integrating muscle fatigue into predictive models for task accomplishment which reflects a significant emphasis on injury prevention in both sports and workplace settings. As a result, several studies have utilized the flexibility of the 3CC model by integrating it into their simulations of muscle force at the joint level ( Barman et al, 2022 ; Sonne and Potvin, 2016 ), or by accounting for redundant muscle forces within a multibody environment ( Michaud et al, 2023 ; Mohamed Refai et al, 2024 ; Pereira et al, 2011 ). While the 3CC approach has been evaluated and validated ( Liu et al, 2002 ; Looft et al, 2018 ; Lugrís et al, 2023 ), the authors of this paper identified limitations when applying this model to predict muscles forces for short-duration high-intensity exercise ( Michaud et al, 2023 ).…”

Section: Introductionmentioning

confidence: 99%

Four-compartment muscle fatigue model to predict metabolic inhibition and long-lasting nonmetabolic components

Michaud,

Beron,

Lugrís

et al. 2024

Front. Physiol.

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Introduction: Computational muscle force models aim to mathematically represent the mechanics of movement and the factors influencing force generation. These tools allow the prediction of the nonlinear and task-related muscle behavior, aiding biomechanics, sports science, and rehabilitation. Despite often overlooking muscle fatigue in low-force scenarios, these simulations are crucial for high-intensity activities where fatigue and force loss play a significant role. Applications include functional electrical stimulation, motor control, and ergonomic considerations in diverse contexts, encompassing rehabilitation and the prevention of injuries in sports and workplaces.Methods: In this work, the authors enhance the pre-existing 3CCr muscle fatigue model by introducing an additional component of force decay associated with central fatigue and a long-term fatigue state. The innovative four-compartment model distinguishes between the short-term fatigued state (related to metabolic inhibition) and the long-term fatigued state (emulating central fatigue and potential microtraumas).Results: Its validation process involved experimental measurements during both short- and long-duration exercises, shedding light on the limitations of the traditional 3CCr in addressing dynamic force profiles.

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Section: Introductionmentioning

confidence: 99%

Four-compartment muscle fatigue model to predict metabolic inhibition and long-lasting nonmetabolic components

Michaud,

Beron,

Lugrís

et al. 2024

Front. Physiol.

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Hill-type models of skeletal muscle and neuromuscular actuators: a systematic review

Caillet

Phillips

Carty

et al. 2022

Preprint

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Backed by a century of research and development, Hill-type muscle-tendon models are extensively used for countless applications. Lacking recent reviews, the field of Hill-type modelling is however dense and hard-to-explore, with detrimental consequences on knowledge transmission, inter-study consistency, and innovation. Here we present the first systematic review of the field of Hill-type muscle-tendon modelling. It aims to clarify the literature by detailing its contents and proposing updated terminology and definitions, and discussing the state-of-the-art by identifying the latest advances, current gaps, and potential improvements in modelling muscle properties. To achieve this aim, fifty-five criteria-abiding studies were extracted using a systematic search and their Hill-type models assessed according to a completeness evaluation, which identified the modelled muscle-tendon properties, and a modelling evaluation, which considered the level of validation and reusability of the model, and attention given to its modelling strategy and calibration. It is concluded that most models (1) do not significantly advance the dated gold standards in muscle modelling and do not build upon more recent advances, (2) overlook the importance of parameter identification and tuning, (3) are not strongly validated, and (4) are not reusable in other studies. Besides providing a convenient tool supported by extensive supplementary material for understanding the literature, the results of this review open a discussion on the necessity for global recommendations in Hill-type modelling and more frequent reviews to optimize inter-study consistency, knowledge transmission and model reusability.

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Towards Wearable Electromyography for Personalized Musculoskeletal Trunk Models using an Inverse Synergy-based Approach

Rook,

Sartori,

Refai

2024

Preprint

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Electromyography (EMG)-driven musculoskeletal models (EMS) of the trunk are used for estimating lumbosacral joint moments and compressive loads during lifting tasks. These models provide personalized estimates of the parameters using information from many sensors. However, to advance technology from labs to workplaces, there is a need for sensor reduction to improve wearability and applicability. Therefore we introduce an EMG sensor reduction approach based on inverse synergy extrapolation, to reconstruct unmeasured EMG signals for different box-lifting techniques. 12 participants performed an array of tasks (squat, stoop, unilateral twist and bilateral twist) with different weights (0 kg, 7.5 kg and 15 kg). We found that two synergies were sufficient to explain the different lifting tasks (median variance accounted for of 0.91). Building upon this, we used two sensors at optimal subject-specific muscle locations to reconstruct the EMG of four unmeasured channels. Evaluation of the reconstructed and reference EMG showed median coefficients of determination (R2) between 0.70 and 0.86, with median root mean squared errors (RMSE) ranging from 0.02 to 0.04 relative to maximal voluntary contraction. This indicates that our proposed method shows promise for sensor reduction for driving a trunk EMS for ambulatory biomechanical risk assessment in occupational settings and exoskeleton control.

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Electromyography-driven musculoskeletal models with time-varying fatigue dynamics improve lumbosacral joint moments during lifting

Cited by 3 publications

References 50 publications

Four-compartment muscle fatigue model to predict metabolic inhibition and long-lasting nonmetabolic components

Four-compartment muscle fatigue model to predict metabolic inhibition and long-lasting nonmetabolic components

Hill-type models of skeletal muscle and neuromuscular actuators: a systematic review

Towards Wearable Electromyography for Personalized Musculoskeletal Trunk Models using an Inverse Synergy-based Approach

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