Is there a reliable and invariant set of muscle synergy during isometric biaxial trunk exertion in the sagittal and transverse planes by healthy subjects?

Sedaghat-Nejad, Ehsan; Mousavi, Seyed Javad; Hadizadeh, Maliheh; Narimani, Roya; Khalaf, Kinda; Campbell-Kyureghyan, Naira; Parnianpour, Mohamad

doi:10.1016/j.jbiomech.2015.06.032

Cited by 13 publications

(7 citation statements)

References 42 publications

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“…For example, Tan et al [19] showed that three synergies were sufficient to reconstruct EMG signals from eight muscles during stoop lifting. These synergies were time-invariant, which was also found by Sedaghat-Nejad et al [20] for isometric trunk exertions in 12 directions with equal 30-degree angular intervals in the transverse plane. Wang et al [21] used high-density EMG with 120 channels and found that only two muscle synergies could explain over 90% of recorded muscle activities in five spinal motions (flexion/extension, lateral bending, axial rotation, sitting, and standing) for healthy subjects.…”

Section: Introductionsupporting

confidence: 79%

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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Section: Introductionsupporting

confidence: 79%

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

Rook,

Sartori,

Refai

2024

Preprint

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“…The recruitment of trunk muscles has been shown to be strongly direction dependent (Nussbaum et al, 1995;Hadizadeh et al, 2014;Sedaghat-Nejad et al, 2015;Eskandari et al, 2016). In quasi-static conditions the emergent synergies responsible for a direction of external load will be linearly scaled.…”

Section: Interpretationsmentioning

confidence: 99%

Estimation of Trunk Muscle Forces Using a Bio-Inspired Control Strategy Implemented in a Neuro-Osteo-Ligamentous Finite Element Model of the Lumbar Spine

Sharifzadeh-Kermani

Arjmand

Vossoughi

et al. 2020

Front. Bioeng. Biotechnol.

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“…For instance, four to five synergies were required to predict upper extremity muscle activation across different spatial, load, and position protocols ( Roh et al, 2012 ), and during visuomotor adaptation ( Gentner et al, 2013 ). Also, a set of three or four trunk synergies could efficiently explain electromyographic (EMG) data during multidirectional target-matching conditions and two different maximum voluntary exertion tasks ( Sedaghat-Nejad et al, 2015 ). Therefore, these studies have shown the robustness of muscle synergies across different isometric conditions in neurologically intact persons.…”

Section: Introductionmentioning

confidence: 99%

Generalizability of muscle synergies in isometric force generation versus point-to-point reaching in the human upper extremity workspace

Pham,

Portilla-Jiménez,

Roh

2023

Front. Hum. Neurosci.

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Isometric force generation and kinematic reaching in the upper extremity has been found to be represented by a limited number of muscle synergies, even across task-specific variations. However, the extent of the generalizability of muscle synergies between these two motor tasks within the arm workspace remains unknown. In this study, we recorded electromyographic (EMG) signals from 13 different arm, shoulder, and back muscles of ten healthy individuals while they performed isometric and kinematic center-out target matches to one of 12 equidistant directional targets in the horizontal plane and at each of four starting arm positions. Non-negative matrix factorization was applied to the EMG data to identify the muscle synergies. Five and six muscle synergies were found to represent the isometric force generation and point-to-point reaches. We also found that the number and composition of muscle synergies were conserved across the arm workspace per motor task. Similar tuning directions of muscle synergy activation profiles were observed at different starting arm locations. Between the isometric and kinematic motor tasks, we found that two to four out of five muscle synergies were common in the composition and activation profiles across the starting arm locations. The greater number of muscle synergies that were involved in achieving a target match in the reaching task compared to the isometric task may explain the complexity of neuromotor control in arm reaching movements. Overall, our results may provide further insight into the neuromotor compartmentalization of shared muscle synergies between two different arm motor tasks and can be utilized to assess motor disabilities in individuals with upper limb motor impairments.

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Is there a reliable and invariant set of muscle synergy during isometric biaxial trunk exertion in the sagittal and transverse planes by healthy subjects?

Cited by 13 publications

References 42 publications

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

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

Estimation of Trunk Muscle Forces Using a Bio-Inspired Control Strategy Implemented in a Neuro-Osteo-Ligamentous Finite Element Model of the Lumbar Spine

Generalizability of muscle synergies in isometric force generation versus point-to-point reaching in the human upper extremity workspace

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