Consistency of muscle synergies during pedaling across different mechanical constraints

2011 ◽  
Vol 106 (1) ◽  
pp. 91-103 ◽  
Author(s):  
François Hug ◽  
Nicolas A. Turpin ◽  
Antoine Couturier ◽  
Sylvain Dorel
Keyword(s):  
Neural Control ◽  
Muscle Synergy ◽  
Muscle Synergies ◽  
Mechanical Constraints ◽  
Relative Contribution ◽  
Lower Limb Muscles ◽  
Emg Patterns ◽  
Mean Variance ◽  
Relative Weighting ◽  
Non Negative Matrix Factorization

The purpose of the present study was to determine whether muscle synergies are constrained by changes in the mechanics of pedaling. The decomposition algorithm used to identify muscle synergies was based on two components: “muscle synergy vectors,” which represent the relative weighting of each muscle within each synergy, and “synergy activation coefficients,” which represent the relative contribution of muscle synergy to the overall muscle activity pattern. We hypothesized that muscle synergy vectors would remain fixed but that synergy activation coefficients could vary, resulting in observed variations in individual electromyographic (EMG) patterns. Eleven cyclists were tested during a submaximal pedaling exercise and five all-out sprints. The effects of torque, maximal torque-velocity combination, and posture were studied. First, muscle synergies were extracted from each pedaling exercise independently using non-negative matrix factorization. Then, to cross-validate the results, muscle synergies were extracted from the entire data pooled across all conditions, and muscle synergy vectors extracted from the submaximal exercise were used to reconstruct EMG patterns of the five all-out sprints. Whatever the mechanical constraints, three muscle synergies accounted for the majority of variability [mean variance accounted for (VAF) = 93.3 ± 1.6%, VAF muscle > 82.5%] in the EMG signals of 11 lower limb muscles. In addition, there was a robust consistency in the muscle synergy vectors. This high similarity in the composition of the three extracted synergies was accompanied by slight adaptations in their activation coefficients in response to extreme changes in torque and posture. Thus, our results support the hypothesis that these muscle synergies reflect a neural control strategy, with only a few timing adjustments in their activation regarding the mechanical constraints.

Is interindividual variability of EMG patterns in trained cyclists related to different muscle synergies?

2010 ◽  
Vol 108 (6) ◽  
pp. 1727-1736 ◽  
Author(s):  
François Hug ◽  
Nicolas A. Turpin ◽  
Arnaud Guével ◽  
Sylvain Dorel
Keyword(s):  
Interindividual Variability ◽  
Nonnegative Matrix ◽  
Rectus Femoris ◽  
Biceps Femoris ◽  
Surface Emg ◽  
Constant Load ◽  
Muscle Synergy ◽  
Muscle Synergies ◽  
Lower Limb Muscles ◽  
Emg Patterns

Our aim was to determine whether muscle synergies are similar across trained cyclists (and thus whether the same locomotor strategies for pedaling are used), despite interindividual variability of individual EMG patterns. Nine trained cyclists were tested during a constant-load pedaling exercise performed at 80% of maximal power. Surface EMG signals were measured in 10 lower limb muscles. A decomposition algorithm (nonnegative matrix factorization) was applied to a set of 40 consecutive pedaling cycles to differentiate muscle synergies. We selected the least number of synergies that provided 90% of the variance accounted for VAF. Using this criterion, three synergies were identified for all of the subjects, accounting for 93.5 ± 2.0% of total VAF, with VAF for individual muscles ranging from 89.9 ± 8.2% to 96.6 ± 1.3%. Each of these synergies was quite similar across all subjects, with a high mean correlation coefficient for synergy activation coefficients (0.927 ± 0.070, 0.930 ± 0.052, and 0.877 ± 0.110 for synergies 1– 3, respectively) and muscle synergy vectors (0.873 ± 0.120, 0.948 ± 0.274, and 0.885 ± 0.129 for synergies 1– 3, respectively). Despite a large consistency across subjects in the weighting of several monoarticular muscles into muscle synergy vectors, we found larger interindividual variability for another monoarticular muscle (soleus) and for biarticular muscles (rectus femoris, gastrocnemius lateralis, biceps femoris, and semimembranosus). This study demonstrated that pedaling is accomplished by the combination of the similar three muscle synergies among trained cyclists. The interindividual variability of EMG patterns observed during pedaling does not represent differences in the locomotor strategy for pedaling.

scholarly journals Flexible recruitments of fundamental muscle synergies in the trunk and lower limbs for highly variable movements and postures

2021 ◽  
Author(s):  
Hiroki Saito ◽  
Hikaru Yokoyama ◽  
Atsushi Sasaki ◽  
Tatsuya Kato ◽  
Kimitaka Nakazawa
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Neural Control ◽  
Static Stability ◽  
Neural Representation ◽  
Lower Limbs ◽  
Muscle Synergies ◽  
Lower Limb Muscles ◽  
The Central Nervous System ◽  
Almost All

The extent to which muscle synergies represent the neural control of human behavior remains unknown. Here, we tested whether certain sets of muscle synergies that are fundamentally necessary across behaviors exist. We measured the electromyographic activities of 26 muscles including bilateral trunk and lower limb muscles during 24 locomotion, dynamic and static stability tasks, and extracted the muscle synergies using non-negative matrix factorization. Our results showed that 13 muscle synergies that may have unique functional roles accounted for almost all 24 tasks by combinations of single and/or merging of synergies. Therefore, our results may support the notion of the low dimensionality in motor outputs, in which the central nervous system flexibly recruits fundamental muscle synergies to execute diverse human behaviors. Further studies using manipulations of the central nervous system and/or neural recording are required the neural representation with such fundamental components of muscle synergies.

scholarly journals Is the Neuromuscular Organization of Throwing Unchanged in Virtual Reality? Implications for Upper Limb Rehabilitation

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1495
Author(s):  
Emilia Scalona ◽  
Juri Taborri ◽  
Darren Richard Hayes ◽  
Zaccaria Del Prete ◽  
Stefano Rossi ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Healthy Subjects ◽  
Muscle Synergy ◽  
Muscle Synergies ◽  
Virtual Reality Environment ◽  
Upper Limb Rehabilitation ◽  
Deceleration Phase ◽  
Research Challenge ◽  
Limb Rehabilitation ◽  
Non Negative Matrix Factorization

Virtual reality (VR) is an appealing approach for increasing the engagement and attention of patients during rehabilitation. Understanding how motor control changes in real vs. virtual scenarios is a research challenge in terms of validating its administration. This study evaluates muscle synergies when subjects conduct throwing tasks in virtual reality. Seventeen healthy subjects performed 20 throws both in a virtual environment and in real one as they threw a ball with both dominant and nondominant arms. The electromyography (EMG) signals of 11 muscles of the upper limbs were recorded. Non-negative matrix factorization was used to extract muscle synergies. The cosine similarity was computed to assess the consistence of muscle synergy organization between virtual and real tasks. The same parameter was used to establish the inter-subject similarity. A three-synergy model was selected as the most likely. No effects of virtual reality and arm side on neuromuscular organization were found. Forearm muscles, not necessary for ball holding and release, were comprised in the activation synergies in the virtual reality environment. Finally, the synergies were consistent across subjects, especially during the deceleration phase. Results are encouraging for the application of virtual reality to complement conventional therapy, improve engagement, and facilitate objective measurements of pathology progression.

scholarly journals Human Muscle Synergy Analysis to Approach the Understanding of Brain Control Algorithm

2021 ◽  
Author(s):  
Fereidoun Nowshiravan Rahatabad ◽  
Parisa Rangraz
Keyword(s):  
Control Algorithm ◽  
Functional Unit ◽  
Recurrence Plot ◽  
Human Muscle ◽  
Muscle Synergy ◽  
Hand Movements ◽  
Muscle Synergies ◽  
Emg Signal ◽  
Random Motions ◽  
Non Negative Matrix Factorization

Purpose: Muscle synergy is a functional unit that coordinates the activity of a number of muscles. In this study, the extraction of muscle synergies in three types of hand movements in the horizontal plane is investigated. Materials and Methods: So, after constructing the tracking pattern of three signals, by LabVIEW, the Electromyography (EMG) signal from six muscles of hand was recorded. Then time-constant muscle synergies and their activity curves from the recorded EMG signals were extracted using Non-negative Matrix Factorization (NMF) method. Results: Comparison of these patterns showed that the non-random motions’ synergies were more similar than the random motions among different individuals. It was observed that in all movements, the similarity of the synergies in one cluster was greater than the similarity of their corresponding activation curves. Conclusion: The results showed that the complexity of the recurrence plot in random movement is greater than that of the other movements.

scholarly journals Muscle Synergy of Lower Limb Motion in Subjects with and without Knee Pathology

Diagnostics ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1318
Author(s):  
Jingcheng Chen ◽  
Yining Sun ◽  
Shaoming Sun
Keyword(s):  
Lower Limb ◽  
Neural Control ◽  
Feature Selection Method ◽  
Muscle Synergy ◽  
Complex Nature ◽  
Motion Recognition ◽  
Analysis System ◽  
Knee Pathology ◽  
Semg Signals ◽  
Non Negative Matrix Factorization

Surface electromyography (sEMG) has great potential in investigating the neuromuscular mechanism for knee pathology. However, due to the complex nature of neural control in lower limb motions and the divergences in subjects’ health and habits, it is difficult to directly use the raw sEMG signals to establish a robust sEMG analysis system. To solve this, muscle synergy analysis based on non-negative matrix factorization (NMF) of sEMG is carried out in this manuscript. The similarities of muscle synergy of subjects with and without knee pathology performing three different lower limb motions are calculated. Based on that, we have designed a classification method for motion recognition and knee pathology diagnosis. First, raw sEMG segments are preprocessed and then decomposed to muscle synergy matrices by NMF. Then, a two-stage feature selection method is executed to reduce the dimension of feature sets extracted from aforementioned matrices. Finally, the random forest classifier is adopted to identify motions or diagnose knee pathology. The study was conducted on an open dataset of 11 healthy subjects and 11 patients. Results show that the NMF-based sEMG classifier can achieve good performance in lower limb motion recognition, and is also an attractive solution for clinical application of knee pathology diagnosis.

scholarly journals Flexible Recruitments of Fundamental Muscle Synergies in the Trunk and Lower Limbs for Highly Variable Movements and Postures

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6186
Author(s):  
Hiroki Saito ◽  
Hikaru Yokoyama ◽  
Atsushi Sasaki ◽  
Tatsuya Kato ◽  
Kimitaka Nakazawa
Keyword(s):  
Neural Control ◽  
Static Stability ◽  
Neural Representation ◽  
Lower Limbs ◽  
Muscle Synergies ◽  
Functional Roles ◽  
Lower Limb Muscles ◽  
Low Dimensionality ◽  
The Central Nervous System ◽  
Almost All

The extent to which muscle synergies represent the neural control of human behavior remains unknown. Here, we tested whether certain sets of muscle synergies that are fundamentally necessary across behaviors exist. We measured the electromyographic activities of 26 muscles, including bilateral trunk and lower limb muscles, during 24 locomotion, dynamic and static stability tasks, and we extracted the muscle synergies using non-negative matrix factorization. Our results show that 13 muscle synergies that may have unique functional roles accounted for almost all 24 tasks by combinations of single and/or merging of synergies. Therefore, our results may support the notion of the low dimensionality in motor outputs, in which the central nervous system flexibly recruits fundamental muscle synergies to execute diverse human behaviors. Further studies are required to validate the neural representation of the fundamental components of muscle synergies.

scholarly journals Lower complexity of motor primitives ensures robust control of high-speed human locomotion

2020 ◽  
Author(s):  
Alessandro Santuz ◽  
Antonis Ekizos ◽  
Yoko Kunimasa ◽  
Kota Kijima ◽  
Masaki Ishikawa ◽  
...  
Keyword(s):  
High Speed ◽  
Muscle Activation ◽  
Human Locomotion ◽  
Muscle Synergies ◽  
Activation Patterns ◽  
Motor Primitives ◽  
Muscle Activation Patterns ◽  
Relative Contribution ◽  
Muscle Activations ◽  
Low Dimensional

AbstractWalking and running are mechanically and energetically different locomotion modes. For selecting one or another, speed is a parameter of paramount importance. Yet, both are likely controlled by similar low-dimensional neuronal networks that reflect in patterned muscle activations called muscle synergies. Here, we investigated how humans synergistically activate muscles during locomotion at different submaximal and maximal speeds. We analysed the duration and complexity (or irregularity) over time of motor primitives, the temporal components of muscle synergies. We found that the challenge imposed by controlling high-speed locomotion forces the central nervous system to produce muscle activation patterns that are wider and less complex relative to the duration of the gait cycle. The motor modules, or time-independent coefficients, were redistributed as locomotion speed changed. These outcomes show that robust locomotion control at challenging speeds is achieved by modulating the relative contribution of muscle activations and producing less complex and wider control signals, whereas slow speeds allow for more irregular control.

Strategies that simplify the control of quadrupedal stance. II. Electromyographic activity

1988 ◽  
Vol 60 (1) ◽  
pp. 218-231 ◽  
Author(s):  
J. M. Macpherson
Keyword(s):  
Muscle Synergy ◽  
Muscle Synergies ◽  
Electromyographic Activity ◽  
Supporting Surface ◽  
Force Vector ◽  
Tuning Curves ◽  
Hindlimb Muscles ◽  
Vector Generation ◽  
High Level ◽  
Selection Of

1. This study tested the hypothesis that muscle synergies underlie the invariance in the direction of corrective forces observed following stance perturbations in the horizontal plane. Electromyographic activity was recorded from selected forelimb and hindlimb muscles of cats subjected to horizontal translations of the supporting surface in 16 different directions. The responses of muscles were quantified for each perturbation, and tuning curves were constructed that related the amplitude of muscle response to the direction of platform movement. 2. Muscle tuning curves tended to group into one of two regions, corresponding to the two directions of force vectors. A few muscles showed clearly different recruitment patterns. The same direction of correction force vector was produced by different patterns of muscle activity, and the particular EMG pattern depended on the direction of platform movement. Therefore a simple muscle synergy organization could not account for the invariance in force vector generation. 3. It is concluded that there is a hierarchy of control in the maintenance of stance in which the vector of force exerted against the ground is a high level, task-dependent controlled variable and the selection of muscles to activate in order to produce the vector is controlled at a lower level. It is proposed that muscles are controlled using a modified synergy strategy. In this scheme, a synergy is not simply a fixed group of muscles, constrained to act as a unit. Rather, muscles are organized as a task-dependent synergy that is tuned or modified as needed by the addition or subtraction of other muscles.

scholarly journals Muscle Synergies Reliability in the Power Clean Exercise

2020 ◽  
Vol 5 (4) ◽  
pp. 75
Author(s):  
Paulo D. G. Santos ◽  
João R. Vaz ◽  
Paulo F. Correia ◽  
Maria J. Valamatos ◽  
António P. Veloso ◽  
...  
Keyword(s):  
Nonnegative Matrix Factorization ◽  
Nonnegative Matrix ◽  
Human Movement ◽  
Muscle Synergy ◽  
Muscle Synergies ◽  
Complex Task ◽  
Muscle Coordination ◽  
High Similarity ◽  
Strength Tests ◽  
Power Clean

Muscle synergy extraction has been utilized to investigate muscle coordination in human movement, namely in sports. The reliability of the method has been proposed, although it has not been assessed previously during a complex sportive task. Therefore, the aim of the study was to evaluate intra- and inter-day reliability of a strength training complex task, the power clean, assessing participants’ variability in the task across sets and days. Twelve unexperienced participants performed four sets of power cleans in two test days after strength tests, and muscle synergies were extracted from electromyography (EMG) data of 16 muscles. Three muscle synergies accounted for almost 90% of variance accounted for (VAF) across sets and days. Intra-day VAF, muscle synergy vectors, synergy activation coefficients and individual EMG profiles showed high similarity values. Inter-day muscle synergy vectors had moderate similarity, while the variables regarding temporal activation were still strongly related. The present findings revealed that the muscle synergies extracted during the power clean remained stable across sets and days in unexperienced participants. Thus, the mathematical procedure for the extraction of muscle synergies through nonnegative matrix factorization (NMF) may be considered a reliable method to study muscle coordination adaptations from muscle strength programs.

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