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Basketball victory relies on an athlete's skill to make precise shots at different distances. While extensive research has explored the kinematics and dynamics of different shooting distances, the specific neuromuscular control strategies involved remain elusive. This study aimed to compare the differences in muscle synergies during basketball shooting at different distances, offering insights into neuromuscular control strategies and guiding athletes' training. Ten skilled shooting right-handed male basketball players participated as subjects in this experiment. Electromyographic (EMG) data for full-phase shooting were acquired at short (3.2 m), middle (5.0 m), and long (6.8 m) distances. Non-negative matrix decomposition extracted muscle synergies (motor modules and motor primitives) during shooting. The results of this study show that all three distance shooting can be broken down into three synergies and that there were differences in the synergies between short and long distances, with differences in motor primitive 1 and motor primitive 2 at the phase of 45% - 59% ( p < 0.001, t* = 4.418), and 78% - 88% ( p < 0.01, t* = 4.579), respectively, and differences in the motor module 3 found in the differences in muscle weights for rectus femoris (RF) ( p = 0.001, d = -2.094), and gastrocnemius lateral (GL) ( p = 0.001, d = -2.083). Shooting distance doesn't affect the number of muscle synergies in basketball shooting but alters synergy patterns. During long distance shooting training, basketball players should place more emphasis on the timing and synergistic activation of upper and lower limbs, as well as core muscles., (© Journal of Sports Science and Medicine.)

Limbs execute diverse actions coordinated by the nervous system through multiple motor programs. The basic architecture of motor neurons that activate muscles that articulate joints for antagonistic flexion and extension movements is conserved from flies to vertebrates. While excitatory premotor circuits are expected to establish sets of leg motor neurons that work together, our study uncovered a new instructive role for inhibitory circuits: their ability to generate rhythmic leg movements. Using electron microscopy data for the Drosophila nerve cord, we categorized ~120 GABAergic inhibitory neurons from the 13A and 13B hemi-lineages into classes based on similarities in morphology and connectivity. By mapping their synaptic partners, we uncovered pathways for inhibiting specific groups of motor neurons, disinhibiting antagonistic counterparts, and inducing alternation between flexion and extension. We tested the function of specific inhibitory neurons through optogenetic activation and silencing, using an in-depth ethological analysis of leg movements during grooming. We combined anatomy and behavior analysis findings to construct a computational model that can reproduce major aspects of the observed behavior, confirming the sufficiency of these premotor inhibitory circuits to generate rhythms.

Objective . This research aims to reveal how the synergistic control of upper limb muscles adapts to varying requirements in complex motor tasks and how expertise shapes the motor modules. Approach . We study the muscle synergies of a complex, highly skilled and flexible task-piano playing-and characterize expertise-related muscle-synergy control that permits the experts to effortlessly execute the same task at different tempo and force levels. Surface EMGs (28 muscles) were recorded from adult novice ( N = 10) and expert ( N = 10) pianists as they played scales and arpeggios at different tempo-force combinations. Muscle synergies were factorized from EMGs. Main results . We found that experts were able to cover both tempo and dynamic ranges using similar synergy selections and achieved better performance, while novices altered synergy selections more to adapt to the changing tempi and keystroke intensities compared with experts. Both groups relied on fine-tuning the muscle weights within specific synergies to accomplish the different task styles, while the experts could tune the muscles in a greater number of synergies, especially when changing the tempo, and switch tempo over a wider range. Significance . Our study sheds light on the control mechanism underpinning expertise-related motor flexibility in highly skilled motor tasks that require decade-long training. Our results have implications on musical and sports training, as well as motor prosthetic design., (© 2024 IOP Publishing Ltd.)

Background: The Lokomat is a robotic device that has been suggested to make gait therapy easier, more comfortable, and more efficient. In this study, we asked whether the Lokomat promotes physiological muscle activation patterns, a fundamental question when considering motor learning and adaptation. Methods: We investigated lower limb muscles coordination in terms of muscle activity level, muscle activity pattern similarity, and muscle synergy in 15 healthy participants walking at 3 km/h on either a treadmill or in a Lokomat at various guidance forces (GF: 30, 50 or 70%) and body weight supports (BWS: 30, 50 or 70% of participant's body weight). Results: Walking in the Lokomat was associated with a greater activation level of the rectus femoris and vastus medialis (×2–3) compared to treadmill walking. The level of activity tended to be diminished in gastrocnemius and semi-tendinosus, which particularly affected the similarity with treadmill walking (normalized scalar product NSP = 0.7–0.8). GF and BWS independently altered the muscle activation pattern in terms of amplitude and shape. Increasing BWS decreased the level of activity in all but one muscle (the soleus). Increasing GF slightly improved the similarity with treadmill walking for the tibialis anterior and vastus medialis muscles. The muscle synergies (N = 4) were similar (NSP = 0.93–0.97), but a cross-validation procedure revealed an alteration by the Lokomat. The activation of these synergies differed (NSP = 0.74–0.82). Conclusion: The effects of GF and BWS are modest compared to the effect of the Lokomat itself, suggesting that Lokomat design should be improved to promote more typical muscle activity patterns. [ABSTRACT FROM AUTHOR]

Objective: While neuroplasticity and functional reorganization during motor recovery can be indirectly reflected and evaluated by functional corticomuscular coupling (fCMC), little work has been published regarding the cortical origin of abnormal muscle synergy and compensatory mechanism in the separation movement of stroke patients. Methods: In this study, we proposed to use extended partial directed coherence (ePDC) combined with an optimal spatial filtering approach to estimate fCMC in stroke patients and healthy controls, and further established muscle synergy model (MSM) to jointly explore the modulation mechanism between cortex and muscles. Results: Compared to healthy controls, stroke patients had significantly reduced coupling strength in both descending and ascending pathway. Moreover, the MSM were abnormal with high variability and low similarity in the separation stage of stroke patients. Further exploration of the positive relationship between fCMC characteristics and MSM parameters proved the possibility of using fCMC-MSM-based correlation indicator to evaluate abnormality of the cortical related synergy movement as well as the rehabilitation level of stroke patients. Conclusion: We developed a computational procedure to evaluate the correlation between fCMC and MSM in stroke patients. Significance: This article provides a quantitative evaluation metrics based on fCMC to reveal the deficits during poststroke motor restoration and a promising approach to help patients correct abnormal movement habits, paving the way for neurophysiological assessment of neuromuscular control in conjunction with clinical scores. [ABSTRACT FROM AUTHOR]

Handedness has been associated with behavioral asymmetries between limbs that suggest specialized function of dominant and non-dominant hand. Whether patterns of muscle co-activation, representing muscle synergies, also differ between the limbs remains an open question. Previous investigations of proximal upper limb muscle synergies have reported little evidence of limb asymmetry; however, whether the same is true of the distal upper limb and hand remains unknown. This study compared forearm and hand muscle synergies between the dominant and non-dominant limb of left-handed and right-handed participants. Participants formed their hands into the postures of the American Sign Language (ASL) alphabet, while EMG was recorded from hand and forearm muscles. Muscle synergies were extracted for each limb individually by applying non-negative-matrix-factorization (NMF). Extracted synergies were compared between limbs for each individual, and between individuals to assess within and across participant differences. Results indicate no difference between the limbs for individuals, but differences in limb synergies at the population level. Left limb synergies were found to be more similar than right limb synergies across left- and right-handed individuals. Synergies of the left hand of left dominant individuals were found to have greater population level similarity than the other limbs tested. Results are interpreted with respect to known differences in the neuroanatomy and neurophysiology of proximal and distal upper limb motor control. Implications for skill training in sports requiring dexterous control of the hand are discussed. [ABSTRACT FROM AUTHOR]

The motor system relies on the recruitment of motor modules to perform various movements. Muscle synergies are the modules used by the central nervous system to simplify the control of complex motor tasks. In this paper, we aim to explore the primitive synergies to reflect different modes of coordination in upper limb motions. Muscle synergies and corresponding activation coefficients were extracted via non-negative matrix factorization from the electromyography signals of three basic and four complex upper limb motions in sagittal plane and coronal plane. Similarities of muscle synergies and activation coefficients between different tasks and different subjects were compared. Moreover, we used network theory to assess the coordination between multiple muscles and to elucidate the neural implementation of muscle synergies. The results showed that the combination of different sets of primitive muscle synergies can achieve complex motions in different planes. The muscle synergy network topology differed significantly between different tasks. We also demonstrated the potential of this study for the understanding of human motor control mechanism and implications for neurorehabilitation. [ABSTRACT FROM AUTHOR]

This article analyzes the current state of studies of aspects of the neurophysiological control of parameters of atypical postures in humans associated with the use of external exoskeleton-type devices. The main results of studies in the last five years relate to the formation of scientific concepts of neurophysiological rearrangements of the motor control system on use of robotic devices. The resulting information can be used in sports physiology, motor rehabilitation, development of upper and lower limb exoskeletons, organizing the work of operators, and training to specific movements. [ABSTRACT FROM AUTHOR]

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.

Abstract Moving about in the world during daily life requires executing and successfully shifting between a variety of functional tasks, such as rising from a chair or bed, walking, turning, and navigating stairs. Moreover, moving about during daily life requires not only navigating between different functional tasks, but also performing these tasks in the presence of mental distractions. However, little is known about underlying neuromuscular control for executing and shifting between these different tasks. In this study, we investigated muscle coordination across walking, turning, and chair transfers by applying motor module (a.k.a. muscle synergy) analysis to the Timed‐Up‐and‐Go (TUG) test with and without a secondary cognitive dual task. We found that healthy young adults recruit a small set of common motor modules across the subtasks of the TUG test and that their composition is robust to cognitive distraction. Instead, cognitive distraction impacted motor module activation timings such that they became more consistent. This work is the first to demonstrate motor module generalization across multiple tasks that are both functionally different and crucial for healthy mobility. Overall, our results suggest that the central nervous system may draw from a “library” of modular control strategies to navigate the variety of movements and cognitive demands required of daily life.

For clinicians to provide more efficient early mobilization in patients with acute stroke, they must quantitatively evaluate the motion characteristics of the patients. To measure the motion in the acute phase, it is necessary to prevent physical interference between the measurement and medical equipment. This study classified abnormal muscle synergies during sit-to-stand motion in patients with acute stroke by using small, wirelessly operable, noninvasive surface electromyography devices. Four patients with acute stroke and four healthy adults performed a six-directional isometric contraction task and a sit-to-stand motion task. A nonnegative matrix factorization algorithm was applied to the muscle activity data to extract the muscle synergies. Hierarchical cluster analysis was used to classify these synergies. The results suggest that sit-to-stand motion characteristics according to the severity of effects in patients with acute stroke can be quantitatively classified by muscle synergy analysis. The spatial structure of muscle synergies of patients was classified into different clusters from that of the healthy adults. The abnormal muscle synergy in patients with severe paresis is considered severe in that it cannot be modulated according to the task. The muscle synergies in patients with moderate paresis were modulated in the sit-to-stand motion to compensate for extensor muscle weakness. Such abnormal muscle synergy in the sit-to-stand motion is useful as a reference for motion practice, especially for early mobilization after the onset of a stroke. In addition, the results verify that the early to late stages of recovery can be consistently evaluated with this small, wireless noninvasive electromyography device.

Moving about in the world during daily life requires executing and successfully shifting between a variety of functional tasks, such as rising from a chair or bed, walking, turning, and navigating stairs. Moreover, moving about during daily life requires not only navigating between different functional tasks, but also performing these tasks in the presence of mental distractions. However, little is known about underlying neuromuscular control for executing and shifting between these different tasks. In this study, we investigated muscle coordination across walking, turning, and chair transfers by applying motor module (a.k.a. muscle synergy) analysis to the Timed‐Up‐and‐Go (TUG) test with and without a secondary cognitive dual task. We found that healthy young adults recruit a small set of common motor modules across the subtasks of the TUG test and that their composition is robust to cognitive distraction. Instead, cognitive distraction impacted motor module activation timings such that they became more consistent. This work is the first to demonstrate motor module generalization across multiple tasks that are both functionally different and crucial for healthy mobility. Overall, our results suggest that the central nervous system may draw from a "library" of modular control strategies to navigate the variety of movements and cognitive demands required of daily life. [ABSTRACT FROM AUTHOR]

It is currently unknown if modular reorganization does occur if not the central nervous system, but the musculoskeletal system is affected. The aims of this study were to investigate 1) the effects of an artificial knee joint constraint on the modular organization of gait in healthy subjects; and 2) the differences in modular organization between healthy subjects with an artificial knee joint constraint and people with a similar but chronic knee joint constraint. Eleven healthy subjects and eight people with a chronic knee joint constraint walked overground at 1 m/s. The healthy subjects also walked with a constraint limiting knee joint movement to 20°. The total variance accounted (tVAF) for one to four synergies and modular organization were assessed using surface electromyography from 11 leg muscles. The distribution of number of synergies were not significantly different between groups. The tVAF and the motor modules were not significantly affected by the artificial knee constraint. A higher tVAF for one and two synergies, as well as merging of motor modules were observed in the chronic knee constraint group. We conclude that in the short-term a knee constraint does not affect the modular organization of gait, but in the long-term a knee constraint results in modular reorganization. These results indicate that merging of motor modules may also occur when changes in the mechanics of the musculoskeletal system is the primary cause of the motor impairment. NEW & NOTEWORTHY It is currently unknown if modular reorganization does occur if not the central nervous system, but the musculoskeletal system is affected. This study showed that in the short-term a knee constraint does not affect the modular organization of gait, but in the long-term a knee constraint results in modular reorganization. These results indicate that modular reorganization may also occur when changes in the mechanics of the musculoskeletal system is the primary cause of the motor impairment. [ABSTRACT FROM AUTHOR]

Sit-to-stand motion is an important daily activity, and it is important to study the mechanism of the motion to improve the ability when it becomes weak. To study the mechanism, we hypothesized that muscle synergy generates muscle activity as a feedforward signal, which is modified by sensory input. This study focuses on determining the sensory input primarily used for modifying sit-to-stand motion. To obtain this, we built artificial neural network models that generate muscle activities based on sensory input and feedforward signals and analyzed the effect of each input on the output. The models were built for each motion phase. The input was information from vestibular and somatosensory input and averaged muscle synergy as feedforward signals, and the output was muscle synergy. As a result, it was revealed that humans may primarily use hip angle to bend forward, ankle and vertical foot reaction force to hip rise, ankle, knee, and lumber angles and vertical foot reaction force to extend body, and lumber angle to stabilize. This indicates the type of sensory input used to control each muscle synergy in each motion phase. The information should be used to modify the sit-to-stand motion in environmental conditions where the motion is performed. [ABSTRACT FROM AUTHOR]

Patients with stroke experience declined physical functions and aim to recover by rehabilitation. It is important to improve their functions in the subacute period. Hemiplegic patients who can stand exhibit differing characteristics such as the center of mass and muscle synergy compared to healthy subjects. However, the characteristics to be achieved by the sit-to-stand motion in the subacute period is unknown. This study investigated the sit-to-stand motions of hemiplegic patients (n = 21) in three months of stroke onset. The patients were partitioned into two groups ('mild' and 'severe'), based on the functional independence score at the time of discharge, and the patient's sit-to-stand motion in the subacute period was analyzed by muscle synergy and kinematics. The severe patients performed a biased standing on the non-paralyzed side, and the activation timing of muscle synergy that contributes to whole-body extension was earlier than that of the mild patients. This study contributes to the development of guidelines for optimal intervention for each patient. [ABSTRACT FROM AUTHOR]

The non-stationary characteristics of surface electromyography (sEMG) and possible adverse variations in real-world conditions make it still an open challenge to realize robust myoelectric control (MEC) for multifunctional prostheses. Variable muscle contraction level is one of the handicaps that may degrade the performance of MEC. In this study, we proposed a force-invariant intent recognition method based on muscle synergy analysis (MSA) in the setting of three self-defined force levels (low, medium, and high). Specifically, a fast matrix factorization algorithm based on alternating non-negativity constrained least squares (NMF/ANLS) was chosen to extract task-specific synergies associated with each of six hand gestures in the training stage; while for the testing samples, we used the non-negative least square (NNLS) method to estimate neural commands for movement classification. The performance of proposed method was compared with conventional pattern recognition (PR) method consisting of LDA (linear discrimination analysis) classifier and representative features in three offline evaluation scenarios. Statistical tests on ten able-bodied subjects revealed no significant difference in intra-force-level (p = 0.353) and multi-force-level (p = 0.695) accuracy; But the synergy-based method performed significantly better than conventional PR-based method under inter-force-level conditions (p < 0.05). Similar results were observed for nine amputee subjects though there was a drop in the classification accuracy. This study was the first to concurrently demonstrate the robustness and predictive power of task-specific synergies under variant force levels and explore their potential for reliable intent recognition against force variation. Although the online performance is yet to be demonstrated, the proposed method is characterized by simple training procedure and acceptable computational efficiency, which would potentially provide an alternative approach for the development of clinically viable prostheses and rehabilitation robots driven by sEMG. [ABSTRACT FROM AUTHOR]

Neural information decomposed from electromyography (EMG) signals provides a new path of EMG-based human-machine interface. Instead of the motor unit decomposition-based method, this work presents a novel neural interface for human gait tracking based on muscle synergy, the high-level neural control information to collaborate muscle groups for performing movements. Three classical synergy extraction approaches include Principle Component Analysis (PCA), Factor Analysis (FA), and Nonnegative Matrix Factorization (NMF), are employed for muscle synergy extraction. A deep regression neural network based on the bidirectional gated recurrent unit (BGRU) is used to extract temporal information from the synergy matrix to estimate joint angles of the lower limb. Eight subjects participated in the experiment while walking at four types of speed: 0.5km/h, 1.0km/h, 2.0km/h, and 3.0km/h. Two machine learning methods based on linear regression (LR) and multilayer perceptron (MLP) are set as the contrast group. The result shows that the synergy-based approach’s performance outperforms two contrast methods with ${R}_{\textit {var}}^{2}$ scores of 0.83~0.88. PCA reaches the highest performance of 0.871±0.029, corresponding to RMSE of 3.836°, 6.278°, 2.197° for hip, knee, and ankle, respectively. The effect of walking speed, synergy number, and joint location will be analyzed. The performance shows that muscle synergy has a good correlation will joint angles which can be unearthed by deep learning. The proposed method explores a new way for gait analysis and contributes to building a novel neural interface with muscle synergy and deep learning. [ABSTRACT FROM AUTHOR]

• Constructed two new cost functions involving muscle synergies. • Used muscle activations predicted by musculoskeletal modelling instead of electromyography to extract muscle synergies. • Verified and validated the ability of the novel cost functions to predict muscle forces. • Explored the potential of muscle synergy hypothesis. Solving the redundant optimization problem for human muscles depends on the cost function. Choosing the appropriate cost function helps to address a specific problem. Muscle synergies are currently limited to those obtained by electromyography. Furthermore, debate continues regarding whether muscle synergy is derived or real. This study proposes new cost functions based on the muscle synergy hypothesis for solving the optimal muscle force output problem through musculoskeletal modeling. We propose two new computational cost functions involving muscle synergies, which are extracted from muscle activations predicted by musculoskeletal modelling rather than electromyography. In this study, we constructed a musculoskeletal model for simulation using the "Grand Challenge Competition to Predict In Vivo Knee Loads" dataset. Muscle synergies were obtained using non-negative matrix factorization. Two cost functions with muscle synergies were constructed by integrating the polynomial and min/max criterion. Two new functions were verified and validated in normal, smooth, and bouncy gaits. The muscle synergies based on normal gaits were classified into four modules. The cosine similarities of the first three modules were all >0.9. In the normal and smooth gaits, the forces in most muscles predicted using the two new functions were within three standard deviations of the root mean square error for electromyographic comparisons. Predicted muscle force curves using the four methods as well as characteristic points (i.e., time points in the gait cycle when the significant difference was observed between normal and bouncy gaits) were obtained to validate their predictive capabilities. This study constructed two new cost functions involving muscle synergies, verified and validated the ability, and explored the potential of muscle synergy hypothesis. [ABSTRACT FROM AUTHOR]

The jump smash is badminton's most aggressive technical manoeuvre, which is often the key to winning a match. This paper aims to explore the neuromuscular control strategies of advanced and beginner players when jumping smash in different ways. Collecting sEMG and kinematic data from 18 subjects with different motor experiences when jumping smash. Nonnegative Matrix Factorization and K-Means clustering were used to extract muscle synergies and exclude irrelevant combined synergies. Uncontrolled manifold analysis was then used to explore the association between synergies and shoulder stability. In addition, motor output at the spinal cord level was assessed by mapping sEMG to each spinal cord segment. The study found that advanced subjects could respond to different jump smash styles by adjusting the coordinated activation strategies of the upper-limb and postural muscles. Long-term training can induce a rapid decrease in the degree of co-variation of the synergies before contact with a shuttlecock to better cope with an upcoming collision. It is recommended that beginners should focus more on training the coordination of upper-limb muscles and postural muscles. [ABSTRACT FROM AUTHOR]

Bipedal locomotion was a major functional change during hominin evolution, yet, our understanding of this gradual and complex process remains strongly debated. Based on fossil discoveries, it is possible to address functional hypotheses related to bipedal anatomy, however, motor control remains intangible with this approach. Using comparative models which occasionally walk bipedally has proved to be relevant to shed light on the evolutionary transition toward habitual bipedalism. Here, we explored the organization of the neuromuscular control using surface electromyography (sEMG) for six extrinsic muscles in two baboon individuals when they walk quadrupedally and bipedally on the ground. We compared their muscular coordination to five human subjects walking bipedally. We extracted muscle synergies from the sEMG envelopes using the non-negative matrix factorization algorithm which allows decomposing the sEMG data in the linear combination of two non-negative matrixes (muscle weight vectors and activation coefficients). We calculated different parameters to estimate the complexity of the sEMG signals, the duration of the activation of the synergies, and the generalizability of the muscle synergy model across species and walking conditions. We found that the motor control strategy is less complex in baboons when they walk bipedally, with an increased muscular activity and muscle coactivation. When comparing the baboon bipedal and quadrupedal pattern of walking to human bipedalism, we observed that the baboon bipedal pattern of walking is closer to human bipedalism for both baboons, although substantial differences remain. Overall, our findings show that the muscle activity of a non-adapted biped effectively fulfills the basic mechanical requirements (propulsion and balance) for walking bipedally, but substantial refinements are possible to optimize the efficiency of bipedal locomotion. In the evolutionary context of an expanding reliance on bipedal behaviors, even minor morphological alterations, reducing muscle coactivation, could have faced strong selection pressure, ultimately driving bipedal evolution in hominins. [ABSTRACT FROM AUTHOR]

Abstract Background Children with cerebral palsy (CP) have altered synergies compared to typically-developing peers, reflecting different neuromuscular control strategies used to move. While these children receive a variety of treatments to improve gait, whether synergies change after treatment, or are associated with treatment outcomes, remains unknown. Methods We evaluated synergies for 147 children with CP before and after three common treatments: botulinum toxin type-A injection (n = 52), selective dorsal rhizotomy (n = 38), and multi-level orthopaedic surgery (n = 57). Changes in synergy complexity were measured by the number of synergies required to explain > 90% of the total variance in electromyography data and total variance accounted for by one synergy. Synergy weights and activations before and after treatment were compared using the cosine similarity relative to average synergies of 31 typically-developing (TD) peers. Results There were minimal changes in synergies after treatment despite changes in walking patterns. Number of synergies did not change significantly for any treatment group. Total variance accounted for by one synergy increased (i.e., moved further from TD peers) after botulinum toxin type-A injection (1.3%) and selective dorsal rhizotomy (1.9%), but the change was small. Synergy weights did not change for any treatment group (average 0.001 ± 0.10), but synergy activations after selective dorsal rhizotomy did change and were less similar to TD peers (− 0.03 ± 0.07). Only changes in synergy activations were associated with changes in gait kinematics or walking speed after treatment. Children with synergy activations more similar to TD peers after treatment had greater improvements in gait. Conclusions While many of these children received significant surgical procedures and prolonged rehabilitation, the minimal changes in synergies after treatment highlight the challenges in altering neuromuscular control in CP. Development of treatment strategies that directly target impaired control or are optimized to an individual’s unique control may be required to improve walking function.

Higher order tensor decompositions have hardly been used in muscle activity analysis despite multichannel electromyography (EMG) datasets naturally occurring as multi-way structures. Here, we seek to demonstrate and discuss the potential of tensor decompositions as a framework to estimate muscle synergies from the third-order EMG tensors built by stacking repetitions of multi-channel EMG for several tasks. We compare the two most widespread tensor decomposition models-parallel factor analysis (PARAFAC) and Tucker-in muscle synergy analysis of the wrist's three main degrees of freedom (DoF) using the public first Ninapro database. Furthermore, we proposed a constrained Tucker decomposition (consTD) method for efficient synergy extraction building on the power of tensor decompositions. This method is proposed as a direct novel approach for shared and task-specific synergy estimation from two biomechanically related tasks. Our approach is compared with the current standard approach of repetitively applying non-negative matrix factorization (NMF) to a series of movements. The results show that the consTD method is suitable for synergy extraction compared with PARAFAC and Tucker. Moreover, exploiting the multi-way structure of muscle activity, the proposed methods successfully identified shared and task-specific synergies for all three DoFs tensors. These were found to be robust to disarrangement with regard to task-repetition information, unlike the commonly used NMF. In summary, we demonstrate how to use tensors to characterize muscle activity and develop a new consTD method for muscle synergy extraction that could be used for shared and task-specific synergies identification. We expect that this paper will pave the way for the development of novel muscle activity analysis methods based on higher order techniques.

• Muscle synergy stability was greater in dual task conditions than single task. • Increasing locomotion speed decreased muscle synergy stability and complexity. • Centre of mass motion became less stable and more complex with increasing speed. • Vertical centre of mass motion was more complex and less stable in dual tasking. • Neuromotor (synergy) stability likely moderates changes in gait local stability. The aim of the study was to determine the stability and complexity of muscle synergies to provide insight to the neural control of gait stability in walking and running and when performing a concurrent cognitive dual task. Eighteen healthy young adults performed walking and running at preferred speeds and 120% of preferred speeds in single and dual task conditions. Muscle synergies were determined from the activity of 9 trunk and leg muscles and centre of mass (COM) motion was recorded with an inertial measurement unit. Local dynamic stability, complexity and width of synergies, and stability and complexity of COM motion were determined, in addition to the cross sample entropy to determine the coupling between COM motion and muscle synergies. Increasing locomotion speed increased complexity and decreased stability of COM motion with a concurrent decrease in synergy complexity and stability but with no change in synergy width. The coupling of COM motion and muscle synergies also increased with increasing speed. Vertical COM motion was more complex and less stable but with no change in anterior-posterior or medio-lateral directions in dual task locomotion. Muscle synergies were also more stable in dual task conditions. These findings indicate that changes in neuromotor dynamics may underpin reported changes in COM local stability during gait as the neural commands responsible for generating the movement are altered in response to increasing task demands. Increased cognitive demands lead to more stable neuromotor commands possibly to maintain local stability of COM motion in the anterior-posterior and medio-lateral directions. [ABSTRACT FROM AUTHOR]

Owing to its potential superiorities in terms of flexibility, compliance, and robustness, the musculoskeletal robotic system has become a promising direction for next-generation robots. However, motion learning and generalization of musculoskeletal systems are still challenging problems. In this article, a muscle-synergies-based neuromuscular control is proposed. First, a new computational model of time-varying muscle synergies is constructed, which utilizes both phasic and tonic muscle synergies to characterize the basic features of muscle excitations more sufficiently. Second, a novel neuromuscular control method is proposed for realizing the motion learning and generalization of musculoskeletal systems. Therein, a radial basis function (RBF) neural network is designed to modulate muscle synergies according to different movement targets. Muscle excitations are computed with the combination of modulated muscle synergies. Covariance matrix adaptation evolutionary strategy is applied to realize the synchronous optimization of muscle synergies and the RBF neural network. In the experiment, a sophisticated musculoskeletal system learns to perform center-out reaching tasks through trial-and-error learning on a few targets. With the muscle synergies and neural modulation learned from a few targets, the musculoskeletal system can also reach many unexperienced targets. The proposed method not only improves the speed and accuracy of motion learning but also enhances motion generalization. This article also promotes the development of the musculoskeletal robotic system and the fusion of neuroscience and robotics. [ABSTRACT FROM AUTHOR]

The central nervous system (CNS) may produce coordinated motor outputs via the combination of motor modules representable as muscle synergies. Identification of muscle synergies has hitherto relied on applying factorization algorithms to multimuscle electromyographic data (EMGs) recorded during motor behaviors. Recent studies have attempted to validate the neural basis of the muscle synergies identified by independently retrieving the muscle synergies through CNS manipulations and analytic techniques such as spike-triggered averaging of EMGs. Experimental data have demonstrated the pivotal role of the spinal premotor interneurons in the synergies' organization and the presence of motor cortical loci whose stimulations offer access to the synergies, but whether the motor cortex is also involved in organizing the synergies has remained unsettled. We argue that one difficulty inherent in current approaches to probing the synergies' neural basis is that the EMG generative model based on linear combination of synergies and the decomposition algorithms used for synergy identification are not grounded on enough prior knowledge from neurophysiology. Progress may be facilitated by constraining or updating the model and algorithms with knowledge derived directly from CNS manipulations or recordings. An investigative framework based on evaluating the relevance of neurophysiologically constrained models of muscle synergies to natural motor behaviors will allow a more sophisticated understanding of motor modularity, which will help the community move forward from the current debate on the neural versus nonneural origin of muscle synergies. [ABSTRACT FROM AUTHOR]

Background: Recent evidence suggests that disinhibition and/or hyperexcitation of the brainstem descending pathways and intraspinal motor network diffuse spastic synergistic activation patterns after stroke. This results in simplified or merged muscle sets (i.e., muscle modules or synergies) compared to non-impaired individuals and this leads to poor walking performance. However, the relations of how these neuromuscular deficits influence gait quality (e.g., symmetry or natural walking patterns) are still unclear. The objective of this exploratory study was to investigate the relations of modular neuromuscular framework and gait quality measures in chronic stroke individuals.Methods: Sixteen chronic post-stroke individuals participated in this study. Full lower body three-dimensional kinematics and electromyography (EMG) were concurrently measured during overground walking at a comfortable speed. We first examined changes in gait quality measures across the number of muscle modules using linear regression model. Then, a stepwise multiple regression was used to investigate the optimal combination of the neuromuscular parameters that associates with gait quality measures.Results: We observed that subjects who had a lower number of muscle modules revealed reduced function (i.e., speed) and greater asymmetry in the kinematic parameters including limb length, footpath area, knee flexion/extension, and hip abduction/adduction (all p < 0.05). We also found that the combination of input variables from the modular neuromuscular control framework significantly associated with gait quality measures (average [Formula: see text]). Those variables included variability accounted for ([Formula: see text]) information from the muscle modules and area under the EMG envelope curves of the quadriceps (i.e., rectus femoris and vastus lateralis) and tibialis anterior muscles.Conclusions: The results suggest that there exists a significant correlation between the neuromuscular control framework and the gait quality measures. This study helps to understand the underlying mechanism of disturbances in gait quality and provides insight for a more comprehensive outcome measure to assess gait impairment after stroke. [ABSTRACT FROM AUTHOR]

Smartphones are currently among the most common handheld devices. Previous studies on such handheld touchscreen devices focused on thumb operations or reach zones by measuring individual muscle or joint angles. However, they were limited to thumb operations and did not consider grasping. In this study, we investigated the grasp types of touchscreen devices and other objects included in an existing grasp taxonomy. To this end, principal component analysis and latent profile analysis clustering were used for extracting and grouping muscle and postural synergies. Fourteen healthy subjects performed up to 15 hand grasps, including that with a smartphone. Electromyography (EMG) data were measured on six muscles in the forearm and the hand, and joint angles were measured for 22 joints in the hand. The first two muscle synergies from the EMG data and the first three postural synergies from the kinematic data were found to account for over 60% of the overall grasping. In terms of the synergies, the grasp for handheld touchscreen devices showed unique characteristics in terms of muscle and postural synergies compared to other objects. The obtained results may aid in understanding of grasping behaviors for handheld touchscreen devices in various applications. [ABSTRACT FROM AUTHOR]

Children with cerebral palsy typically exhibit reduced complexity of muscle coordination patterns during walking; however, the specific patterns that characterize their gait abnormalities are still not well documented. This study aimed to identify the specific repertoire of muscle coordination patterns in children with CP during walking compared to same-aged peers without CP and their relationships to gait performance. To identify muscle coordination patterns, we extracted muscle synergies from 10 children with CP and 10 age-matched typically developing children (TD). K-mean clustering and discriminant analyses of all extracted synergies were used to group similar synergies. Then, weight-averaged z-scores were quantified for each cluster to determine their group-specific level. In this cohort, 10 of the 17 distinct clusters were largely CP-specific while six clusters were seen mainly in TD, and one was non-specific. CP-specific clusters generally showed merging of two TD synergies, excessive antagonist co-activation, decreased muscle activation compared to TD, and complex or atypical pattern. Significant correlations were found between weight-averaged z-scores and step length asymmetry, cadence asymmetry, self-selected treadmill speed and AP-COM displacement of the pelvis such that greater CP-specificity of muscle synergies was related to poorer performance, thus indicating that CP-specific synergies can influence motor dysfunction.

Muscle synergy analysis is a kind of modularized decomposition of muscles during exercise controlled by the central nervous system (CNS). It can not only extract the synergistic muscles in exercise, but also obtain the activation states of muscles to reflect the coordination and control relationship between muscles. However, previous studies have mainly focused on the time-domain synergy without considering the frequency-specific characteristics within synergy structures. Therefore, this study proposes a novel method, named time-frequency non-negative matrix factorization (TF-NMF), to explore the time-varying regularity of muscle synergy characteristics of multi-channel surface electromyogram (sEMG) signals at different frequency bands. In this method, the wavelet packet transform (WPT) is used to transform the time-scale signals into time-frequency dimension. Then, the NMF method is calculated in each time-frequency window to extract the synergy modules. Finally, this method is used to analyze the sEMG signals recorded from 8 muscles during the conversion between wrist flexion (WF stage) and wrist extension (WE stage) movements in 12 healthy people. The experimental results show that the number of synergy modules in wrist flexion transmission to wrist extension (Motion Conversion, MC stage) is more than that in the WF stage and WE stage. Furthermore, the number of flexor and extensor muscle synergies in the frequency band of 0–125 Hz during the MC stage is more than that in the frequency band of 125–250 Hz. Further analysis shows that the flexion muscle synergies mostly exist in the frequency band of 140.625–156.25 Hz during the WF stage, and the extension muscle synergies appear in the frequency band of 125–156.25 Hz during the WE stage. These results can help to better understand the time-frequency features of muscle synergy, and expand study perspective related to motor control in nervous system.

Recently, many muscle synergy-based human motion prediction models and algorithms have been proposed. In this study, the muscle synergies extracted from electromyography (EMG) data were used to construct a musculoskeletal model (MSM) to predict the joint angles of the wrist, thumb, index finger, and middle finger. EMG signals were analyzed using independent component analysis to reduce signal noise and task-irrelevant artifacts. The weights of each independent component (IC) were converted into a heat map related to the motion pattern and compared with human anatomy to find a different number of ICs matching the motion pattern. Based on the properties of the MSM, non-negative matrix factorization was used to extract muscle synergies from selected ICs that represent the extensor and flexor muscle groups. The effects of these choices on the prediction accuracy was also evaluated. The performance of the model was evaluated using the correlation coefficient (CC) and normalized root-mean-square error (NRMSE). The proposed method has a higher prediction accuracy than those of traditional methods, with an average CC of 92.0% and an average NRMSE of 10.7%.

Children with cerebral palsy typically exhibit reduced complexity of muscle coordination patterns during walking; however, the specific patterns that characterize their gait abnormalities are still not well documented. This study aimed to identify the specific repertoire of muscle coordination patterns in children with CP during walking compared to same-aged peers without CP and their relationships to gait performance. To identify muscle coordination patterns, we extracted muscle synergies from 10 children with CP and 10 age-matched typically developing children (TD). K-mean clustering and discriminant analyses of all extracted synergies were used to group similar synergies. Then, weight-averaged z-scores were quantified for each cluster to determine their group-specific level. In this cohort, 10 of the 17 distinct clusters were largely CP-specific while six clusters were seen mainly in TD, and one was non-specific. CP-specific clusters generally showed merging of two TD synergies, excessive antagonist co-activation, decreased muscle activation compared to TD, and complex or atypical pattern. Significant correlations were found between weight-averaged z-scores and step length asymmetry, cadence asymmetry, self-selected treadmill speed and AP-COM displacement of the pelvis such that greater CP-specificity of muscle synergies was related to poorer performance, thus indicating that CP-specific synergies can influence motor dysfunction. [ABSTRACT FROM AUTHOR]

• Jaw antagonist synergy during speech is significantly disrupted by bulbar motor involvement in ALS across the prodromal and symptomatic stages. • Jaw antagonist synergy shows relatively high sensitivity and specificity in detecting bulbar motor involvement in ALS. • Disease-related changes in jaw antagonist synergy are associated with the kinematic and functional speech deficits related to the progression of bulbar ALS. To identify a novel physiologic marker of bulbar motor involvement in amyotrophic lateral sclerosis (ALS) based on jaw muscle synergies. Muscle synergies were extracted from the surface electromyographic recordings of five jaw muscles during speech in 11 individuals at the prodromal or symptomatic stages of bulbar ALS and 10 neurologically-healthy controls, using non-negative matrix factorization. The disrupted muscle synergies in ALS were identified; their efficacy in differentiating individuals with ALS from healthy controls and relation to the previously-reported kinematic and functional speech deficits were determined. An antagonist synergy (i.e., masseter × digastric) was significantly disrupted in ALS, which differentiated individuals with ALS from healthy controls with 82% sensitivity and 90% specificity. Such a disruption occurred prodromally and was associated with slowed jaw movement and reduced speaking rate across the range of severity. The disruption of jaw antagonist synergy in ALS likely reflects the impact of impaired neural drive on the coordinative functioning of bulbar muscles, which may be used to assess bulbar motor involvement. Jaw antagonist synergy shows promise as a novel physiologic marker of bulbar motor involvement in ALS, which has the potential to serve as a quantitative measurement tool for bulbar assessment. [ABSTRACT FROM AUTHOR]

Twelve sambo wrestlers took part in the study. The spatio-temporal organization features of muscle synergies using principle components analysis (PCA) and by evaluating the auto and cross-correlation functions of skeletal muscle electromyograms when different periods of leg-grabbing throw performing was studied. It was shown than the electrical activity of large muscle synergies varies depending on the values of muscle efforts, typical for different periods of the performed movement. Skeletal muscle synergetic relationships are plastic in relation to their spatial and temporal organization, which provides reliable control of motor function in such conditions. [ABSTRACT FROM AUTHOR]

Foot Drop (FD) is a condition, which is very commonly found in post-stoke patients; however it can also be seen in patients with multiple sclerosis, and cerebral palsy. It is a sign of neuromuscular damage caused by the weakness of the muscles. There are various approaches of FD's rehabilitation, such as physiotherapy, surgery, and the use of technological devices. Recently, researchers have worked on developing various technologies to enhance assisting and rehabilitation of FD. This review analyzes different types of technologies available for FD. This include devices that are available commercially or still under research. 101 studies published between 2015 and 2020 were identified for the review, many were excluded due to various reasons, e.g., were not robot-based devices, did not include FD as one of the targeted diseases, or was insufficient information. 24 studies that met our inclusion criteria were assessed. These studies were further classified into two different categories: robot-based ankle-foot orthosis (RAFO) and Functional Electrical Stimulation (FES) devices. Studies included showed that both RAFO and FES showed considerable improvement in the gait cycle of the patients. Future trends are inclining towards integrating FES with other neuro-concepts such as muscle-synergies for further developments. [ABSTRACT FROM AUTHOR]

How our central nervous system efficiently controls our complex musculoskeletal system is still debated. The muscle synergy hypothesis is proposed to simplify this complex system by assuming the existence of functional neural modules that coordinate several muscles. Modularity based on muscle synergies can facilitate motor learning without compromising task performance. However, the effectiveness of modularity in motor control remains debated. This ambiguity can, in part, stem from overlooking that the performance of modularity depends on the mechanical aspects of modules of interest, such as the torque the modules exert. To address this issue, this study introduces two criteria to evaluate the quality of module sets based on commonly used performance metrics in motor learning studies: the accuracy of torque production and learning speed. One evaluates the regularity in the direction of mechanical torque the modules exert, while the other evaluates the evenness of its magnitude. For verification of our criteria, we simulated motor learning of torque production tasks in a realistic musculoskeletal system of the upper arm using feed-forward neural networks while changing the control conditions. We found that the proposed criteria successfully explain the tendency of learning performance in various control conditions. These result suggest that regularity in the direction of and evenness in magnitude of mechanical torque of utilized modules are significant factor for determining learning performance. Although the criteria were originally conceived for an error-based learning scheme, the approach to pursue which set of modules is better for motor control can have significant implications in other studies of modularity in general., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Fukunishi, Kutsuzawa, Owaki and Hayashibe.)

Uphill walking is a common task encountered in daily life, with steeper inclines potentially imposing greater biomechanical and neuromuscular demands on the human body. The heel-to-toe drop (HTD) in footwear may influence the biomechanical and neuromuscular pattern of uphill walking; but the impact remains unclear. Adjustments in HTD can modulate biomechanical and neuromuscular patterns, mitigating the demands and optimizing the body's response to different inclinations. We hypothesize that adjustments in HTD can modulate biomechanical and neuromuscular patterns, mitigating the demands and optimizing the body's response to different inclinations. Nineteen healthy men walked on an adjustable slope walkway, with varied inclinations (6°, 12°, 20°) and HTD shoes (10mm, 25mm, 40 mm), while the marker positions, ground reaction forces and electromyography data were collected. Our study reveals that gait temporo-spatial parameters are predominantly affected by inclination over HTD. Inclination has a more pronounced effect on kinematic variables, while both inclination and HTD significantly modulate kinetic and muscle synergy parameters. This study demonstrates that an increase in the inclination leads to changes in biomechanical and neuromuscular responses during uphill walking and the adjustment of HTD can modulate these responses during uphill walking. However, the present study suggests that an increased HTD may lead to elevated loads on the knee joint and these adverse effects need more attention., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Jiang, Qu, Yang, Chen, Gao, Sun and Huo.)

Background: Stand-to-sit (StandTS) is an important daily activity widely used in rehabilitation settings to improve strength, postural stability, and mobility. Modifications in movement smoothness and speed significantly influence the kinematics, kinetics, and muscle activation patterns of the movement. Understanding the impact of StandTS speed and smoothness on movement control can provide valuable insights for designing effective and personalized rehabilitation training programs., Research Question: How do the smoothness and speed of StandTS movement affect joint kinematics, kinetics, muscle activation patterns, and postural stability during StandTS?, Methods: Twelve healthy younger adults participated in this study. There were two StandTS conditions. In the reference condition, participants stood in an upright position with their feet positioned shoulder-width apart on the force plate. Upon receiving a visual cue, participants performed StandTS at their preferred speed. In the smooth condition, participants were instructed to perform StandTS as smoothly as possible, aiming to minimize contact pressure on the seat. Lower leg kinetics, kinematics, and coordination patterns of muscle activation during StandTS were measured: (1) angular displacement of the trunk, knee, and hip flexion; (2) knee and hip extensor eccentric work; (3) muscle synergy pattern derived from electromyography (EMG) activity of the leg muscles; and (4) postural sway in the anterior-posterior (A-P), medio-lateral (M-L), and vertical directions., Results: Compared to the reference condition, the smooth condition demonstrated greater eccentric knee extensor flexion and increased joint work in both the knee and hip joints. Analysis of specific muscle synergy from EMG activity revealed a significant increase in the relative contribution of hip joint muscles during the smooth condition. Additionally, a negative correlation was observed between knee extensor and vertical postural sway, as well as hip extensor work and M-L postural sway., Conclusion: Smooth StandTS facilitates enhanced knee eccentric control and increased joint work at both the hip and knee joints, along with increased involvement of hip joint muscles to effectively manage falling momentum during StandTS. Furthermore, the increased contributions of knee and hip joint work reduced postural sway in the vertical and M-L directions, respectively. These findings provide valuable insights for the development of targeted StandTS rehabilitation training., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Jeon, Dong, Dalby and Goh.)

Much of the current research on sprint start has attempted to analyze the biomechanical characteristics of elite athletes to provide guidance on the training of sprint technique, with less attention paid to the effects of motor experience gained from long-term training on neuromuscular control characteristics. The present study attempted to investigate the effect of motor experience on the modular organization of the neuromuscular system during starting, based on he clarification of the characteristics of muscle synergies during starting. It was found that exercise experience did not promote an increase in the number of synergies but rather a more focused timing of the activation of each synergy, allowing athletes to quickly complete the postural transition from crouching to running during the starting.

Muscle synergy has been widely acknowledged as a possible strategy of neuromotor control, but current research has ignored the potential inhibitory components in muscle synergies. Our study aims to identify and characterize the inhibitory components within motor modules derived from electromyography (EMG), investigate the impact of aging and motor expertise on these components, and better understand the nervous system's adaptions to varying task demands. We utilized a rectified latent variable model (RLVM) to factorize motor modules with inhibitory components from EMG signals recorded from ten expert pianists when they played scales and pieces at different tempo-force combinations. We found that older participants showed a higher proportion of inhibitory components compared with the younger group. Senior experts had a higher proportion of inhibitory components on the left hand, and most inhibitory components became less negative with increased tempo or decreased force. Our results demonstrated that the inhibitory components in muscle synergies could be shaped by aging and expertise, and also took part in motor control for adapting to different conditions in complex tasks.

Background: Although the spatio-temporal structure of muscle activation in cutting have been studied extensively, including time-varying motor primitives and time-invariant motor modules under various conditions, the factorisation methods suitable for cutting are unclear, and the extent to which each factorisation method loses information about movement during dimensionality reduction is uncertain., Research Question: To clarify the extent to which NMF, PCA and ICA retain information about movement when downscaling, and to explore the factorisation method suitable for cutting., Methods: The kinematic data during cutting was captured with a Vicon motion capture system, from which the kinematic features of the pelvic centre of mass were calculated. NMF, PCA and ICA were used to obtain muscle synergies based on sEMG of the cutting at different angles, respectively. A back propagation neural network was constructed using temporal component of synergy as input and the kinematics data of pelvic as output. Calculation of the Hurst index using fractal analysis based on the temporal component of muscle synergy., Results: The quality of sEMG reconstruction is significantly higher with ICA ( P  < 0.01) than with NMF and PCA for the cutting. The NMF reconstruction has a high degree of preservation of movement, whereas the ICA loses movement information about the most of the swing phase, and the PCA loses information related to the change of direction. Hurst index less than 0.5 for all three angles of cutting., Significance: NMF is suitable for extracting muscle synergies in all directions of cutting. Information related to movement may be lost when using PCA and ICA to extract the synergy of cutting. The high individual variability of muscle synergy in cutting may be responsible for the loss of movement information in muscle synergy., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)