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Objective To identify a novel physiologic marker of bulbar motor involvement in amyotrophic lateral sclerosis (ALS) based on jaw muscle synergies. Methods 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. Results 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. Conclusions 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. Significance 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.

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 researchStudies 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.

Sit-to-stand (STS) motion is an important daily activity and many post-stroke patients have difficulty in performing the STS motion. Post-stroke patients who can perform STS independently, still utilize four muscle synergies (synchronized muscle activation) as seen in healthy people. In addition, temporal muscle synergy features can reflect motor impairment of post-stroke patients. However, it has been unclear whether post-stroke patients improve their STS movements in short-term rehabilitation and which muscle synergy features can estimate this improvement. Here, we demonstrate that temporal features of muscle synergies which contribute to body extension and balance maintenance can estimate the effect of short-term rehabilitation based on machine learning methods. By analyzing muscle synergies of post-stroke patients (n = 33) before and with the intervention of physical therapists, we found that about half of the patients who were severely impaired, improved activation timing of muscle synergy to raise the hip with the intervention. Additionally, we identified the temporal features that can estimate whether severely impaired post-stroke patients improve. We conclude that temporal features of muscle synergies can estimate the motor recovery in short-term rehabilitation of post-stroke patients. This finding may lead to new rehabilitation strategies for post-stroke patients that focus on improving activation timing of different muscle synergies.

The aim of this study was to explore the underlying age-related differences in dynamic motor control during different step ascent conditions using muscle synergy analysis. Eleven older women (67.0 y &plusmn, 2.5) and ten young women (22.5 y &plusmn, 1.6) performed stepping in forward and lateral directions at step heights of 10, 20 and 30 cm. Surface electromyography was obtained from 10 lower limb and torso muscles. Non-negative matrix factorization was used to identify sets of (n) synergies across age groups and stepping conditions. In addition, variance accounted for (VAF) by the detected number of synergies was compared to assess complexity of motor control. Finally, correlation coefficients of muscle weightings and between-subject variability of the temporal activation patterns were calculated and compared between age groups and stepping conditions. Four synergies accounted for &gt, 85% VAF across age groups and stepping conditions. Age and step height showed a significant negative correlation with VAF during forward stepping but not lateral stepping, with lower VAF indicating higher synergy complexity. Muscle weightings showed higher similarity across step heights in older compared to young women. Neuromuscular control of young and community-dwelling older women could not be differentiated based on the number of synergies extracted. Additional analyses of synergy structure and complexity revealed subtle age- and step-height-related differences, indicating that older women rely on more complex neuromuscular control strategies.

AIM: To determine if muscle synergy structure (activations and weights) differs between gait patterns in children with spastic cerebral palsy (CP). METHOD: In this cross-sectional study, we classified 188 children with unilateral (n=82) or bilateral (n=106) spastic CP (mean age: 9y 5mo, SD: 4y 3mo, range: 3y 9mo-17y 7mo; 75 females; Gross Motor Function Classification System [GMFCS] level I: 106, GMFCS level II: 55, GMFCS level III: 27) into a minor deviations (n=34), drop foot (n=16), genu recurvatum (n=26), apparent equinus (n=53), crouch (n=39), and jump gait pattern (n=20). Surface electromyography recordings from eight lower limb muscles of the most affected side were used to calculate synergies with weighted non-negative matrix factorization. We compared synergy activations and weights between the patterns. RESULTS: Synergy structure was similar between gait patterns, although weights differed in the more impaired children (crouch and jump gait) when compared to the other patterns. Variability in synergy structure between participants was high. INTERPRETATION: The similarity in synergy structure between gait patterns suggests a generic motor control strategy to compensate for the brain lesion. However, the differences in weights and high variability between participants indicate that this generic motor control strategy might be individualized and dependent on impairment level. ispartof: DEVELOPMENTAL MEDICINE AND CHILD NEUROLOGY vol:64 issue:4 pages:462-468 ispartof: location:England status: published

Reaching and grasping (R&G) is a skilled voluntary movement which is critical for animals. In this work, we aim to identify muscle synergy patterns from R&G movements in rats and show how these patterns can be used to characterize such movements and investigate their consistency and repeatability. For that purpose, we analyzed the electromyographic (EMG) activity of five forelimb muscles recorded while the animals were engaged in R&G tasks. Our dataset included 200 R&G attempts from three different rats. Non-negative matrix factorization was used to decompose EMG signals and extract muscle synergies. We compared all pairs of attempts and created cross-validated models to study intra- and inter-subject variability. We found that three synergies were enough to accurately reconstruct the EMG envelopes. These muscle synergies and their corresponding activation coefficients were very similar for all the attempts in the database, providing a general pattern to describe the movement. Results suggested that the movement strategy adopted by an individual in its different attempts was highly repetitive, but also resembled the strategies adopted by the other animals. Inter-subject variability was not much higher than intra-subject variability. This study is a proof-of-concept, but the proposed approaches can help to establish whether there is a stereotyped pattern of neuromuscular activity in R&G movement in healthy rats, and the changes that occur in animal models of acute neurological injuries. Research on muscle synergies could elucidate motor control mechanisms, and lead to quantitative tools for evaluating upper limb motor impairment after an injury.

Human movement is complex, presenting clinical and research challenges regarding how it is described and investigated. This paper discusses the commonalities and differences on how human movement is conceptualized from neuroscientific and clinical perspectives with respect to postural control; the limitations of linear measures; movement efficiency with respect to metabolic energy cost and selectivity; and, how muscle synergy analysis may contribute to our understanding of movement variability. We highlight the role of sensory information on motor performance with respect to the base of support and alignment, illustrating a potential disconnect between the clinical and neuroscientific perspectives. The purpose of this paper is to discuss the commonalities and differences in how movement concepts are defined and operationalized by Bobath clinicians and the neuroscientific community to facilitate a common understanding and open the dialogue on the research practice gap.

Muscle synergies are the building blocks for generating movement by the central nervous system (CNS). According to this hypothesis, CNS decreases the complexity of motor control by combination of a small number of muscle synergies. The aim of this work is to investigate similarity of muscle synergies during cycling across various mechanical conditions. Twenty healthy subjects performed three 6- min cycling tasks at over a range of rotational speed (40, 50, and 60 rpm) and resistant torque (3, 5, and 7 N/m). Surface electromyography (sEMG) signals were recorded during pedaling from eight muscles of the right and left legs. We extracted four synchronous muscle synergies by using the non-negative matrix factorization (NMF) method. Mean and standard deviation of the goodness of the signal reconstruction (R2) for all subjects was obtained 0.9898 ± 0.0535. We investigated the functional roles of both leg muscles during cycling by synchronous muscle synergy extraction. We compared the muscle synergies extracted from all subjects in all mechanical conditions. The total mean and standard deviation of the similarity of synergy vectors for all subjects in all mechanical conditions was obtained 0.8788 ± 0.0709. We found the high degrees of similarity among the sets of synchronous muscle synergies across mechanical conditions and also across different subjects. Our results demonstrated that different subjects at different mechanical conditions use the same motor control strategies for cycling, despite inter-individual variability of muscle patterns.

International audience; Crosstalk is an important source of error in interpreting surface electromyography (EMG) signals. Here, we aimed at characterizing crosstalk for three groups of synergistic muscles by the identification of individual motor unit action potentials. Moreover, we explored whether spatial filtering (single and double differential) of the EMG signals influences the level of crosstalk. Three experiments were conducted. Participants (total twenty-five) performed isometric contractions at 10% of the maximal voluntary contraction (MVC) with digit muscles and knee extensors, and at 30% MVC with plantar flexors. High-density surface EMG signals were recorded and decomposed into motor unit spike trains. For each muscle, we quantified the crosstalk induced to neighboring muscles and the level of contamination by the nearby muscle activity. We also estimated the influence of crosstalk on the EMG power spectrum and intermuscular correlation. Most motor units (80%) generated significant crosstalk signals to neighboring muscle EMG in monopolar recording mode, but this proportion decreased with spatial filtering (50% and 42% for single and double differential, respectively). Crosstalk induced overestimations of intermuscular correlation and has a small effect on the EMG power spectrum, which indicates that crosstalk is not reduced with high-pass temporal filtering. Conversely, spatial filtering diminished the crosstalk magnitude and the overestimations of intermuscular correlation, confirming to be an effective and simple technique to reduce crosstalk. This paper presents a new method for the identification and quantification of crosstalk at the motor unit level and clarifies the influence of crosstalk on EMG interpretation for muscles with different anatomy.

Muscle synergy assessments are often employed to evaluate the modular organization of the spinal cord during a locomotion task. While they provide valuable insights into the pattern formation of the a-motoneurons at the spinal cord, by construction they cannot capture control from supra-spinal layers. We examined how locomotor muscle synergies are represented in the sensorimotor cortex, with particular focus on the cortico-synergy coherence as a measure of coupling along the cortico-spinal tract. Non-negative matrix factorization served to decompose multivariate electromyographic signals into muscle synergies. Their representations were localized in the cortex using coherence-based beamforming. Overall, the cortico-synergy coherence was maximal in sensorimotor areas especially in the beta-frequency band. However, only for the synergies timed to heel strike, that are related to the double support phases, the coherence was significant. These coherences were closely related to the timing of the activation patterns of the synergies, suggesting sensorimotor cortex to be strongly involved in emergence and control of these synergies.

In this paper, we present a novel muscle synergy extraction method based on multivariate curve resolution–alternating least squares (MCR-ALS) to overcome the limitation of the nonnegative matrix factorization (NMF) method for extracting non-sparse muscle synergy, and we study its potential application for evaluating motor function of stroke survivors. Nonnegative matrix factorization (NMF) is the most widely used method for muscle synergy extraction. However, NMF is susceptible to components’ sparseness and usually provides inferior reliability, which significantly limits the promotion of muscle synergy. In this study, MCR-ALS was employed to extract muscle synergy from electromyography (EMG) data. Its performance was compared with two other matrix factorization algorithms, NMF and self-modeling mixture analysis (SMMA). Simulated data sets were utilized to explore the influences of the sparseness and noise on the extracted synergies. As a result, the synergies estimated by MCR-ALS were the most similar to true synergies as compared with SMMA and NMF. MCR-ALS was used to analyze the muscle synergy characteristics of upper limb movements performed by healthy (n = 11) and stroke (n = 5) subjects. The repeatability and intra-subject consistency were used to evaluate the performance of MCR-ALS. As a result, MCR-ALS provided much higher repeatability and intra-subject consistency as compared with NMF, which were important for the reliability of the motor function evaluation. The stroke subjects had lower intra-subject consistency and seemingly had more synergies as compared with the healthy subjects. Thus, MCR-ALS is a promising muscle synergy analysis method for motor function evaluation of stroke patients.

Reactive stepping responses are essential to prevent falls after a loss of balance. It has previously been well described that both voluntary and reactive step training could improve the efficacy of reactive stepping in different populations. However, the effect of aging on neuromuscular control during voluntary and reactive stepping remains unclear. Electromyography (EMG) signals during both backward voluntary stepping in response to an auditory cue and backward reactive stepping elicited by a forward slip-like treadmill perturbation during stance were recorded in ten healthy young adults and ten healthy older adults. Using muscle synergy analysis, we extracted the muscle synergies for both voluntary and reactive stepping. Our results showed that fewer muscle synergies were used during reactive stepping than during voluntary stepping in both young and older adults. Minor differences in the synergy structure were observed for both voluntary and reactive stepping between age groups. Our results indicate that there is a low similarity of muscle synergies between voluntary stepping and reactive stepping and that aging had a limited effect on the structure of muscle synergies. This study enhances our understanding of the neuromuscular basis of both voluntary and reactive stepping as well as the potential effect of aging on neuromuscular control during balance tasks.

Voluntary movement could be initiated in spite of involuntary resting tremor in patients with Parkinson's disease (PD). It is unknown how the central nervous system (CNS) transits from the ongoing involuntary motor program of tremor to the execution of voluntary reaching movement. In this paper, muscle synergy analysis was used to unveil the motor module transitions from resting tremor to compound movement. Three tremor symptom dominant PD patients performed tasks of targeted forward reaching movements with background tremor. Kinematics and surface electromyography (EMG) of six muscles were recorded. Synergy vectors and time profiles were analyzed using EMG data during resting tremor and forward reaching. Results revealed that the representative vector of tremor remained unchanged during performance of voluntary movement. Other synergy vectors of tremor were modified to accommodate vectors of movement synergies. The merge of tremor module with movement module could be explained by a procedure of linear combination. The distribution of timing of movement initiation with respect to tremor cycle displayed a weak sign of clusters. The analysis suggested that the CNS combined two motor modules in order to initiate a voluntary movement with background tremor. More extensive analysis with a larger number of patients needs to be carried out to confirm these findings.

Early brain lesions which produce cerebral palsy (CP) may affect the development of walking. It is unclear whether or how neuromuscular control, as evaluated by muscle synergy analysis, differs in young children with CP compared to typically developing (TD) children with the same walking ability, before and after the onset of independent walking. Here we grouped twenty children with (high risk of) CP and twenty TD children (age 6.5–52.4 months) based on their walking ability, supported or independent walking. Muscle synergies were extracted from electromyography data of bilateral leg muscles using non-negative matrix factorization. Number, synergies’ structure and variability accounted for when extracting one (VAF1 ) or two (VAF2 ) synergies were compared between CP and TD. Children in the CP group recruited fewer synergies with higher VAF1 and VAF2 compared to TD children in the supported and independent walking group. The most affected side in children with asymmetric CP walking independently recruited fewer synergies with higher VAF1 compared to the least affected side. Our findings suggest that early brain lesions result in early alterations of neuromuscular control, specific for the most affected side in asymmetric CP.

Muscle coordination in human movement has been assessed through muscle synergy analysis. In sports science, this procedure has been mainly applied to the comparison between highly trained and unexperienced participants. However, the lack of knowledge regarding strength training exercises led us to study the differences in neural strategies to perform the power clean between weightlifters and untrained individuals. Synergies were extracted from electromyograms of 16 muscles of ten unexperienced participants and seven weightlifters. To evaluate differences, we determined the pairwise correlations for the synergy components and electromyographic profiles. While the shape of activation patterns presented strong correlations across participants of each group, the weightings of each muscle were more variable. The three extracted synergies were shifted in time with the unexperienced group anticipating synergy #1 (−2.46 ± 18.7%, p &lt, 0.001) and #2 (−4.60 ± 5.71%, 0.001) and delaying synergy #3 (1.86 ± 17.39%, p = 0.01). Moreover, muscle vectors presented more inter-group variability, changing the composition of synergy #1 and #3. These results may indicate an adaptation in intermuscular coordination with training, and athletes in an initial phase of training should attempt to delay the hip extension (synergy #1), as well as the upper-limb flexion (synergy #2).

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.

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.

The handstand is an uncommon posture, highly demanding in terms of muscle and joint stability, used in sporting and artistic practices in a variety of disciplines. Despite its becoming increasingly widespread, there is no specific way to perform a handstand, and the neuromuscular organizational mechanisms involved are unknown. The objective of this study was to determine the muscle synergy of four handstand postures through a semblance analysis based on wavelets of electromyographic signals in the upper limbs of experienced circus performers between 18- and 35-year old. The results show that there is a large difference in positive and negative correlations depending on the posture, which suggests that the more asymmetrical the position of the lower limbs, the greater the number of strategies to maintain the posture. Although it is not a statistically significant data, it is observed that the posture 3 in particular, possesses the greatest number of positive correlations, which suggests it has the greatest synergy.

We aim to develop an assist system that corrects changes in muscle synergy during human body movements. In this paper, we investigate the effect of a passive lower-limb assist device with four different spring arrangement patterns on human muscle synergy during standing motion. The results indicate was possible to change muscle synergies, which are dominant in the standing motion, without changing their composition.

Humans learn motor skills (MSs) through practice and experience and may then retain them for recruitment, which is effective as a rapid response for novel contexts. For an MS to be recruited for novel contexts, its recruitment range must be extended. In addressing this issue, we hypothesized that an MS is dynamically modulated according to the feedback context to expand its recruitment range into novel contexts, which do not involve the learning of an MS. The following two sub-issues are considered. We previously demonstrated that the learned MS could be recruited in novel contexts through its modulation, which is driven by dynamically regulating the synergistic redundancy between muscles according to the feedback context. However, this modulation is trained in the dynamics under the MS learning context. Learning an MS in a specific condition naturally causes movement deviation from the desired state when the MS is executed in a novel context. We hypothesized that this deviation can be reduced with the additional modulation of an MS, which tunes the MS-produced muscle activities by using the feedback gain signals driven by the deviation from the desired state. Based on this hypothesis, we propose a feedback gain signal-driven tuning model of a learned MS for its robust recruitment. This model is based on the neurophysiological architecture in the cortico-basal ganglia circuit, in which an MS is plausibly retained as it was learned and is then recruited by tuning its muscle control signals according to the feedback context. In this study, through computational simulation, we show that the proposed model may be used to neurophysiologically describe the recruitment of a learned MS in novel contexts.

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. 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). 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). 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.

Objective: To clarify whether there are any muscle synergy changes in individuals with knee osteoarthritis, and to determine whether muscle synergy analysis could be applied to other musculoskeletal diseases. Methods: Subjects in this study included 11 young controls (YC), 10 elderly controls (EC), and 10 knee osteoarthritis patients (KOA). Gait was assessed on a split-belt treadmill at 3 km/h. A non-negative matrix factorization (NNMF) was applied to the electromyogram data matrix to extract muscle synergies. To assess the similarity of each module, we performed the NNMF analysis assuming four modules for all of the participants. Further, we calculated joint angles to compare the kinematic data between the module groups. Results: The number of muscle modules was significantly lower in the EC (2–3) and KOA (2–3) groups than in the YC group (3–4), which reflects the merging of late swing and early stance modules. The EC and KOA groups also showed greater knee flexion angles in the early stance phase. Contrarily, by focusing on the module structure, we found that the merging of early and late stance modules is characteristic in KOA. Conclusion: The lower number of modules in the EC and KOA groups was due to the muscle co-contraction with increased knee flexion angle. Contrarily, the merging of early and late stance modules are modular structures specific to KOA and may be biomarkers for detecting KOA. Significance: Describing the changes in multiple muscle control associated with musculoskeletal degeneration can serve as a fundamental biomarker in joint disease.

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 $${R}^{2}=42.5\mathrm{\%}$$ R 2 = 42.5 % ). Those variables included variability accounted for ($$VAF$$ VAF ) 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.

Electromyography (EMG)-driven musculoskeletal modeling relies on high-quality measurements of muscle electrical activity to estimate muscle forces. However, a critical challenge for practical deployment of this approach is missing EMG data from muscles that contribute substantially to joint moments. This situation may arise due to either the inability to measure deep muscles with surface electrodes or the lack of a sufficient number of EMG electrodes. Muscle synergy analysis is a dimensionality-reduction approach to decompose a large number of muscle excitations into a small number of time-varying synergy excitations along with time-invariant synergy weights that define the contribution of each corresponding synergy excitation to a specific muscle excitation. This study evaluates how accurately missing muscle excitations can be predicted using synergy excitations extracted from muscles with available EMGs (henceforth called “synergy extrapolation”). The results were reported on a gait dataset collected from a stroke survivor walking on an instrumented treadmill at self-selected and fastest-comfortable speeds. The evaluation process started with full calibration of a lower-body EMG-driven model using 16-channel EMGs (including surface and indwelling) in each leg. One indwelling EMG (either iliopsoas or adductor longus) was then treated as unmeasured at a time. The synergy weights associated with the unmeasured muscle were predicted through solving a nonlinear optimization problem where the errors between inverse dynamics and EMG-driven joint moments were minimized. We also quantitatively evaluated how synergy analysis algorithms (principal component analysis (PCA) and non-negative matrix factorization (NMF)), EMG normalization methods, and number of synergies affect the accuracy of the predicted unmeasured muscle excitation. Synergy extrapolation performance was most influenced by the choice of synergy analysis algorithm and number of synergies. PCA with 5 or 6 synergies consistently predicted unmeasured muscle excitations most accurately and with greatest robustness to choice of EMG normalization method. Furthermore, the associated joint moment matching accuracy was comparable to that produced by the full EMG-driven calibration. The synergy extrapolation method described in this study may facilitate the assessment of human neuromuscular control and biomechanics in response to surgical or rehabilitation treatment when important EMG signals are missing.

Surface electromyography (EMG) measurements are affected by various noises such as power source and movement artifacts and adjacent muscle activities. Hardware solutions have been found that use multi-channel EMG signal to attenuate noise signals related to sensor positions. However, studies addressing the overcoming of crosstalk from EMG and the division of overlaid superficial and deep muscles are scarce. In this study, two signal decompositions—independent component analysis and non-negative matrix factorization—were used to create a low-dimensional input signal that divides noise, surface muscles, and deep muscles and utilizes them for movement classification based on direction. In the case of index finger movement, it was confirmed that the proposed decomposition method improved the classification performance with the least input dimensions. These results suggest a new method to analyze more dexterous movements of the hand by separating superficial and deep muscles in the future using multi-channel EMG signals.

Establishing a natural communication interface between the user and the terminal device is one of the central challenges of hand neuroprosthetics research. Surface electromyography (EMG) is the most common source of neural signals for interpreting a user’s intent in these interfaces. However, how the capacity of EMG generation is affected by various clinical parameters remains largely unknown. In this study, we examined the EMG activity of forearm muscles recorded from 11 transradially amputated subjects who performed a wide range of movements. EMG recordings from 40 able-bodied subjects were also analyzed to provide comparative benchmarks. By using non-negative matrix factorization, we extracted the synergistic EMG patterns for each subject to estimate the dimensionality of muscle control, under the framework of motor synergies. We found that amputees exhibited less than four synergies (with substantial variability related to the length of remaining limb and age), whereas able-bodied subjects commonly demonstrate five or more synergies. The results of this study provide novel insight into the muscle synergy framework and the design of natural myoelectric control interfaces.

Identifying balance deficits associated with aging is critical to preventing falls in elderly people. The purpose of this study was to investigate the effects of aging on the multi-muscle synergy in lower extremities during standing on sloped surfaces. Eighteen healthy elderly subjects and 18 healthy young subjects were recruited in the experiment. Subjects were required to stand quietly on slopes at 5 different angles for 30 s with and without visual feedback. Surface electromyography signals of muscles in the lower limbs were collected simultaneously during standing. The muscle synergy of synergistic muscles and of antagonistic muscles were quantified by the parameters of multidimensional recurrence quantification analysis (MdRQA). The results showed that the dynamical synergies in synergistic and antagonistic muscle groups were significantly enhanced in elderly group, especially during standing on sloped surfaces (p < 0.05). The MdRQA parameters were significantly increased when standing without visual feedback than with visual feedback (p < 0.05). The aging and the absence of visual feedback led to more deterministic structures in the dynamical coupling of muscle activations, indicating strengthened synergistic contractions of muscles. These changes in elderly may increase the restriction on balance control and reduce the adaptability of motor system to potential external perturbations. This study shed light on the effects of aging on standing balance control and may facilitate to develop novel strategies for evaluation of aging and predication of falls.

Muscle synergy is the theory that movements are controlled by a module of coordinated combined muscles. This theory is thought to solve the degrees-of-freedom problem in the musculoskeletal system. Previous studies have investigated the robustness of muscle synergies under conditions such as varying speeds and required degrees of accuracy. One of the principles of human movement is that when movement becomes faster, spatial accuracy is reduced. This is called the "speed–accuracy trade-off" (SAT), and many models have been proposed to explain this phenomenon. Studies on muscle synergies have shown that muscle synergy modules are robust against changes in speed; however, the relationship between SAT and motor control by muscle synergies remains unclear. Therefore, we investigated the relationship between changes in spatial accuracy and changes in speed and muscle synergies from measured behavioral data and surface electromyography. This was achieved by performing an isometric contraction task in which subjects exerted a horizontal force with various movement speeds. The results showed that the module structures of muscle synergies were robust against speed changes, and that the neural commands to muscle synergies changed in response to speed changes. In addition, changes in spatial accuracy with variations in speed tended to increase when movement was performed with a single muscle synergy. These results suggest that the number of muscle synergies used for movement may affect movement accuracy.Clinical Relevance—The results of this study suggest that the number of muscle synergies used for movement affects spatial accuracy.

Objective. Powered exoskeletons have been used to help persons with gait impairment regain some walking ability. However, little is known about its impact on neuromuscular coordination in persons with stroke. The objective of this study is to investigate how a powered exoskeleton could affect the neuromuscular coordination of persons with post-stroke hemiparesis. Approach. Eleven able-bodied subjects and ten stroke subjects participated in a single-visit treadmill walking assessment, in which their motion and lower-limb muscle activities were captured. By comparing spatiotemporal parameters, kinematics, and muscle synergy pattern between two groups, we characterized the normal gait pattern and the post-stroke motor deficits. Five eligible stroke subjects received exoskeleton-assisted gait trainings and walking assessments were conducted pre-intervention (Pre) and post-intervention (Post), without (WO) and with (WT) the exoskeleton. We compared their gait performance between (a) Pre and Post to investigate the effect of exoskeleton-assisted gait training and, (b) WO and WT the exoskeleton to investigate the effect of exoskeleton wearing on stroke subjects. Main results. While four distinct motor modules were needed to describe lower-extremity activities during stead-speed walking among able-bodied subjects, three modules were sufficient for the paretic leg from the stroke subjects. Muscle coordination complexity, module composition and activation timing were preserved after the training, indicating the intervention did not significantly change the neuromuscular coordination. In contrast, walking WT the exoskeleton altered the stroke subjects’ synergy pattern, especially on the paretic side. The changes were dominated by the activation profile modulation towards the normal pattern observed from the able-bodied group. Significance. This study gave us some critical insight into how a powered exoskeleton affects the stroke subjects’ neuromuscular coordination during gait and demonstrated the potential to use muscle synergy as a method to evaluate the effect of the exoskeleton training. This study was registered at ClinicalTrials.gov (identifier: NCT03057652).

Muscle synergy analysis is commonly used to study how the nervous system coordinates the activation of a large number of muscles during human reaching. In synergy analysis, muscle activation data collected from various reaching directions are subjected to dimensionality reduction techniques to extract muscle synergies. Typically, muscle activation data are obtained only from a limited set of reaches with an inherent assumption that the performed reaches adequately represent all possible reaches. In this study, we investigated how the number of reaching directions included in the synergy analysis influences the validity of the extracted synergies. We used a musculoskeletal model to compute muscle activations required to perform 36 evenly spaced planar reaches. Nonnegative matrix factorization (NMF) and principal component analysis (PCA) were then used to extract reference synergies. We then selected several subsets of reaches and compared the ability of the extracted synergies from each subset to represent the muscle activation from all 36 reaches. We found that 6 reaches were required to extract valid synergies, and a further reduction in the number of reaches changed the composition of the resulting synergies. Further, we found that the choice of reaching directions included in the analysis for a given number of reaches also affected the validity of the extracted synergies. These findings indicate that both the number and the choice of reaching directions included in the analysis impacted the validity of the extracted synergies.

Background: Walking problems in children with cerebral palsy (CP) can in part be explained by limited selective motor control. Muscle synergy analysis is increasingly used to quantify altered neuromuscular control during walking. The early brain injury in children with CP may lead to a different development of muscle synergies compared to typically developing (TD) children, which might characterize the abnormal walking patterns. Objective: The overarching aim of this review is to give an overview of the existing studies investigating muscle synergies during walking in children with CP compared to TD children. The main focus is on how muscle synergies differ between children with CP and TD children, and we examine the potential of muscle synergies as a measure to quantify and predict treatment outcomes. Methods: Bibliographic databases were searched by two independent reviewers up to 22 April 2019. Studies were included if the focus was on muscle synergies of the lower limbs during walking, obtained by a matrix factorization algorithm, in children with CP. Results: The majority (n = 12) of the 16 included studies found that children with CP recruited fewer muscle synergies during walking compared to TD children, and several studies (n = 8) showed that either the spatial or temporal structure of the muscle synergies differed between children with CP and TD children. Variability within and between subjects was larger in children with CP than in TD children, especially in more involved children. Muscle synergy characteristics before treatments to improve walking function could predict treatment outcomes (n = 3). Only minimal changes in synergies were found after treatment. Conclusions: The findings in this systematic review support the idea that children with CP use a simpler motor control strategy compared to TD children. The use of muscle synergy analysis as a clinical tool to quantify altered neuromuscular control and predict clinical outcomes seems promising. Further investigation on this topic is necessary, and the use of muscle synergies as a target for development of novel therapies in children with CP could be explored.

Currently, myoelectric prostheses lack dexterity and ease of control, in part because of inadequate schemes to extract relevant muscle features that can approximate muscle activation patterns that enable individuated dexterous finger motion. This project seeks to apply a novel algorithm pipeline that extracts muscle activation patterns from one limb, as well as from forearm muscles of the opposite limb, to predict muscle activation data of opposite limb intrinsic hand muscles, with the long-range goal of informing dexterous prosthetic control.

Healthy aging modifies neuromuscular control of dynamic balance. Challenging tasks could amplify such modifications, providing clinical insights. We examined the effects of age and walking condition difficulty on neuromuscular control of walking balance. We analyzed whole-body kinematics and activity of 13 right leg and trunk muscles in 17 young (11 males and 6 females; age 24 ± 3 years) and 14 older adults (3 males and 11 females; age 69 ± 4 years) while walking on a taped line on the floor and a 6-cm wide beam. Spatiotemporal parameters of gait, margin of stability, motor performance, and muscle synergies were estimated. Regardless of age, maintaining walking balance was more difficult on the beam compared to the taped line as evidenced by a shorter distance walked (17.3%), a reduction in step length (5.8%) and speed (10.3%), as well as a 40.0% smaller margin of stability during beam vs. tape walking. The number of muscle synergies was also higher during beam vs. tape walking. Compared to younger adults, older adults had larger margin of stability during beam walking. Older adults also had higher muscle co-activity within each muscle synergy and greater variance accounted for by the first muscle synergy regardless of condition. Such age-effects may be interpreted as a safer, less efficient, and less complex neuromuscular modular control strategy. In conclusion, beam walking increased the difficulty of maintaining walking balance and induced adaptations in modular control. It seems that healthy older adults reduce the complexity and efficiency of neuromuscular control of walking to preserve walking balance.

Over the last two decades, experimental studies in humans and other vertebrates have increasingly used muscle synergy analysis as a computational tool to examine the physiological basis of motor control. The theoretical background of muscle synergies is based on the potential ability of the motor system to coordinate muscles groups as a single unit, thus reducing high-dimensional data to low-dimensional elements. Muscle synergy analysis may represent a new framework to examine the pathophysiological basis of specific motor symptoms in Parkinson’s disease (PD), including balance and gait disorders that are often unresponsive to treatment. The precise mechanisms contributing to these motor symptoms in PD remain largely unknown. A better understanding of the pathophysiology of balance and gait disorders in PD is necessary to develop new therapeutic strategies. This narrative review discusses muscle synergies in the evaluation of motor symptoms in PD. We first discuss the theoretical background and computational methods for muscle synergy extraction from physiological data. We then critically examine studies assessing muscle synergies in PD during different motor tasks including balance, gait and upper limb movements. Finally, we speculate about the prospects and challenges of muscle synergy analysis in order to promote future research protocols in PD.

Humans walk adaptively in varying environments by manipulating their complicated and redundant musculoskeletal system. Although the central pattern generators in the spinal cord are largely responsible for adaptive walking through sensory-motor coordination, it remains unclear what neural mechanisms determine walking adaptability. It has been reported that locomotor rhythm and phase are regulated by the production of phase shift and rhythm resetting (phase resetting) for periodic motor commands in response to sensory feedback and perturbation. While the phase resetting has been suggested to make a large contribution to adaptive walking, it has only been investigated based on fictive locomotion in decerebrate cats, and thus it remains unclear if human motor control has such a rhythm regulation mechanism during walking. In our previous work, we incorporated a phase resetting mechanism into a motor control model and demonstrated that it improves the stability and robustness of walking through forward dynamic simulations of a human musculoskeletal model. However, this did not necessarily verify that phase resetting plays a role in human motor control. In our other previous work, we used kinematic measurements of human walking to identify the phase response curve (PRC), which explains phase-dependent responses of a limit cycle oscillator to a perturbation. This revealed how human walking rhythm is regulated by perturbations. In this study, we integrated these two approaches using a physical model and identification of the PRC to examine the hypothesis that phase resetting plays a role in the control of walking rhythm in humans. More specifically, we calculated the PRC using our neuromusculoskeletal model in the same way as our previous human experiment. In particular, we compared the PRCs calculated from two different models with and without phase resetting while referring to the PRC for humans. As a result, although the PRC for the model without phase resetting did not show any characteristic shape, the PRC for the model with phase resetting showed a characteristic phase-dependent shape with trends similar to those of the PRC for humans. These results support our hypothesis and will improve our understanding of adaptive rhythm control in human walking.

This study is aimed at comparing muscle activations and synergies in badminton forehand overhead smash (BFOS) between elite and nonelite players to clarify how the central nervous system (CNS) controls neuromuscular synergy and activation to generate complex overhead movements. EMG of five upper limb muscles was recorded through surface electromyography (EMG) electrodes from twenty players. Athletics is divided into two groups: elite and nonelite. Eventually, nonnegative matrix factorization (NNMF) was utilized to the calculated electromyography signals for muscle synergy comparison. Similarities between elite and nonelite groups were calculated by scalar product method. Results presented that three muscles synergies could sufficiently delineate the found electromyography signals for elite and nonelite players. Individual muscle patterns were moderately to highly similar between elite and nonelite groups (between-group similarity range: 0.52 to 0.90). In addition, high similarities between groups were found for the shape of synergy activation coefficients (range: 0.85 to 0.89). These results indicate that the synergistic organization of muscle coordination during badminton forehand overhead smash is not profoundly affected by expertise.

With modern upper limb myoelectric prostheses, many movements can be produced when many control signals are available. Some of them could originate from the multifunctional biceps brachii which appears to be composed of up to six individually innervated compartments. Given its compartmental nature, this muscle behaves as if composed of many individual muscles acting in synergy to achieve a given motor task. Through an appropriate synergy model, its EMG signals could thus be used to produce some of the many control signals required with modern upper limb myoelectric prostheses. Exploring that possibility, muscular synergy which is usually applied to a group of different muscles, was tested on the biceps brachii only. A non-negative matrix factorization method was applied on pre-recorded data consisting of 8 surface electromyographic signals collected across the biceps of 10 normal subjects who, in Seat or Stand posture, held their hand in 3 different postures. We found that muscular synergies can be extracted from the biceps brachii. With a learning process and a classifier, it was also possible, between a pair of static hand postures, to identify which one was used when a given record was made. The mean score of correctly detected hand posture was >80% for our subjects.

Is there a neuromuscular basis for falls? If so, it may provide new insight into falls and their assessment and treatment. We hypothesized that falls and recoveries from a laboratory-induced slip would be characterized by differences in multimuscle coordination patterns. Using muscle synergy analysis, we identified different multimuscle coordination patterns between older adults who fell and those who recovered from a laboratory-induced “feet-forward” slip. Participants who fell recruited fewer muscle synergies than participants who recovered. This suggests that a fall may result from recruitment of an inadequate number of muscle synergies to produce the necessary mechanical functions required to maintain balance. Participants who fell also recruited different muscle synergies, including one with high levels of coactivity consistent with a startle-like response. These differences in multimuscle coordination between slip outcomes were not accompanied by differences in slip difficulty or gait kinematics before or during the slip response. The differences in neuromuscular control may therefore reflect differences in sensorimotor control rather than kinematic constraints imposed by the slip, or the musculoskeletal system. Further research is required to test the robustness of these results and their interpretation with respect to additional mechanical variables (e.g., joint torques, ground reaction forces), responses to other fall types (e.g., trips), and within rather than between individuals. NEW & NOTEWORTHY Do falls and recoveries possess distinct neuromuscular features? We identified differences in neuromuscular control between older adults who fell and those who recovered from a “feet-forward” slip. Differences in neuromuscular control were not accompanied by differences in gait or slip kinematics before or during the slip response, suggesting differences in sensorimotor control rather than kinematics dictated the observed differences in neuromuscular control. An analysis of additional mechanical variables is required to confirm this interpretation.

We constructed a recurrent neural network model that can generate human reaching motion. Given a target position, the neural network model is capable of producing muscular activation signals that m...

Stroke patients suffer from declined physical ability, and it is important to analyze rehabilitation intervention and clarify its effect on the motion of patients. In this study, the effect of intervention on the standing-up motion of stroke patients is investigated. First, the intervention timing of a physical therapist (PT) is analyzed quantitatively from the muscle activity of upper limbs during therapy. Next, the intervention effect is evaluated based on body kinematics and muscle synergy. In this study, twenty trials are conducted, in which the standing-up motion of hemiplegic patients (n=12) is measured with and without the intervention by a PT. The results show that PTs teach hemiplegic patients the timing of lifting their buttocks during standing-up motion. Furthermore, it has been found that this intervention could improve the standing-up motion, although stroke patients had inadequate muscle synergy structure. In particular, some patients had delayed activation of the synergy and they could only stood up after they moved their center of mass toward their feet. However, the intervention by PTs could induce earlier activation of the synergy. Moreover, the intervention could properly shorten the activation duration of muscle synergy for those who had unusually inappropriate longer activation of synergy. These results imply that disordered and inadequate muscle synergy structure can be improved by proper intervention, and this study contributes to the further development of new rehabilitation methodologies.

Electromyogram signal (EMG) measurement frequently experiences uncertainty attributed to issues caused by technical constraints such as cross talk and maximum voluntary contraction. Due to these problems, individual EMGs exhibit uncertainty in representing their corresponding muscle activations. To regulate this uncertainty, we proposed an EMG refinement, which refines EMGs with regulating the contribution redundancy of the signals from EMGs to approximating torques through EMG-driven torque estimation (EDTE) using the muscular skeletal forward dynamic model. To regulate this redundancy, we must consider the synergistic contribution redundancy of muscles, including “unmeasured” muscles, to approximating torques, which primarily causes redundancy of EDTE. To suppress this redundancy, we used the concept of muscle synergy, which is a key concept of analyzing the neurophysiological regulation of contribution redundancy of muscles to exerting torques. Based on this concept, we designed a muscle-synergy-based EDTE as a framework for EMG refinement, which regulates the abovementioned uncertainty of individual EMGs in consideration of unmeasured muscles. In achieving the proposed EMG refinement, the most considerable point is to suppress a large change such as overestimation attributed to enhancement of the contribution of particular muscles to estimating torques. Therefore it is reasonable to refine EMGs by minimizing the change in EMGs. To evaluate this model, we used a Bland-Altman plot, which quantitatively evaluates the proportional bias of refined signals to EMGs. Through this evaluation, we showed that the proposed EDTE minimizes the bias while approximating torques. Therefore this minimization optimally regulates the uncertainty of EMGs and thereby leads to optimal EMG refinement.

This study aimed to identify muscle synergies of the lower limb during treadmill running on level and inclined ground. Eight subjects ran on a treadmill at three speeds (2.5, 3.3, and 4.1 m/s) and two grades (level and 10% grade). Surface electromyographic (EMG) signals were recorded from 10 muscles of the lower limb, including deeper muscles such as vastus intermedius, adductor magnus, and adductor longus. Muscle synergies were extracted applying a non-negative matrix factorization algorithm, and relative co-activations across muscles and the temporal recruitment pattern were identified by muscle synergy vector and synergy activation coefficient, respectively. The scalar product between pairs of synergy vectors and synergy activation coefficients during level and uphill running conditions were analyzed as a similarity index, with values above 0.8 recognized as similar. Approximately 4 muscle synergies controlled the majority of variability in 10 EMGs during running, and were common between level and uphill conditions. At each running speed, inter-condition similarity was observed in synergy vector (r > 0.83) and synergy activation coefficients (r > 0.84) at each type of synergy. These results suggest that types of synergy are consistent between level and uphill running.

Muscle synergy describes reduced set of functional muscle co-activation patterns. We aimed to identify muscle synergies of turning compared with straight walking. Twelve healthy adults (men: 7, women: 5) performed straight walking (SW), left turning (LT), and right turning (RT) at self-selected speeds. By using non-negative matrix factorization (NMF), we extracted muscle synergies from sixteen electromyography (EMG) signals on the right side and assigned similar muscle synergies among SW, LT, and RT into the same cluster by combining k-means clustering and intraclass correlation coefficient (ICC) analysis. We obtained task-specific clusters of muscle synergies extracted from SW, LT, or RT condition and identified the clusters that share synergies among the conditions. The central nervous system produces specific synergies involving turning behaviors and fundamental synergies for walking.

Background Physiological evidence suggests that the nervous system controls motion by using a low-dimensional synergy organization for muscle activation. Because the muscle activation produces joint torques, kinetic changes accompanying aging can be related to changes in muscle synergies. Objectives We explored the effects of aging on muscle synergies underlying sit-to-stand tasks, and examined their relationships with kinetic characteristics. Methods Four younger and three older adults performed the sit-to-stand task at two speeds. Subsequently, we extracted the muscle synergies used to perform these tasks. Hierarchical cluster analysis was used to classify these synergies. We also calculated kinetic variables to compare the groups. Results Three independent muscle synergies generally appeared in each subject. The spatial structure of these synergies was similar across age groups. The change in motion speed affected only the temporal structure of these synergies. However, subject-specific muscle synergies and kinetic variables existed. Conclusions Our results suggest common muscle synergies underlying the sit-to-stand task in both young and elderly adults. People may actively change only the temporal structure of each muscle synergy. The precise subject-specific structuring of each muscle synergy may incorporate knowledge of the musculoskeletal kinetics.

It is largely unknown how the CNS regulates multiple muscle systems in the presence of pain. This study used muscle synergy analysis to investigate multiple forearm muscles in individuals with chronic elbow pain during the development of grip force. Eleven individuals with chronic elbow pain and 11 healthy age-matched control subjects developed grip force to 15% and 30% of maximum voluntary contraction (MVC). Surface electromyography was obtained from six forearm muscles during force development before nonnegative matrix factorization was performed. The relationship between muscle synergies and standard clinical tests of elbow pain were examined by linear regression. During grip force development to 15% MVC the pain group had a lower number of forearm muscle synergies, increased similarity in spatial activation patterns, increased cocontraction of forearm flexors, and a greater magnitude of muscle weightings across the forearm when performing the task. During the 30% MVC grip the numbers of muscle synergies were the same for both groups; however, the pain group had lower activation and reduced variability in the timing of peak activation. The timing of peak activation was delayed in the pain group regardless of the task, and performing the grip in different wrist postures did not affect muscle synergy characteristics in either group. Although localized pain causes direct dysfunction of an affected muscle, this study provides evidence that the timing and amplitude of agonist and antagonist muscle activity are also affected with chronic pain. NEW & NOTEWORTHY Muscle activation patterns of individuals with chronic elbow pain are simplified compared with healthy individuals. This is apparent as individuals with pain exhibit fewer forearm muscle synergies, and increased similarity of activation patterns between forearm muscles, when performing pain-free isometric gripping. As such, even during pain-free tasks it is possible to observe changes in motor control in people with chronic pain.

Motor activities during daily life always involve simultaneous control of multiple degrees of freedom (DOFs), which has not yet been fully explored in myoelectric control due to difficulty in sufficiently decoding the complex neural control information. This study presents a novel framework for simultaneous myoelectric control based on pattern recognition incorporated with a muscle synergy motor control strategy for each DOF. An experiment for discriminating 18 dexterous finger movement tasks was designed to evaluate the performance of the framework for the simultaneous control of 5 DOFs. Task discrimination was assessed with 18 neurologically intact subjects, and the framework exhibited high accuracy (96.79% ±2.46%), outperforming three other methods, including the routine myoelectric pattern-recognition approach for conventional sequential control ( p

OBJECTIVE Muscle synergy is the activation of a group of muscles that contribute to a particular movement. The goal of the present study is to examine the hypothesis that human reaching movements at different speeds share similar muscle synergies and to investigate the kinesiology basis and innervation of muscles. METHODS Electromyographic activity from six muscles of the upper limb and shoulder girdle were recorded during three movements at different speeds, i.e. slow, moderate and fast. The effect of window length on the RMS signal of the EMG was analyzed and then EMG envelope signals were decomposed using non-negative matrix factorization. For each of the ten subjects, three synergies were extracted which accounted for at least 99% of the VAF. For each movement, the muscle synergies and muscle activation coefficients of all participants were clustered in to three partitions. Investigation showed a high similarity and dependency of cluster members due to the cosine similarity and mutual information in muscle synergy clustering. For further verification, the EMG envelope signals for all subjects were reconstructed. RESULTS The results indicated a lower reconstruction error using the center of the muscle synergy clusters in comparison with the average of the activation coefficients, which confirms the current research's hypothesis.

Changing the gait is crucial for adaptive and smooth locomotion of animals. Although it remains unclear what makes animals decide the gait, energy efficiency is an important factor. It has been reported that the relationship of the oxygen consumption with the speed is U-shaped for each horse gait and that different gaits have different speeds at which oxygen consumption is minimized. This allows the horse to produce energy-efficient locomotion in a wide speed range by changing the gait. However, the underlying mechanisms why the oxygen consumption is U-shaped and why the speeds for the minimum consumption are different between the gaits are unclear. In the present study, we used a neuromusculoskeletal model of the rat to examine the mechanism from a dynamic viewpoint. Specifically, we constructed the musculoskeletal part of the model based on empirical anatomical data of the rat and the motor control model based on the physiological concepts of the spinal central pattern generator and muscle synergy. We also incorporated the posture and speed regulation models at the levels of the brainstem and cerebellum. Our model achieved walking through forward dynamic simulation and the simulated joint kinematics and muscle activities were compared with animal data. Our model also achieved trotting by changing only the phase difference of the muscle-synergy-based motor commands between the forelimb and hindlimb. Furthermore, the speed of each gait varied by changing only the extension phase duration and amplitude of the muscle-synergy-based motor commands and reference values for the regulation models. The relationship between the cost of transport (CoT) and speed was U-shaped for both the generated walking and trotting and the speeds for the minimum CoT were different for the two gaits, as observed in the oxygen consumption of horses. We found that the resonance property and the posture and speed regulations contributed to the CoT shape and difference in the speeds for the minimum CoT. We further discussed the energy efficiency of gait based on the simulation results.

In this study, seven-channel electromyography signal-based two-dimensional wrist joint movement estimation with and without handgrip motions was carried out. Electromyography signals were analyzed using the synergy-based linear regression model and musculoskeletal model; they were subsequently compared with respect to single and combined wrist joint movements and handgrip. Using each one of wrist motion and grip trial as a training set, the synergy-based linear regression model exhibited a statistically significant performance with 0.7891 ± 0.0844 Pearson correlation coefficient (r) value in two-dimensional wrist motion estimation compared with 0.7608 ± 0.1037 r value of the musculoskeletal model. Estimates on the grip force produced 0.8463 ± 0.0503 r value with 0.2559 ± 0.1397 normalized root-mean-square error of the wrist motion range. This continuous wrist and handgrip estimation can be considered when electromyography-based multi-dimensional input signals in the prosthesis, virtual interface, and rehabilitation are needed.

Many studies have demonstrated covariation between muscle activations during behavior, suggesting that muscles are not controlled independently. According to one common proposal, this covariation reflects simplification of task performance by the nervous system so that muscles with similar contributions to task variables are controlled together. Alternatively, this covariation might reflect regulation of low-level aspects of movements that are common across tasks, such as stresses within joints. We examined these issues by analyzing covariation patterns in quadriceps muscle activity during locomotion in rats. The three monoarticular quadriceps muscles (vastus medialis [VM], vastus lateralis [VL], and vastus intermedius [VI]) produce knee extension and so have identical contributions to task performance; the biarticular rectus femoris (RF) produces an additional hip flexion. Consistent with the proposal that muscle covariation is related to similarity of muscle actions on task variables, we found that the covariation between VM and VL was stronger than their covariations with RF. However, covariation between VM and VL was also stronger than their covariations with VI. Since all vastii have identical actions on task variables, this finding suggests that covariation between muscle activity is not solely driven by simplification of overt task performance. Instead, the preferentially strong covariation between VM and VL is consistent with the control of internal joint stresses: Since VM and VL produce opposing mediolateral forces on the patella, the high positive correlation between their activation minimizes the net mediolateral patellar force. These results provide important insights into the interpretation of muscle covariations and their role in movement control., This research was supported by NIH Grant NS086973 (M.C.T.).