Muscle synergy analysis in children with cerebral palsy

Changes in walking function and neural control following pelvic cancer surgery with reconstruction

Introduction: Surgical planning and custom prosthesis design for pelvic cancer patients are challenging due to the unique clinical characteristics of each patient and the significant amount of pelvic bone and hip musculature often removed. Limb-sparing internal hemipelvectomy surgery with custom prosthesis reconstruction has become a viable option for this patient population. However, little is known about how post-surgery walking function and neural control change from pre-surgery conditions. Methods: This case study combined comprehensive walking data (video motion capture, ground reaction, and electromyography) with personalized neuromusculoskeletal computer models to provide a thorough assessment of pre- to post-surgery changes in walking function (ground reactions, joint motions, and joint moments) and neural control (muscle synergies) for a single pelvic sarcoma patient who received internal hemipelvectomy surgery with custom prosthesis reconstruction. Pre- and post-surgery walking function and neural control were quantified using pre- and post-surgery neuromusculoskeletal models, respectively, whose pelvic anatomy, joint functional axes, muscle-tendon properties, and muscle synergy controls were personalized using the participant's pre-and post-surgery walking and imaging data. For the post-surgery model, virtual surgery was performed to emulate the implemented surgical decisions, including removal of hip muscles and implantation of a custom prosthesis with total hip replacement. Results: The participant's post-surgery walking function was marked by a slower self-selected walking speed coupled with several compensatory mechanisms necessitated by lost or impaired hip muscle function, while the participant's post-surgery neural control demonstrated a dramatic change in coordination strategy (as evidenced by modified time-invariant synergy vectors) with little change in recruitment timing (as evidenced by conserved time-varying synergy activations). Furthermore, the participant's post-surgery muscle activations were fitted accurately using his pre-surgery synergy activations but fitted poorly using his pre-surgery synergy vectors. Discussion: These results provide valuable information about which aspects of post-surgery walking function could potentially be improved through modifications to surgical decisions, custom prosthesis design, or rehabilitation protocol, as well as how computational simulations could be formulated to predict post-surgery walking function reliably given a patient's pre-surgery walking data and the planned surgical decisions and custom prosthesis design.

Does crouch alter the effects of neuromuscular impairments on gait? A simulation study

Cerebral palsy (CP) is a neurologic injury that impacts control of movement. Individuals with CP also often develop secondary impairments like weakness and contracture. Both altered motor control and secondary impairments influence how an individual walks after neurologic injury. However, understanding the complex interactions between and relative effects of these impairments makes analyzing and improving walking capacity in CP challenging. We used a sagittal-plane musculoskeletal model and neuromuscular control framework to simulate crouch and nondisabled gait. We perturbed each simulation by varying the number of synergies controlling each leg (altered control), and imposed weakness and contracture. A Bayesian Additive Regression Trees (BART) model was also used to parse the relative effects of each impairment on the muscle activations required for each gait pattern. By using these simulations to evaluate gait-pattern specific effects of neuromuscular impairments, we identified some advantages of crouch gait. For example, crouch tolerated 13 % and 22 % more plantarflexor weakness than nondisabled gait without and with altered control, respectively. Furthermore, BART demonstrated that plantarflexor weakness had twice the effect on total muscle activity required during nondisabled gait than crouch gait. However, crouch gait was also disadvantageous in the presence of vasti weakness: crouch gait increased the effects of vasti weakness on gait without and with altered control. These simulations highlight gait-pattern specific effects and interactions between neuromuscular impairments. Utilizing computational techniques to understand these effects can elicit advantages of gait deviations, providing insight into why individuals may select their gait pattern and possible interventions to improve energetics.

Understanding muscle coordination during gait based on muscle synergy and its association with symptoms in patients with knee osteoarthritis

OBJECTIVE

We aimed to investigate the muscle coordination differences between a control group and patients with mild and severe knee osteoarthritis (KOA) using muscle synergy analysis and determine whether muscle coordination was associated with symptoms of KOA.

METHOD

Fifty-three women with medial KOA and 19 control patients participated in the study. The gait analyses and muscle activity measurements of seven lower limb muscles were assessed using a motion capture system and electromyography. Gait speed and knee adduction moment impulse were calculated. The spatiotemporal components of muscle synergy were extracted using non-negative matrix factorization, and the dynamic motor control index during walking (walk-DMC) was computed. The number of muscle synergy and their spatiotemporal components were compared among the mild KOA, severe KOA, and control groups. Moreover, the association between KOA symptoms with walk-DMC and other gait parameters was evaluated using multi-linear regression analysis.

RESULTS

The number of muscle synergies was lower in mild and severe KOA compared with those in the control group. In synergy 1, the weightings of biceps femoris and gluteus medius in severe KOA were higher than that in the control group. In synergy 3, the weightings of higher tibial anterior and lower gastrocnemius lateralis were confirmed in the mild KOA group. Regression analysis showed that the walk-DMC was independently associated with knee-related symptoms of KOA after adjusting for the covariates.

CONCLUSIONS

Muscle coordination was altered in patients with KOA. The correlation between muscle coordination and KOA may be attributed to the knee-related symptoms. Key points • Patients with knee osteoarthritis (OA) experienced a deterioration in muscle coordination when walking. • Loss of muscle coordination was associated with severe knee-related symptoms in knee OA. • Considering muscle coordination as a knee OA symptom-related factor may provide improved treatment.

Compromised neuromuscular function of walking in people with diabetes: a narrative review

AIM

This review summarizes recent studies that have investigated the neuromuscular dysfunction of walking in people with diabetes and its relationship to ulcer formation.

METHODS

A comprehensive electronic search in the database (Scopus, Web of Science, PsycINFO, ProQuest, and PubMed) was performed for articles pertaining to diabetes and gait biomechanics.

RESULTS

The Achilles tendon is thicker and stiffer in those with diabetes. People with diabetes demonstrate changes in walking kinematics and kinetics, including slower self-selected gait speed, shorter stride length, longer stance phase duration, and decreased ankle, knee, and metatarsophalangeal (MTP) joint range of motion. EMG is altered during walking and may reflect diabetes-induced changes in muscle synergies. Synergies are notable because they provide a more holistic pattern of muscle activations and can help develop better tools for characterizing disease progression.

CONCLUSION

Diabetes compromises neuromuscular coordination and function. The mechanisms contributing to ulcer formation are incompletely understood. Diabetes-related gait impairments may be a significant independent risk factor for the development of foot ulcers.

Muscle synergy analysis of eight inter-limb coordination modes during human hands-knees crawling movement

In order to reveal in-depth the neuromuscular control mechanism of human crawling, this study carries out muscle synergy extraction and analysis on human hands-knees crawling under eight specific inter-limb coordination modes, which are defined according to the swing sequence of limbs and includes two-limb swing crawling modes and six single-limb swing crawling modes. Ten healthy adults participate in crawling data collection, and surface electromyography (sEMG) signals are recorded from 30 muscles of limbs and trunk. Non-negative matrix factorization (NNMF) algorithm is adopted for muscle synergy extraction, and a three-step muscle synergy analysis scheme is implemented by using the hierarchical clustering method. Based on results of muscle synergy extraction, 4 to 7 synergies are extracted from each participant in each inter-limb coordination mode, which supports the muscle synergy hypothesis to some extent, namely, central nervous system (CNS) controls the inter-limb coordination modes during crawling movement by recruiting a certain amount of muscle synergies, rather than a single muscle. In addition, when different participants crawl in the same inter-limb coordination mode, they share more temporal features in recruiting muscle synergies. Further, by extracting and analyzing intra-mode shared synergies among participants and inter-mode shared synergies among the eight inter-limb coordination modes, the CNS is found to realize single-limb swing crawling modes by recruiting the four inter-mode shared synergy structures related to the swing function of each limb in different orders, and realize the two-limb swing crawling modes by recruiting synchronously two intra-mode shared synergy structures. The research results of the muscle synergy analysis on the eight specific inter-limb coordination modes, on the one hand, provide a basis for muscle synergy hypothesis from the perspective of crawling motion, on the other hand, also provide a possible explanation for the choice of the inter-limb coordination mode in human crawling.

Motor control complexity can be dynamically simplified during gait pattern exploration using motor control-based biofeedback

Understanding how the central nervous system coordinates diverse motor outputs has been a topic of extensive investigation. Although it is generally accepted that a small set of synergies underlies many common activities, such as walking, whether synergies are equally robust across a broader array of gait patterns or can be flexibly modified remains unclear. Here, we evaluated the extent to which synergies changed as nondisabled adults (n = 14) explored gait patterns using custom biofeedback. Secondarily, we used Bayesian additive regression trees to identify factors that were associated with synergy modulation. Participants explored 41.1 ± 8.0 gait patterns using biofeedback, during which synergy recruitment changed depending on the type and magnitude of gait pattern modification. Specifically, a consistent set of synergies was recruited to accommodate small deviations from baseline, but additional synergies emerged for larger gait changes. Synergy complexity was similarly modulated; complexity decreased for 82.6% of the attempted gait patterns, but distal gait mechanics were strongly associated with these changes. In particular, greater ankle dorsiflexion moments and knee flexion through stance, as well as greater knee extension moments at initial contact, corresponded to a reduction in synergy complexity. Taken together, these results suggest that the central nervous system preferentially adopts a low-dimensional, largely invariant control strategy but can modify that strategy to produce diverse gait patterns. Beyond improving understanding of how synergies are recruited during gait, study outcomes may also help identify parameters that can be targeted with interventions to alter synergies and improve motor control after neurological injury.NEW & NOTEWORTHY We used a motor control-based biofeedback system and machine learning to characterize the extent to which nondisabled adults can modulate synergies during gait pattern exploration. Results revealed that a small library of synergies underlies an array of gait patterns but that recruitment from this library changes as a function of the imposed biomechanical constraints. Our findings enhance understanding of the neural control of gait and may inform biofeedback strategies to improve synergy recruitment after neurological injury.

Analysis of cerebral palsy gait based on movement primitives

BACKGROUND

Cerebral palsy is the most prevalent motor disorder among children. Despite extensive studies on motor modularity of gait of children with cerebral palsy, kinematic modularity of their gait has not been addressed which is the main goal of this study.

METHODS

The kinematics of the gait of 13 typical development children and 188 children with cerebral palsy was captured and analyzed, where the cerebral palsy children were grouped into True, Jump, Apparent, and Crouch. Non-negative matrix factorization method was used to extract the kinematic modulus of each group, which were then clustered to find their characteristic movement primitives. The movement primitives of groups were then matched based on the similarity of their activation profiles.

FINDINGS

The number of movement primitives was three for the Crouch group, four for the other cerebral palsy groups, and five for the typical development group. Compared to the typical development children, the kinematic modules and activations of the cerebral palsy groups involved higher variability and co-activation, respectively (P < 0.05). Three temporally matched movement primitives were shared by all groups, but with altered structures.

INTERPRETATION

The gait of children with cerebral palsy involved lower complexity and higher variability due to the reduced and inconsistent kinematic modularity. Three basic movement primitives were sufficient to prodcue the overall gait kinematics, as observed in the Crouch group. Other movement primitives, were responsible for providing smooth transitions between basic movement primitives, as seen in more complex gait patterns.

Recent developments in muscle synergy analysis in young people with neurodevelopmental diseases: A Systematic Review

The central nervous system simplifies motor control by sending motor commands activating groups of muscles, known as synergies. Physiological locomotion can be described as a coordinated recruitment of four to five muscle synergies. The first studies on muscle synergies in patients affected by neurological diseases were on stroke survivors. They showed that synergies can be used as biomarkers for motor impairment as they vary in patients with respect to healthy people. Likewise, muscle synergy analysis has been applied to developmental diseases (DD). The need for a comprehensive view of the present findings is crucial for comparing results achieved so far and promote future directions in the field. In the present review, we screened three scientific databases and selected thirty-six papers investigating muscle synergies extracted from locomotion in children affected by DD. Thirty-one articles investigate how cerebral palsy (CP) influences motor control, the currently exploited method in studying motor control in CP and finally the effects of treatments in these patients in terms of synergies and biomechanics; two articles investigate how muscle synergies vary in Duchenne muscular dystrophy (DMD), and three other articles assess other developmental pathologies, such as chronic and acute neuropathic pain. For CP, most of the studies demonstrate that the number of synergies is lower and that the synergy composition varies in the affected children with respect to normal controls. Still, the predictability of treatment's effects and the etiology of muscle synergy variation are open questions, as it has been reported that treatments minimally modify synergies, even if they improve biomechanics. The application of different algorithms in extracting synergies might bring about more subtle differences. Considering DMD, no correlation was found between non-neural muscle weakness and muscle modules' variation, while in chronic pain a decreased number of synergies was observed as a possible consequence of plastic adaptations. Even if the potential of the synergistic approach for clinical and rehabilitation practices is recognized, there is not full consensus on protocols nor widely accepted guidelines for the systematic clinical adoption of the method in DD. We critically commented on the current findings, on the methodological issues and the relative open points, and on the clinical impact of muscle synergies in neurodevelopmental diseases to fill the gap for applying the method in clinical practice.

Influence of the number of muscles and strides on selective motor control during gait in individuals with cerebral palsy

OBJECTIVE

To evaluate the influence of the number of muscles and strides on estimating motor control accuracy during treadmill-gait, in individuals with cerebral palsy (CP).

METHODS

Bilateral lower limb electromyography data were extracted for 44 children/adolescents with CP. The number of synergy solutions required to explain 90 % of the variance (tVAF-threshold) and the total variance accounted for by one synergy (tVAF₁) were calculated for a different number of strides (between 5 and 50) and muscles both unilaterally (four to seven) and bilaterally (eight to 14). The kappa and intraclass correlation coefficients were used to assess similarities in tVAF-threshold and tVAF₁ between the different number of strides and muscle sets.

RESULTS

In both analyses, the number of muscles influenced the tVAF-threshold. Additionally, using <30 strides led to only substantial-moderate agreement with 50 strides (k < 0.80). In both analyses, the mean tVAF₁ values demonstrated high-agreement between the different number of muscles (intraclass-correlations = 0.88-0.93) and strides (intraclass-correlations = 0.96-0.99); In the group level, it may result in an error of ≤2.3 %. However, in the individual level, using different number of muscles or <40 strides may result in an error of ≥6 %.

CONCLUSION

Differing numbers of muscles and strides did not influence the group mean tVAF₁ value, but it influenced the tVAF-threshold value. In addition, using different number of muscles or strides can lead to a large measurement error in the individual tVAF₁ value.

Estimation of Time-Frequency Muscle Synergy in Wrist Movements

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.

A muscle synergy-based method to estimate muscle activation patterns of children with cerebral palsy using data collected from typically developing children

Preparing children with cerebral palsy prior to gait analysis may be a challenging and time-intensive task, especially when large number of sensors are involved. Collecting minimum number of electromyograms (EMG) and yet providing adequate information for clinical assessment might improve clinical workflow. The main goal of this study was to develop a method to estimate activation patterns of lower limb muscles from EMG measured from a small set of muscles in children with cerebral palsy. We developed and implemented a muscle synergy extrapolation method able to estimate the full set of lower limbs muscle activation patterns from only three experimentally measured EMG. Specifically, we extracted a set of hybrid muscle synergies from muscle activation patterns of children with cerebral palsy and their healthy counterparts. Next, those muscle synergies were used to estimate activation patterns of muscles, which were not initially measured in children with cerebral palsy. Two best combinations with three (medial gastrocnemius, semi membranous, and vastus lateralis) and four (lateral gastrocnemius, semi membranous, sartorius, and vastus medialis) experimental EMG were able to estimate the full set of 10 muscle activation patterns with mean (± standard deviation) variance accounted for of 79.93 (± 9.64)% and 79.15 (± 6.40)%, respectively, using only three muscle synergies. In conclusion, muscle activation patterns of unmeasured muscles in children with cerebral palsy can be estimated from EMG measured from three to four muscles using our muscle synergy extrapolation method. In the future, the proposed muscle synergy-based method could be employed in gait clinics to minimise the required preparation time.

Number of synergies impacts sensitivity of gait to weakness and contracture

Muscle activity during gait can be described by a small set of synergies, weighted groups of muscles, that are theorized to reflect underlying neural control. For people with neurologic injuries, like cerebral palsy or stroke, even fewer synergies are required to explain muscle activity during gait. This reduction in synergies is thought to reflect altered control and is associated with impairment severity and treatment outcomes. Individuals with neurologic injuries also develop secondary musculoskeletal impairments, like weakness or contracture, that can impact gait. Yet, the combined impacts of altered control and musculoskeletal impairments on gait remains unclear. In this study, we use a two-dimensional musculoskeletal model constrained to synergy control to simulate unimpaired gait. We vary the number of synergies, while simulating muscle weakness and contracture to examine how altered control impacts sensitivity to musculoskeletal impairment while tracking unimpaired gait. Results demonstrate that reducing the number of synergies increases sensitivity to weakness and contracture for specific muscle groups. For example, simulations using five-synergy control tolerated 40% and 51% more knee extensor weakness than those using four- or three-synergy control, respectively. Furthermore, when constrained to four- or three-synergy control, the model was increasingly sensitive to contracture and weakness of proximal muscles, such as the hamstring and hip flexors. Contrastingly, neither the amount of generalized nor plantarflexor weakness tolerated was affected by the number of synergies. These findings highlight the interactions between altered control and musculoskeletal impairments, emphasizing the importance of measuring and incorporating both in future simulation and experimental studies.

Synergies are minimally affected during emulation of cerebral palsy gait patterns

Muscle synergy analysis is commonly used to characterize motor control during dynamic tasks like walking. For clinical populations, such as children with cerebral palsy (CP), synergies are altered compared to nondisabled (ND) peers and have been associated with both function and treatment outcomes. However, the factors that contribute to altered synergies remain unclear. In particular, the extent to which synergies reflect altered biomechanics (e.g., changes in gait) or underlying neurologic injury is debated. To evaluate the effect that altered biomechanics have on synergies, we compared synergy complexity and structure while ND individuals (n = 14) emulated four common CP gait patterns (equinus, equinus-crouch, mild-crouch, and moderate crouch). Secondarily, we compared the similarity of ND synergies during emulation to synergies from a retrospective cohort of individuals with CP walking in similar gait patterns (n = 28 per pattern). During emulation, ND individuals recruited similar synergies as baseline walking. However, pattern-specific deviations in synergy activations and complexity emerged. In particular, equinus gait altered plantarflexor activation timing and reduced synergy complexity. Importantly, ND synergies during emulation were distinct from those observed in CP for all gait patterns. These results suggest that altered gait patterns are not primarily driving the changes in synergies observed in CP, highlighting the value of using synergies as a tool to capture patient-specific differences in motor control. However, they also highlight the sensitivity of both synergy activations and complexity to altered biomechanics, which should be considered when using these measures in clinical care.

What is an artificial muscle? A comparison of soft actuators to biological muscles

Interest in emulating the properties of biological muscles that allow for fast adaptability and control in unstructured environments has motivated researchers to develop new soft actuators, often referred to as 'artificial muscles'. The field of soft robotics is evolving rapidly as new soft actuator designs are published every year. In parallel, recent studies have also provided new insights for understanding biological muscles as 'active' materials whose tunable properties allow them to adapt rapidly to external perturbations. This work presents a comparative study of biological muscles and soft actuators, focusing on those properties that make biological muscles highly adaptable systems. In doing so, we briefly review the latest soft actuation technologies, their actuation mechanisms, and advantages and disadvantages from an operational perspective. Next, we review the latest advances in understanding biological muscles. This presents insight into muscle architecture, the actuation mechanism, and modeling, but more importantly, it provides an understanding of the properties that contribute to adaptability and control. Finally, we conduct a comparative study of biological muscles and soft actuators. Here, we present the accomplishments of each soft actuation technology, the remaining challenges, and future directions. Additionally, this comparative study contributes to providing further insight on soft robotic terms, such as biomimetic actuators, artificial muscles, and conceptualizing a higher level of performance actuator named artificial supermuscle. In conclusion, while soft actuators often have performance metrics such as specific power, efficiency, response time, and others similar to those in muscles, significant challenges remain when finding suitable substitutes for biological muscles, in terms of other factors such as control strategies, onboard energy integration, and thermoregulation.

Recording activity in proximal muscle networks with surface EMG in assessing infant motor development

OBJECTIVE

To develop methods for recording and analysing infant's proximal muscle activations.

METHODS

Surface electromyography (sEMG) of truncal muscles was recorded in three months old infants (N = 18) during spontaneous movement and controlled postural changes. The infants were also divided into two groups according to motor performance. We developed an efficient method for removing dynamic cardiac artefacts to allow i) accurate estimation of individual muscle activations, as well as ii) quantitative characterization of muscle networks.

RESULTS

The automated removal of cardiac artefacts allowed quantitation of truncal muscle activity, which showed predictable effects during postural changes, and there were differences between high and low performing infants.The muscle networks showed consistent change in network density during spontaneous movements between supine and prone position. Moreover, activity correlations in individual pairs of back muscles linked to infant́s motor performance.

CONCLUSIONS

The hereby developed sEMG analysis methodology is feasible and may disclose differences between high and low performing infants. Analysis of the muscle networks may provide novel insight to central control of motility.

SIGNIFICANCE

Quantitative analysis of infant's muscle activity and muscle networks holds promise for an objective neurodevelopmental assessment of motor system.

Modular reorganization of gait in chronic but not in artificial knee joint constraint

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.

Early Development of Locomotor Patterns and Motor Control in Very Young Children at High Risk of Cerebral Palsy, a Longitudinal Case Series

The first years of life might be critical for encouraging independent walking in children with cerebral palsy (CP). We sought to identify mechanisms that may underlie the impaired development of walking in three young children with early brain lesions, at high risk of CP, via comprehensive instrumented longitudinal assessments of locomotor patterns and muscle activation during walking. We followed three children (P1–P3) with early brain lesions, at high risk of CP, during five consecutive gait analysis sessions covering a period of 1 to 2 years, starting before the onset of independent walking, and including the session during the first independent steps. In the course of the study, P1 did not develop CP, P2 was diagnosed with unilateral and P3 with bilateral CP. We monitored the early development of locomotor patterns over time via spatiotemporal gait parameters, intersegmental coordination (estimated via principal component analysis), electromyography activity, and muscle synergies (determined from 11 bilateral muscles via nonnegative matrix factorization). P1 and P2 started to walk independently at the corrected age of 14 and 22 months, respectively. In both of them, spatiotemporal gait parameters, intersegmental coordination, muscle activation patterns, and muscle synergy structure changed from supported to independent walking, although to a lesser extent when unilateral CP was diagnosed (P2), especially for the most affected leg. The child with bilateral CP (P3) did not develop independent walking, and all the parameters did not change over time. Our exploratory longitudinal study revealed differences in maturation of locomotor patterns between children with divergent developmental trajectories. We succeeded in identifying mechanisms that may underlie impaired walking development in very young children at high risk of CP. When verified in larger sample sizes, our approach may be considered a means to improve prognosis and to pinpoint possible targets for early intervention.

Can spatial filtering separate voluntary and involuntary components in children with dyskinetic cerebral palsy?

The design of myocontrolled devices faces particular challenges in children with dyskinetic cerebral palsy because the electromyographic signal for control contains both voluntary and involuntary components. We hypothesized that voluntary and involuntary components of movements would be uncorrelated and thus detectable as different synergistic patterns of muscle activity, and that removal of the involuntary components would improve online EMG-based control. Therefore, we performed a synergy-based decomposition of EMG-guided movements, and evaluated which components were most controllable using a Fitts' Law task. Similarly, we also tested which muscles were most controllable. We then tested whether removing the uncontrollable components or muscles improved overall function in terms of movement time, success rate, and throughput. We found that removal of less controllable components or muscles did not improve EMG control performance, and in many cases worsened performance. These results suggest that abnormal movement in dyskinetic CP is consistent with a pervasive distortion of voluntary movement rather than a superposition of separable voluntary and involuntary components of movement.

Neuromuscular Control before and after Independent Walking Onset in Children with Cerebral Palsy

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.

Quantification of muscle coordination underlying basic shoulder movements using muscle synergy extraction

Numerous muscles around the shoulder joint are required to work in a coordinated manner, even when a basic shoulder movement is executed. Muscle synergy can be utilized as an index to determine muscle coordination. The purpose of the present study was to investigate the muscle coordination among different shoulder muscles underlying basic shoulder movements based on muscle synergy. Thirteen men performed 14 multiplanar shoulder movements; five movements were associated with elevation and lowering, while five were associated with horizontal abduction and adduction. The four additional movements were simple rotations at different positions. Muscle activity was measured from 12 muscle portions using surface electromyography. Using the dimensionality reduction technique, synergies were extracted first for each movement separately ("separate" synergies), and then for the global dataset (containing all movements; "global" synergies). The least number that provided 90% of the variance accounted for was selected as the optimal number of synergies. For each subject, approximately two separate synergies and approximately six global synergies with small residual values were extracted from the separate and global electromyography datasets, respectively. Specific patterns of these muscle synergies in each task were observed during each movement. In the cross-validation method, six global synergies explained 88.0 ± 1.3% of the global dataset. These findings indicate that muscle activities underlying basic shoulder movements are expressed as six units, and these units could be proxies for shoulder muscle coordination.

Clinical Relevance of State-of-the-Art Analysis of Surface Electromyography in Cerebral Palsy

Surface electromyography (sEMG) can be used to assess the integrity of the neuromuscular system and its impairment in neurological disorders. Here we will consider several issues related to the current clinical applications, difficulties and limited usage of sEMG for the assessment and rehabilitation of children with cerebral palsy. The uniqueness of this methodology is that it can determine hyperactivity or inactivity of selected muscles, which cannot be assessed by other methods. In addition, it can assist for intervention or muscle/tendon surgery acts, and it can evaluate integrated functioning of the nervous system based on multi-muscle sEMG recordings and assess motor pool activation. The latter aspect is especially important for understanding impairments of the mechanisms of neural controllers rather than malfunction of individual muscles. Although sEMG study is an important tool in both clinical research and neurorehabilitation, the results of a survey on the clinical relevance of sEMG in a typical department of pediatric rehabilitation highlighted its limited clinical usage. We believe that this is due to limited knowledge of the sEMG and its neuromuscular underpinnings by many physiotherapists, as a result of lack of emphasis on this important methodology in the courses taught in physical therapy schools. The lack of reference databases or benchmarking software for sEMG analysis may also contribute to the limited clinical usage. Despite the existence of educational and technical barriers to a widespread use of, sEMG does provide important tools for planning and assessment of rehabilitation treatments for children with cerebral palsy.

Accurate recognition of lower limb ambulation mode based on surface electromyography and motion data using machine learning

Background and Objective The lower limb activity of recognition of the elderly, the weak, the disabled and the sick is an irreplaceable role in the caring of daily life. The main purpose of this study is to assess the feasibility of using the surface electromyography (sEMG) signal and inertial measurement units (IMUs) data to determine the optimal fusion features and classifier for the study of daily ambulation mode recognition. Methods We have carried out several steps of experiments to obtain and test the optimal combination of the sEMG data and the body motion data at the feature level and the most suitable machine learning classification algorithm. Firstly, the sEMG and IMUs signals of eighteen participants performing four different ambulatory activities have recorded using wearable sensors. Secondly, several features of the sEMG sensors and IMU data were extracted and tested by the Markov Random Field based Fisher-Markov feature selector. Finally, four ML classifiers with several feature combinations were estimated with sensitivity, precision and recognition accurate rate of ambulatory activity classification. Results The results of this work showed that all selected features were significantly statistical difference in four ambulation modes. The principal component analysis was used to reduce the dimension of selected sEMG features and IMU features to form a fusion feature input support vector machine classifier, which could predict ambulatory activities with good classification performance. Conclusions It is concluded that the results demonstrate the feasibility of the ML classification model, which could provide a more novel way to guarantee the recognition rate and effectiveness of monitor daily ambulatory activity.

Maturation of the Locomotor Circuitry in Children With Cerebral Palsy

The first years of life represent an important phase of maturation of the central nervous system, processing of sensory information, posture control and acquisition of the locomotor function. Cerebral palsy (CP) is the most common group of motor disorders in childhood attributed to disturbances in the fetal or infant brain, frequently resulting in impaired gait. Here we will consider various findings about functional maturation of the locomotor output in early infancy, and how much the dysfunction of gait in children with CP can be related to spinal neuronal networks vs. supraspinal dysfunction. A better knowledge about pattern generation circuitries in infancy may improve our understanding of developmental motor disorders, highlighting the necessity for regulating the functional properties of abnormally developed neuronal locomotor networks as a target for early sensorimotor rehabilitation. Various clinical approaches and advances in biotechnology are also considered that might promote acquisition of the locomotor function in infants at risk for locomotor delays.

Quantitative Assessment of Traumatic Upper-Limb Peripheral Nerve Injuries Using Surface Electromyography

Background

There is a great demand for convenient and quantitative assessment of upper-limb traumatic peripheral nerve injuries (PNIs) beyond their clinical routine. This would contribute to improved PNI management and rehabilitation.

Objective

The aim of this study was to develop a novel surface EMG examination method for quantitatively evaluating traumatic upper-limb PNIs.

Methods

Experiments were conducted to collect surface EMG data from forearm muscles on both sides of seven male subjects during their performance of eight designated hand and wrist motion tasks. All participants were clinically diagnosed as unilateral traumatic upper-limb PNIs on the ulnar nerve, median nerve, or radial nerve. Ten healthy control participants were also enrolled in the study. A novel framework consisting of two modules was also proposed for data analysis. One module was first used to identify whether a PNI occurs on a tested forearm using a machine learning algorithm by extracting and classifying features from surface EMG data. The second module was then used to quantitatively evaluate the degree of injury on three individual nerves on the examined arm.

Results

The evaluation scores yielded by the proposed method were highly consistent with the clinical assessment decisions for three nerves of all 34 examined arms (7 × 2 + 10 × 2), with a sensitivity of 81.82%, specificity of 98.90%, and significate linear correlation (p < 0.05) in quantitative decision points between the proposed method and the routine clinical approach.

Conclusion

This study offers a useful tool for PNI assessment and helps to promote extensive clinical applications of surface EMG.

Locomotor patterns during obstacle avoidance in children with cerebral palsy

Previous studies mainly evaluated the neuromuscular pattern generation in cerebral palsy (CP) during unobstructed gait. Here we characterized impairments in the obstacle task performance associated with a limited adaptation of the task-relevant muscle module timed to the foot lift during obstacle crossing. Impaired task performance in children with CP may reflect basic developmental deficits in the adaptable control of gait when the locomotor task is superimposed with the voluntary movement.

Older adults reduce the complexity and efficiency of neuromuscular control to preserve walking balance

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.

Muscle Synergies During Walking in Children With Cerebral Palsy: A Systematic Review

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.

Muscle Synergy and Musculoskeletal Model-Based Continuous Multi-Dimensional Estimation of Wrist and Hand Motions

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.

Muscle Synergy Constraints Do Not Improve Estimates of Muscle Activity From Static Optimization During Gait for Unimpaired Children or Children With Cerebral Palsy

Neuromusculoskeletal simulation provides a promising platform to inform the design of assistive devices or inform rehabilitation. For these applications, a simulation must be able to accurately represent the person of interest, such as an individual with a neurologic injury. If a simulation fails to predict how an individual recruits and coordinates their muscles during movement, it will have limited utility for informing design or rehabilitation. While inverse dynamic simulations have previously been used to evaluate anticipated responses from interventions, like orthopedic surgery or orthoses, they frequently struggle to accurately estimate muscle activations, even for tasks like walking. The simulated muscle activity often fails to represent experimentally measured muscle activity from electromyographic (EMG) recordings. Research has theorized that the nervous system may simplify the range of possible activations used during dynamic tasks, by constraining activations to weighted groups of muscles, referred to as muscle synergies. Synergies are altered after neurological injury, such as stroke or cerebral palsy (CP), and may provide a method for improving subject-specific models of neuromuscular control. The aim of this study was to test whether constraining simulation to synergies could improve estimated muscle activations compared to EMG data. We evaluated modeled muscle activations during gait for six typically developing (TD) children and six children with CP. Muscle activations were estimated with: (1) static optimization (SO), minimizing muscle activations squared, and (2) synergy SO (SynSO), minimizing synergy activations squared using the weights identified from EMG data for two to five synergies. While SynSO caused changes in estimated activations compared to SO, the correlation to EMG data was not higher in SynSO than SO for either TD or CP groups. The correlations to EMG were higher in CP than TD for both SO (CP: 0.48, TD: 0.36) and SynSO (CP: 0.46, TD: 0.26 for five synergies). Constraining activations to SynSO caused the simulated muscle stress to increase compared to SO for all individuals, causing a 157% increase with two synergies. These results suggest that constraining simulated activations in inverse dynamic simulations to subject-specific synergies alone may not improve estimation of muscle activations during gait for generic musculoskeletal models.

Modularity underlying the performance of unusual locomotor tasks inspired by developmental milestones

Motor behaviors are often hypothesized to be set up from the combination of a small number of modules encoded in the central nervous system. These modules are thought to combine such that a variety of motor tasks can be realized, from reproducible tasks such as walking to more unusual locomotor tasks that typically exhibit more step-by-step variability. We investigated the impact of step-by-step variability on the modular architecture of unusual tasks compared with walking. To this aim, 20 adults had to perform walking and two unusual modes of locomotion inspired by developmental milestones (cruising and crawling). Sixteen surface electromyography (EMG) signals were recorded to extract both spatial and temporal modules. Modules were extracted from both averaged and nonaveraged (i.e., single step) EMG signals to assess the significance of step-to-step variability when participants practiced such unusual locomotor tasks. The number of modules extracted from averaged data was similar across tasks, but a higher number of modules was required to reconstruct nonaveraged EMG data of the unusual tasks. Although certain walking modules were shared with cruising and crawling, task-specific modules were necessary to account for the muscle patterns underlying these unusual locomotion modes. These results highlight a more complex modularity (e.g., more modules) for cruising and crawling compared with walking, which was only apparent when the step-to-step variability of EMG patterns was considered. This suggests that considering nonaveraged data is relevant when muscle modularity is studied, especially in motor tasks with high variability as in motor development.NEW & NOTEWORTHY This study addresses the general question of modularity in locomotor control. We demonstrate for the first time the importance of intraindividual variability in the muscle modularity of unusual locomotor behaviors that exhibit greater step-by-step variability than standard walking. Crawling and cruising, the unusual locomotor modes considered, are based on a more complex modular organization than walking. More spatial and temporal modules, task specific or shared with walking modules, are needed to reconstruct muscle patterns.

Quantitative assessment of lower limbs gross motor function in children with cerebral palsy based on surface EMG and inertial sensors

Taking advantage of motion sensing technology, a quantitative assessment method for lower limbs motor function of cerebral palsy (CP) based on the gross motor function measurement (GMFM)-24 scale was explored in this study. According to the motion analysis on GMFM-24 scale, we translated the assessment problem of GMFM-24 scale into a detection problem of different motion modes including static state, fall, step, turning, alternating gait, walking, running, lifting legs, kicking balls, and jumping. The surface electromyography (sEMG) electrodes and inertial sensors were adopted to capture motion data, and a framework integrating a series of detection algorithms was presented for the assessment of lower limbs gross motor function. Two groups of participants including 8 healthy adults and 14 CP children were recruited. A self-developed data acquisition equipment integrating 24 sEMG electrodes and 9 inertial units was adopted for data acquisition. A platform based on two laser beam sensors was used to perform cross-border detection. The parameters/thresholds of motion detection algorithms were determined by the data from healthy adults, and the lower limbs gross motor function evaluation was conducted on 14 CP children. The experimental results verified the feasibility and effectiveness of the proposed quantitative assessment method. Compared to the clinical assessment score based on GMFM-24 scale, 90.1% accuracy was obtained for evaluation of 303 tasks in 14 CP children. The objective motor function assessment method proposed has potential application value for the quantitative assessment of lower limbs motor function of CP children in clinical practice. Graphical abstract The algorithm framework for the assessment of lower limbs gross motor function. Using the GMFM-24 scale as the evaluation standard, a quantitative evaluation program for the lower limbs gross motor function of CP children based on motion sensing technology was proposed.

Muscle Synergies in Response to Biofeedback-Driven Gait Adaptations in Children With Cerebral Palsy

Background

Children with cerebral palsy (CP) often show impaired selective motor control (SMC) that induces limitations in motor function. Children with CP can improve aspects of pathological gait in an immediate response to visual biofeedback. It is not known, however, how these gait adaptations are achieved at the neural level, nor do we know the extent of SMC plasticity in CP.

Aim

Investigate the underlying SMC and changes that may occur when gait is adapted with biofeedback.

Methods

Twenty-three ambulatory children with CP and related (hereditary) forms of spastic paresis (Aged: 10.4 ± 3.1, 6–16 years, M: 16/F: 9) were challenged with real-time biofeedback to improve step length, knee extension, and ankle power while walking on an instrumented treadmill in a virtual reality environment. The electromyograms of eight superficial muscles of the leg were analyzed and synergies were further decomposed using non-negative matrix factorization (NNMF) using 1 to 5 synergies, to quantify SMC. Total variance accounted for (tVAF) was used as a measure of synergy complexity. An imposed four synergy solution was investigated further to compare similarity in weightings and timing patterns of matched paired synergies between baseline and biofeedback trials.

Results

Despite changes in walking pattern, changes in synergies were limited. The number of synergies required to explain at least 90% of muscle activation increased significantly, however, the change in measures of tVAF₁ from baseline (0.75 ± 0.08) were less than ±2% between trials. In addition, within-subject similarity of synergies to baseline walking was high (>0.8) across all biofeedback trials.

Conclusion

These results suggest that while gait may be adapted in an immediate response, SMC as quantified by synergy analysis is perhaps more rigidly impaired in CP. Subtle changes in synergies were identified; however, it is questionable if these are clinically meaningful at the level of an individual. Adaptations may be limited in the short term, and further investigation is essential to establish if long term training using biofeedback leads to adapted SMC.

Comparison of muscle synergies extracted from both legs during cycling at different mechanical conditions

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.

Gait synergetic neuromuscular control in children with cerebral palsy at different gross motor function classification system levels

Cerebral palsy (CP) is a neural developmental disease featured with gait abnormalities. CP gait assessment is usually performed with the Gross Motor Function Classification System (GMFCS) in clinics, which does not involve a thorough assessment of neuromuscular control. To understand how the neuromuscular control disorders lead to gait abnormalities, we explored the relationship between GMFCS levels and the gait synergetic control characteristics in this study. In total, 18 children with CP at different GMFCS levels (mean age: 4.41±1.30 yr) and 8 age-matched typically developing (TD) children (mean age: 4.43±1.36 yr) were recruited to perform a straight walking task, and the surface electromyographic (sEMG) signals from eight lower limb muscles on each side and accelerometer data were collected. A nonnegative matrix factorization method was applied to obtain the muscle synergies from the sEMG signals. Next, synergy structures were projected onto the basic gait synergies to test the completeness of those structures. Subsequently, synergy activation parameters, including total activation duration and coactivation index, were compared across the participants. This study showed that children with CP at GMFCS levels I and II and the TD children had similar synergy structures, but the synergy activations of these children with CP were different from those of TD children. In addition, similar to previous research, we also found that children with CP at GMFCS level III could not access all four basic synergies on both sides. Based on the synergy analysis results, a gait assessment paradigm was proposed to facilitate the clinical CP gait evaluation.

NEW & NOTEWORTHY Understanding the mechanism of gait abnormality has important clinical significance for the diagnosis, prognosis, and possible treatment of motor dysfunction in children with cerebral palsy (CP). In this study, the comparisons of the lower limb muscle synergies among different groups of children with CP at different Gross Motor Function Classification System levels might provide some new insight into the mechanism underlying the gait disorder. In particular, the discrepancies of gait synergy structure and activation patterns across the study groups may indicate different neurophysiological and pathological attributes in different groups of patients.

On the Relationship Between Muscle Synergies and Redundant Degrees of Freedom in Musculoskeletal Systems

It has been suggested that the human nervous system controls motions in the task (or operational) space. However, little attention has been given to the separation of the control of the task-related and task-irrelevant degrees of freedom. Aim: We investigate how muscle synergies may be used to separately control the task-related and redundant degrees of freedom in a computational model. Approach: We generalize an existing motor control model, and assume that the task and redundant spaces have orthogonal basis vectors. This assumption originates from observations that the human nervous system tightly controls the task-related variables, and leaves the rest uncontrolled. In other words, controlling the variables in one space does not affect the other space; thus, the actuations must be orthogonal in the two spaces. We implemented this assumption in the model by selecting muscle synergies that produce force vectors with orthogonal directions in the task and redundant spaces. Findings: Our experimental results show that the orthogonality assumption performs well in reconstructing the muscle activities from the measured kinematics/dynamics in the task and redundant spaces. Specifically, we found that approximately 70% of the variation in the measured muscle activity can be captured with the orthogonality assumption, while allowing efficient separation of the control in the two spaces. Implications: The developed motor control model is a viable tool in real-time simulations of musculoskeletal systems, as well as model-based control of bio-mechatronic systems, where a computationally efficient representation of the human motion controller is needed.

Muscle synergies demonstrate only minimal changes after treatment in cerebral palsy

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.

Children With Cerebral Palsy Have Greater Stride-to-Stride Variability of Muscle Synergies During Gait Than Typically Developing Children: Implications for Motor Control Complexity

BACKGROUND

There is mounting evidence that the central nervous system utilizes a modular approach for neuromuscular control of walking by activating groups of muscles in units termed muscle synergies. Examination of muscle synergies in clinical populations may provide insights into alteration of neuromuscular control underlying pathological gait patterns. Previous studies utilizing synergy analysis have reported reduced motor control complexity during walking in those with neurological deficits, revealing the potential clinical utility of this approach.

METHODS

We extracted muscle synergies on a stride-to-stride basis from 20 children with cerebral palsy (CP; Gross Motor Function Classification System levels I-II) and 8 children without CP, allowing the number of synergies to vary for each stride. Similar muscle synergies across all participants and strides were grouped using a k-means clustering and discriminant analysis.

RESULTS

In total, 10 clusters representing 10 distinct synergies were found across the 28 individuals. Relative to their total number of synergies deployed during walking, synergies from children with CP were present in a higher number of clusters than in children with typical development (TD), indicating significantly greater stride-to-stride variability. This increased variability was present despite reduced complexity, as measured by the mean number of synergies in each stride. Whereas children with CP demonstrate some novel synergies, they also deploy some of the same muscle synergies as those with TD, although less frequently and with more variability.

CONCLUSION

A stride-by-stride approach to muscle synergy analysis expands its clinical utility and may provide a method to tailor rehabilitation strategies by revealing inconsistent but functional synergies in each child with CP.

Synergistic Myoelectrical Activities of Forearm Muscles Improving Robust Recognition of Multi-Fingered Gestures

Currently, surface electromyography (sEMG) features of the forearm multi-tendon muscles are widely used in gesture recognition, however, there are few investigations on the inherent physiological mechanism of muscle synergies. We aimed to study whether the muscle synergies could be used for gesture recognition. Five healthy participants executed five gestures of daily life (pinch, fist, open hand, grip, and extension) and the sEMG activity was acquired from six forearm muscles. A non-negative matrix factorization (NMF) algorithm was employed to decompose the pre-treated six-channel sEMG data to obtain the muscle synergy matrixes, in which the weights of each muscle channel determined the feature set for hand gesture classification. The results showed that the synergistic features of forearm muscles could be successfully clustered in the feature space, which enabled hand gestures to be recognized with high efficiency. By augmenting the number of participants, the mean recognition rate remained at more than 96% and reflected high robustness. We showed that muscle synergies can be well applied to gesture recognition.

Repeatability of electromyography recordings and muscle synergies during gait among children with cerebral palsy

BACKGROUND

Clinical gait analysis is commonly used in the evaluation and treatment of children with cerebral palsy (CP). While the repeatability of kinematic and kinetic measures of gait has previously been evaluated, the repeatability of electromyography (EMG) recordings or measures calculated from EMG data, such as muscle synergies, remains unclear for this population.

RESEARCH QUESTION

Are EMG recordings and muscle synergies from clinical gait analysis repeatable between visits for children with CP?

METHODS

We recruited 20 children with bilateral CP who had been referred for clinical gait analysis. The children completed two visits less than six weeks apart with EMG data collected bilaterally from five muscles (rectus femoris, medial hamstrings, vastus lateralis, anterior tibialis, and medial gastrocnemius). Variance ratio and cosine similarity were used to evaluate repeatability of EMG waveforms between visits. Nonnegative matrix factorization was used to calculate synergies from EMG data at each visit to compare synergy weights and activations.

RESULTS & SIGNIFICANCE

The inter-visit variance ratios of EMG data for children with CP were similar to previously reported results for typically-developing children and unimpaired adults (range: 0.39 for vastus lateralis to 0.66 for rectus femoris). The average cosine similarity of the EMG waveforms between visits was greater than 0.9 for all muscles, while synergy weights and activations also had high similarity - greater than 0.8 and 0.9 between visits, respectively. These results demonstrate that EMG repeatability between visits during clinical gait analysis for children with CP is similar to unimpaired individuals. These results provide a baseline for evaluating whether observed changes in EMG recordings between visits reflect real changes in muscle activity or are within the range of inter-visit variability.

Associations Between Muscle Synergies and Treatment Outcomes in Cerebral Palsy Are Robust Across Clinical Centers

OBJECTIVE

To determine whether patient-specific differences in motor control quantified using muscle synergy analysis were associated with changes in gait after treatment of cerebral palsy (CP) across 2 clinical centers with different treatments and clinical protocols.

DESIGN

Retrospective cohort study.

SETTING

Clinical medical center.

PARTICIPANTS

Center 1: children with CP (n=473) and typically developing (TD) children (n=84). Center 2: children with CP (n=163) and TD children (n=12).

INTERVENTIONS

Standard clinical care at each center.

MAIN OUTCOME MEASURES

The Dynamic Motor Control Index During Walking (walk-DMC) was computed from electromyographic data during gait using muscle synergy analysis. Regression analysis was used to evaluate whether pretreatment walking speed or kinematics, muscle synergies, treatment group, prior treatment, or age were associated with posttreatment changes in gait at both clinical centers.

RESULTS

Walk-DMC was significantly associated with changes in speed and kinematics after treatment with similar regression models at both centers. Children with less impaired motor control were more likely to have improvements in walking speed and gait kinematics after treatment, independent of treatment group.

CONCLUSIONS

Dynamic motor control evaluated with synergy analysis was associated with changes in gait after treatment at both centers, despite differences in treatments and clinical protocols. This study further supports the finding that walk-DMC provides additional information, not captured in traditional gait analysis, that may be useful for treatment planning.

Modular Control of Human Movement During Running: An Open Access Data Set

The human body is an outstandingly complex machine including around 1000 muscles and joints acting synergistically. Yet, the coordination of the enormous amount of degrees of freedom needed for movement is mastered by our one brain and spinal cord. The idea that some synergistic neural components of movement exist was already suggested at the beginning of the 20th century. Since then, it has been widely accepted that the central nervous system might simplify the production of movement by avoiding the control of each muscle individually. Instead, it might be controlling muscles in common patterns that have been called muscle synergies. Only with the advent of modern computational methods and hardware it has been possible to numerically extract synergies from electromyography (EMG) signals. However, typical experimental setups do not include a big number of individuals, with common sample sizes of 5 to 20 participants. With this study, we make publicly available a set of EMG activities recorded during treadmill running from the right lower limb of 135 healthy and young adults (78 males and 57 females). Moreover, we include in this open access data set the code used to extract synergies from EMG data using non-negative matrix factorization (NMF) and the relative outcomes. Muscle synergies, containing the time-invariant muscle weightings (motor modules) and the time-dependent activation coefficients (motor primitives), were extracted from 13 ipsilateral EMG activities using NMF. Four synergies were enough to describe as many gait cycle phases during running: weight acceptance, propulsion, early swing, and late swing. We foresee many possible applications of our data that we can summarize in three key points. First, it can be a prime source for broadening the representation of human motor control due to the big sample size. Second, it could serve as a benchmark for scientists from multiple disciplines such as musculoskeletal modeling, robotics, clinical neuroscience, sport science, etc. Third, the data set could be used both to train students or to support established scientists in the perfection of current muscle synergies extraction methods. All the data is available at Zenodo (doi: 10.5281/zenodo.1254380).

The Effects of Selective Muscle Weakness on Muscle Coordination in the Human Arm

Despite the fundamental importance of muscle coordination in daily life, it is currently unclear how muscle coordination adapts when the musculoskeletal system is perturbed. In this study, we quantified the impact of selective muscle weakness on several metrics of muscle coordination. Seven healthy subjects performed 2D and 3D isometric force target matches, while electromyographic (EMG) signals were recorded from 13 elbow and shoulder muscles. Subsequently, muscle weakness was induced by a motor point block of brachialis muscle. Postblock subjects repeated the force generation tasks. We quantified muscle coordination pre- and postblock using three metrics: tuning curve preferred direction, tuning curve area, and motor modules analysis via nonnegative matrix factorization. For most muscles, the tuning direction for the 2D protocol was not substantially altered postblock, while tuning areas changed more drastically. Typically, five motor modules were identified from the 3D task, and four motor modules were identified in the 2D task; this result held across both pre- and postblock conditions. The composition of one or two motor modules, ones that involved mainly the activation of shoulder muscles, was altered postblock. Our results demonstrate that selective muscle weakness can induce nonintuitive alternations in muscle coordination in the mechanically redundant human arm.

Degraded Synergistic Recruitment of sEMG Oscillations for Cerebral Palsy Infants Crawling

Background: Synergistic recruitment of muscular activities is a generally accepted mechanism for motor function control, and motor dysfunction, such as cerebral palsy (CP), destroyed the synergistic electromyography activities of muscle group for limb movement. However, very little is known how motor dysfunction of CP affects the organization of the myoelectric frequency components due to the abnormal motor unit recruiting patterns. Objectives: Exploring whether the myoelectric activity can be represented with synergistic recruitment of surface electromyography (sEMG) frequency components; evaluating the effect of CP motor dysfunction on the synergistic recruitment of sEMG oscillations. Methods: Twelve CP infants and 17 typically developed (TD) infants are recruited for self-paced crawling on hands and knees. sEMG signals have been recorded from bilateral biceps brachii (BB) and triceps brachii (TB) muscles. Multi-scale oscillations are extracted via multivariate empirical mode decomposition (MEMD), and non-negative matrix factorization (NMF) method is employed to obtain synergistic pattern of these sEMG oscillations. The coefficient curve of sEMG oscillation synergies are adopted to quantify the time-varying recruitment of BB and TB myoelectric activity during infants crawling. Results: Three patterns of sEMG oscillation synergies with specific frequency ranges are extracted in BB and TB of CP or TD infants. The contribution of low-frequency oscillation synergy of BB in CP group is significantly less than that in TD group (p < 0.05) during forward swing phase for slow contraction; however, this low-frequency oscillation synergy keep higher level during the backward swing phase crawling. For the myoelectric activities of TB, there is not enough high-frequency oscillation recruitment of sEMG for the fast contraction in propulsive phase of CP infants crawling. Conclusion: Our results reveal that, the myoelectric activities of a muscle can be manifested as sEMG oscillation synergies, and motor dysfunction of CP degrade the synergistic recruitment of sEMG oscillations due to the impaired CNS regulation and destroyed MU/muscle fiber. Our preliminary work suggests that time-varying coefficient curve of sEMG oscillation synergies is a potential index to evaluate the abnormal recruitment of electromyography activities affected by CP disorders.

The motor repertoire of older adult fallers may constrain their response to balance perturbations

Older adults are at a high risk of falls, and most falls occur during locomotor activities like walking. This study aimed to improve our understanding of changes in neuromuscular control associated with increased risk of falls in older adults in the presence of dynamic balance challenges during walking. Motor module (also known as muscle synergy) analyses identified changes in the neuromuscular recruitment of leg muscles during walking with and without perturbations designed to elicit the visual perception of lateral instability. During normal walking we found that a history of falls (but not age) was associated with reduced motor module complexity and that age (but not a history of falls) was associated with increased step-to-step variability of module recruitment timing. Furthermore, motor module complexity was unaltered in the presence of optical flow perturbations. The specific effects of a history of falls on leg muscle recruitment included an absence and/or inability to independently recruit motor modules normally recruited to perform biomechanical functions important for walking balance control. These results suggest that fallers do not recruit the appropriate motor modules necessary for well-coordinated walking balance control even in the presence of perturbations. The identified changes in the modular control of walking balance in older fallers may either represent a neural deficit that leads to poor balance control or a prior history of falls that results in a compensatory motor adaptation. In either case, our study provides initial evidence that a reduced motor repertoire in older adult fallers may be a constraint on their ability to appropriately respond to balance challenges during walking. NEW & NOTEWORTHY This is the first study to demonstrate a reduced motor repertoire during walking in older adults with a history of falls but without any overt neurological deficits. Furthermore, using virtual reality during walking to elicit the visual perception of lateral instability, we provide initial evidence that a reduced motor repertoire in older adult fallers may be a constraint on their ability to appropriately respond to balance challenges during walking.

Estimation of Time-Varying Coherence Amongst Synergistic Muscles During Wrist Movements

The central nervous system (CNS) controls the limb movement by modulating multiple skeletal muscles with synergistic modules and neural oscillations with different frequencies between the activated muscles. Several researchers have found intermuscular coherence existing within the synergistic muscle pairs, and pointed out that the intermuscular synchronization existed when functional forces were generated. However, few studies involved the time-varying characteristics of the intermuscular coherence in each synergy module though all activated muscles keep in a dynamic and varying process. Therefore, this study aims to explore the time-varying coherence amongst synergistic muscles during movements based on the combination of the non-negative matrix factorization (NMF) method and the time-frequency coherence (TFC) method. We applied these methods into the electromyogram (EMG) signals recorded from eight muscles involved in the sequence of the wrist movements [wrist flexion (WF), wrist flexion transmission to wrist extension (MC) and wrist extension (WE)] in 12 healthy people. The results showed three synergistic flexor pairs (FCR-PL, FCR-FDS, and PL-FDS) in the WF stage and three extensor pairs (ECU-ECR, ECU-B, and ECR-B) in both MC and WE stages. Further analysis showed intermuscular coherence between each pairwise synergistic muscles. The intermuscular coherence between the flexor muscle pairs was mainly observed in the beta band (15-35 Hz) during the WF stage, and that amongst the extensor muscle pairs was also observed in the beta band during the WE stage. However, the intermuscular coherence between the extensor muscle pairs mainly on gamma band during the MC stage. Additionally, compared to the flexor muscle pairs, the intermuscular coherence of the extensor muscle pairs were lower in the WF stage, and higher in both MC and WE stages. These results demonstrated the time-varying mechanisms of the synergistic modulation and synchronous oscillation in motor-control system. This study contributes to expanded researches for motor control.

An isometric muscle force estimation framework based on a high-density surface EMG array and an NMF algorithm

OBJECTIVE

To realize accurate muscle force estimation, a novel framework is proposed in this paper which can extract the input of the prediction model from the appropriate activation area of the skeletal muscle.

APPROACH

Surface electromyographic (sEMG) signals from the biceps brachii muscle during isometric elbow flexion were collected with a high-density (HD) electrode grid (128 channels) and the external force at three contraction levels was measured at the wrist synchronously. The sEMG envelope matrix was factorized into a matrix of basis vectors with each column representing an activation pattern and a matrix of time-varying coefficients by a nonnegative matrix factorization (NMF) algorithm. The activation pattern with the highest activation intensity, which was defined as the sum of the absolute values of the time-varying coefficient curve, was considered as the major activation pattern, and its channels with high weighting factors were selected to extract the input activation signal of a force estimation model based on the polynomial fitting technique.

MAIN RESULTS

Compared with conventional methods using the whole channels of the grid, the proposed method could significantly improve the quality of force estimation and reduce the electrode number.

SIGNIFICANCE

The proposed method provides a way to find proper electrode placement for force estimation, which can be further employed in muscle heterogeneity analysis, myoelectric prostheses and the control of exoskeleton devices.

A Systematic Review on Muscle Synergies: From Building Blocks of Motor Behavior to a Neurorehabilitation Tool

The central nervous system (CNS) is believed to utilize specific predefined modules, called muscle synergies (MS), to accomplish a motor task. Yet questions persist about how the CNS combines these primitives in different ways to suit the task conditions. The MS hypothesis has been a subject of debate as to whether they originate from neural origins or nonneural constraints. In this review article, we present three aspects related to the MS hypothesis: (1) the experimental and computational evidence in support of the existence of MS, (2) algorithmic approaches for extracting them from surface electromyography (EMG) signals, and (3) the possible role of MS as a neurorehabilitation tool. We note that recent advances in computational neuroscience have utilized the MS hypothesis in motor control and learning. Prospective advances in clinical, medical, and engineering sciences and in fields such as robotics and rehabilitation stand to benefit from a more thorough understanding of MS.