Coordination of locomotion with voluntary movements in humans

Stepping up after spinal cord injury: negotiating an obstacle during walking

Every day walking consists of frequent voluntary modifications in the gait pattern to negotiate obstacles. After spinal cord injury, stepping over an obstacle becomes challenging. Stepping over an obstacle requires sensorimotor transformations in several structures of the brain, including the parietal cortex, premotor cortex, and motor cortex. Sensory information and planning are transformed into motor commands, which are sent from the motor cortex to spinal neuronal circuits to alter limb trajectory, coordinate the limbs, and maintain balance. After spinal cord injury, bidirectional communication between the brain and spinal cord is disrupted and animals, including humans, fail to voluntarily modify limb trajectory to step over an obstacle. Therefore, in this review, we discuss the neuromechanical control of stepping over an obstacle, why it fails after spinal cord injury, and how it recovers to a certain extent.

Transforming the Anthropomorphic Passive Free-Flow Foot Prosthesis Into a Powered Foot Prosthesis With Intuitive Control and Sensation (Bionic FFF)

INTRODUCTION

Approximately 89% of all service members with amputations do not return to duty. Restoring intuitive neural control with somatosensory sensation is a key to improving the safety and efficacy of prosthetic locomotion. However, natural somatosensory feedback from lower-limb prostheses has not yet been incorporated into any commercial prostheses.

MATERIALS AND METHODS

We developed a neuroprosthesis with intuitive bidirectional control and somatosensation and evoking phase-dependent locomotor reflexes, we aspire to significantly improve the prosthetic rehabilitation and long-term functional outcomes of U.S. amputees. We implanted the skin and bone integrated pylon with peripheral neural interface pylon into the cat distal tibia, electromyographic electrodes into the residual gastrocnemius muscle, and nerve cuff electrodes on the distal tibial and sciatic nerves. Results. The bidirectional neural interface that was developed was integrated into the existing passive Free-Flow Foot and Ankle prosthesis, WillowWood, Mount Sterling, OH. The Free-Flow Foot was chosen because it had the highest Index of Anthropomorphicity among lower-limb prostheses and was the first anthropomorphic prosthesis brought to market. Conclusion. The cats walked on a treadmill with no cutaneous feedback from the foot in the control condition and with their residual distal tibial nerve stimulated during the stance phase of walking.

Associations Between Music and Dance Relationships, Rhythmic Proficiency, and Spatiotemporal Movement Modulation Ability in Adults with and without Mild Cognitive Impairment

Background

Personalized dance-based movement therapies may improve cognitive and motor function in individuals with mild cognitive impairment (MCI), a precursor to Alzheimer's disease. While age- and MCI-related deficits reduce individuals' abilities to perform dance-like rhythmic movement sequences (RMS)-spatial and temporal modifications to movement-it remains unclear how individuals' relationships to dance and music affect their ability to perform RMS.

Objective

Characterize associations between RMS performance and music or dance relationships, as well as the ability to perceive rhythm and meter (rhythmic proficiency) in adults with and without MCI.

Methods

We used wearable inertial sensors to evaluate the ability of 12 young adults (YA; age = 23.9±4.2 years; 9F), 26 older adults without MCI (OA; age = 68.1±8.5 years; 16F), and 18 adults with MCI (MCI; age = 70.8±6.2 years; 10F) to accurately perform spatial, temporal, and spatiotemporal RMS. To quantify self-reported music and dance relationships and rhythmic proficiency, we developed Music (MRQ) and Dance Relationship Questionnaires (DRQ), and a rhythm assessment (RA), respectively. We correlated MRQ, DRQ, and RA scores against RMS performance for each group separately.

Results

The OA and YA groups exhibited better MRQ and RA scores than the MCI group (p < 0.006). Better MRQ and RA scores were associated with better temporal RMS performance for only the YA and OA groups (r2 = 0.18-0.41; p < 0.045). DRQ scores were not associated with RMS performance in any group.

Conclusions

Cognitive deficits in adults with MCI likely limit the extent to which music relationships or rhythmic proficiency improve the ability to perform temporal aspects of movements performed during dance-based therapies.

Transferring Sensor-Based Assessments to Clinical Practice: The Case of Muscle Synergies

Sensor-based assessments in medical practice and rehabilitation include the measurement of physiological signals such as EEG, EMG, ECG, heart rate, and NIRS, and the recording of movement kinematics and interaction forces. Such measurements are commonly employed in clinics with the aim of assessing patients' pathologies, but so far some of them have found full exploitation mainly for research purposes. In fact, even though the data they allow to gather may shed light on physiopathology and mechanisms underlying motor recovery in rehabilitation, their practical use in the clinical environment is mainly devoted to research studies, with a very reduced impact on clinical practice. This is especially the case for muscle synergies, a well-known method for the evaluation of motor control in neuroscience based on multichannel EMG recordings. In this paper, considering neuromotor rehabilitation as one of the most important scenarios for exploiting novel methods to assess motor control, the main challenges and future perspectives for the standard clinical adoption of muscle synergy analysis are reported and critically discussed.

Associations between music and dance relationships, rhythmic proficiency, and spatiotemporal movement modulation ability in adults with and without mild cognitive impairment

Background

Personalized dance-based movement therapies may improve cognitive and motor function in individuals with mild cognitive impairment (MCI), a precursor to Alzheimer's disease. While age- and MCI-related deficits reduce individuals' abilities to perform dance-like rhythmic movement sequences (RMS)-spatial and temporal modifications to movement-it remains unclear how individuals' relationships to dance and music affect their ability to perform RMS.

Objective

Characterize associations between RMS performance and music or dance relationships, as well as the ability to perceive rhythm and meter (rhythmic proficiency) in adults with and without MCI.

Methods

We used wearable inertial sensors to evaluate the ability of 12 young adults (YA; age=23.9±4.2 yrs; 9F), 26 older adults without MCI (OA; age=68.1±8.5 yrs; 16F), and 18 adults with MCI (MCI; age=70.8±6.2 yrs; 10F) to accurately perform spatial, temporal, and spatiotemporal RMS. To quantify self-reported music and dance relationships and rhythmic proficiency, we developed Music (MRQ) and Dance Relationship Questionnaires (DRQ), and a rhythm assessment (RA), respectively. We correlated MRQ, DRQ, and RA scores against RMS performance for each group separately.

Results

The OA and YA groups exhibited better MRQ and RA scores than the MCI group (p<0.006). Better MRQ and RA scores were associated with better temporal RMS performance for only the YA and OA groups (r2=0.18-0.41; p<0.045). DRQ scores were not associated with RMS performance in any group.

Conclusions

Cognitive deficits in adults with MCI likely limit the extent to which music relationships or rhythmic proficiency improve the ability to perform temporal aspects of movements performed during dance-based therapies.

Role of the Cerebellum in the Construction of Functional and Geometrical Spaces

The perceptual and motor systems appear to have a set of movement primitives that exhibit certain geometric and kinematic invariances. Complex patterns and mental representations can be produced by (re)combining some simple motor elements in various ways using basic operations, transformations, and respecting a set of laws referred to as kinematic laws of motion. For example, point-to-point hand movements are characterized by straight hand paths with single-peaked-bell-shaped velocity profiles, whereas hand speed profiles for curved trajectories are often irregular and more variable, with speed valleys and inflections extrema occurring at the peak curvature. Curvature and speed are generically related by the 2/3 power law. Mathematically, such laws can be deduced from a combination of Euclidean, affine, and equi-affine geometries, whose neural correlates have been partially detected in various brain areas including the cerebellum and the basal ganglia. The cerebellum has been found to play an important role in the control of coordination, balance, posture, and timing over the past years. It is also assumed that the cerebellum computes forward internal models in relationship with specific cortical and subcortical brain regions but its motor relationship with the perceptual space is unclear. A renewed interest in the geometrical and spatial role of the cerebellum may enable a better understanding of its specific contribution to the action-perception loop and behavior's adaptation. In this sense, we complete this overview with an innovative theoretical framework that describes a possible implementation and selection by the cerebellum of geometries adhering to different mathematical laws.

Influence of Backpack Carriage and Walking Speed on Muscle Synergies in Healthy Children

Four to five muscle synergies account for children's locomotion and appear to be consistent across alterations in speed and slopes. Backpack carriage induces alterations in gait kinematics in healthy children, raising questions regarding the clinical consequences related to orthopedic and neurological diseases and ergonomics. However, to support clinical decisions and characterize backpack carriage, muscle synergies can help with understanding the alterations induced in this condition at the motor control level. In this study, we investigated how children adjust the recruitment of motor patterns during locomotion, when greater muscular demands are required (backpack carriage). Twenty healthy male children underwent an instrumental gait analysis and muscle synergies extraction during three walking conditions: self-selected, fast and load conditions. In the fast condition, a reduction in the number of synergies (three to four) was needed for reconstructing the EMG signal with the same accuracy as in the other conditions (three to five). Synergies were grouped in only four clusters in the fast condition, while five clusters were needed for the self-selected condition. The right number of clusters was not clearly identified in the load condition. Speed and backpack carriage altered nearly every spatial-temporal parameter of gait, whereas kinematic alterations reflected mainly hip and pelvis adaptations. Although the synergistic patterns were consistent across conditions, indicating a similar motor pattern in different conditions, the fast condition required fewer synergies for reconstructing the EMG signal with the same level of accuracy.

Abnormal interlimb coordination of motor developmental delay during infant crawling based on kinematic synergy analysis

BACKGROUND

Previous studies have reported that abnormal interlimb coordination is a typical characteristic of motor developmental delay (MDD) during human movement, which can be visually manifested as abnormal motor postures. Clinically, the scale assessments are usually used to evaluate interlimb coordination, but they rely heavily on the subjective judgements of therapists and lack quantitative analysis. In addition, although abnormal interlimb coordination of MDD have been studied, it is still unclear how this abnormality is manifested in physiology-related kinematic features.

OBJECTIVES

This study aimed to evaluate how abnormal interlimb coordination of MDD during infant crawling was manifested in the stability of joints and limbs, activation levels of synergies and intrasubject consistency from the kinematic synergies of tangential velocities of joints perspective.

METHODS

Tangential velocities of bilateral shoulder, elbow, wrist, hip, knee and ankle over time were computed from recorded three-dimensional joint trajectories in 40 infants with MDD [16 infants at risk of developmental delay, 11 infants at high risk of developmental delay, 13 infants with confirmed developmental delay (CDD group)] and 20 typically developing infants during hands-and-knees crawling. Kinematic synergies and corresponding activation coefficients were derived from those joint velocities using the non-negative matrix factorization algorithm. The variability accounted for yielded by those synergies and activation coefficients, and the synergy weightings in those synergies were used to measure the stability of joints and limbs. To quantify the activation levels of those synergies, the full width at half maximum and center of activity of activation coefficients were calculated. In addition, the intrasubject consistency was measured by the cosine similarity of those synergies and activation coefficients.

RESULTS

Interlimb coordination patterns during infant crawling were the combinations of four types of single-limb movements, which represent the dominance of each of the four limbs. MDD mainly reduced the stability of joints and limbs, and induced the abnormal activation levels of those synergies. Meanwhile, MDD generally reduced the intrasubject consistency, especially in CDD group.

CONCLUSIONS

These features have the potential for quantitatively evaluating abnormal interlimb coordination in assisting the clinical diagnosis and motor rehabilitation of MDD.

Quantifying changes in individual-specific template-based representations of center-of-mass dynamics during walking with ankle exoskeletons using Hybrid-SINDy

Ankle exoskeletons alter whole-body walking mechanics, energetics, and stability by altering center-of-mass (CoM) motion. Controlling the dynamics governing CoM motion is, therefore, critical for maintaining efficient and stable gait. However, how CoM dynamics change with ankle exoskeletons is unknown, and how to optimally model individual-specific CoM dynamics, especially in individuals with neurological injuries, remains a challenge. Here, we evaluated individual-specific changes in CoM dynamics in unimpaired adults and one individual with post-stroke hemiparesis while walking in shoes-only and with zero-stiffness and high-stiffness passive ankle exoskeletons. To identify optimal sets of physically interpretable mechanisms describing CoM dynamics, termed template signatures, we leveraged hybrid sparse identification of nonlinear dynamics (Hybrid-SINDy), an equation-free data-driven method for inferring sparse hybrid dynamics from a library of candidate functional forms. In unimpaired adults, Hybrid-SINDy automatically identified spring-loaded inverted pendulum-like template signatures, which did not change with exoskeletons (p > 0.16), except for small changes in leg resting length (p < 0.001). Conversely, post-stroke paretic-leg rotary stiffness mechanisms increased by 37-50% with zero-stiffness exoskeletons. While unimpaired CoM dynamics appear robust to passive ankle exoskeletons, how neurological injuries alter exoskeleton impacts on CoM dynamics merits further investigation. Our findings support Hybrid-SINDy's potential to discover mechanisms describing individual-specific CoM dynamics with assistive devices.

Intermuscular coherence reveals that affective emotional pictures modulate neural control mechanisms during the initiation of arm pointing movements

Introduction

Several studies in psychology provided compelling evidence that emotions significantly impact motor control. Yet, these evidences mostly rely on behavioral investigations, whereas the underlying neurophysiological processes remain poorly understood.

Methods

Using a classical paradigm in motor control, we tested the impact of affective pictures associated with positive, negative or neutral valence on the kinematics and patterns of muscle activations of arm pointing movements performed from a standing position. The hand reaction and movement times were measured and electromyography (EMG) was used to measure the activities from 10 arm, leg and trunk muscles that are involved in the postural maintenance and arm displacement in pointing movements. Intermuscular coherence (IMC) between pairs of muscles was computed to measure changes in patterns of muscle activations related to the emotional stimuli.

Results

The hand movement time increased when an emotional picture perceived as unpleasant was presented as compared to when the emotional picture was perceived as pleasant. When an unpleasant emotional picture was presented, beta (β, 15-35 Hz) and gamma (γ, 35-60 Hz) IMC decreased in the recorded pairs of postural muscles during the initiation of pointing movements. Moreover, a linear relationship between the magnitude of the intermuscular coherence in the pairs of posturo-focal muscles and the hand movement time was found in the unpleasant scenarios.

Discussion

These findings reveal that emotional stimuli can significantly affect the content of the motor command sent by the central nervous system to muscles when performing voluntary goal-directed movements.

Intramuscular and intermuscular coherence analysis while obstacle crossing during treadmill gait

PURPOSE

This study aimed to identify the contribution of the common synaptic drives to motor units during obstacle avoidance, using coherence analysis between a-pair electromyography (EMG) signals (EMG-EMG coherence).

MATERIALS AND METHODS

Fourteen healthy volunteers walked on a treadmill with and without obstacle avoidance. During obstacle gait, subjects were instructed to step over an obstacle with their right leg while walking that would randomly and unpredictably appear. Surface EMG signals were recorded from the following muscles of the right leg: the proximal and distal ends of tibialis anterior (TAp and TAd), biceps femoris (BF), semitendinosus (ST), lateral gastrocnemius (LG), and medial gastrocnemius (MG). Beta-band (13-30 Hz) EMG-EMG coherence was analysed.

RESULTS

Beta-band EMG-EMG coherence of TAp-TAd during swing phase and BF-ST during pre and initial swing phase when stepping over an obstacle were significantly higher compared to normal gait (both p < 0.05). Beta-band EMG-EMG coherence of TAp-TAd, BF-ST, and LG-MG during stance phase were not significantly different between the two gait conditions (all p > 0.05).

CONCLUSIONS

The present findings suggest increased common synaptic drives to motor units in ankle dorsiflexor and knee flexor muscles during obstacle avoidance. It also may reflect an increased cortical contribution to modify the gait patterns to avoid an obstacle.

Muscle synergies are associated with intermuscular coherence and cortico-synergy coherence in an isometric upper limb task

To elucidate the underlying physiological mechanisms of muscle synergies, we investigated long-range functional connectivity by cortico-muscular (CMC), intermuscular (IMC) and cortico-synergy (CSC) coherence. Fourteen healthy participants executed an isometric upper limb task in synergy-tuned directions. Cortical activity was recorded using 32-channel electroencephalography (EEG) and muscle activity using 16-channel electromyography (EMG). Using non-negative matrix factorisation (NMF), we calculated muscle synergies from two different tasks. A preliminary multidirectional task was used to identify synergy-preferred directions (PDs). A subsequent coherence task, consisting of generating forces isometrically in the synergy PDs, was used to assess the functional connectivity properties of synergies. Overall, we were able to identify four different synergies from the multidirectional task. A significant alpha band IMC was consistently present in all extracted synergies. Moreover, IMC alpha band was higher between muscles with higher weights within a synergy. Interestingly, CSC alpha band was also significantly higher across muscles with higher weights within a synergy. In contrast, no significant CMC was found between the motor cortex area and synergy muscles. The presence of a shared input onto synergistic muscles within a synergy supports the idea of neurally derived muscle synergies that build human movement. Our findings suggest cortical modulation of some of the synergies and the consequential existence of shared input between muscles within cortically modulated synergies.

Phasic and tonic muscle synergies are different in number, structure and sparseness

In the last two decades, muscle synergies analysis has been commonly used to assess the neurophysiological mechanisms underlying human motor control. Several synergy models and algorithms have been employed for processing the electromyographic (EMG) signal, and it has been shown that the coordination of motor control is characterized by the presence of phasic (movement-related) and tonic (anti-gravity and related to co-contraction) EMG components. Neural substrates indicate that phasic and tonic components have non-homogeneous origin; however, it is still unclear if these components are generated by the same set of synergies or by distinct synergies. This study aims at testing whether phasic and tonic components are generated by distinct phasic and tonic synergies or by the same set of synergies with phasic and tonic activation coefficients. The study also aims at characterizing the differences between the phasic and the tonic synergies. Using a comprehensive mapping of upper-limb point-to-point movements, synergies were extracted from phasic and tonic EMG signal separately, estimating the tonic components with a linear ramp model. The goodness of reconstruction (R2) as a function of the number of synergies was compared, and sets of synergies extracted from each dataset at three R2 threshold levels (0.80, 0.85, 0.90) were retained for further analysis. Then, shared, phasic-specific, and tonic-specific synergies were extracted from the two datasets concatenated. The dimensionality of the synergies shared between the phasic and the tonic datasets was estimated with a bootstrap procedure based on the evaluation of the distribution of principal angles between the subspaces spanned by phasic and tonic synergies due to noise. We found only few shared synergies, indicating that phasic and tonic synergies have in general different structures. To compare consistent differences in synergy composition, shared, phasic-specific, and tonic-specific synergies were clustered separately. Phasic-specific clusters were more numerous than tonic-specific ones, suggesting that they were more differentiated among subjects. The structure of phasic clusters and the higher sparseness indicated that phasic synergies capture specific muscle activation patterns related to the movement while tonic synergies show co-contraction of multiple muscles for joint stabilization and holding postures. These results suggest that in many scenarios phasic and tonic synergies should be extracted separately, especially when performing muscle synergy analysis in patients with abnormal tonic activity and for tuning devices with gravity support.

Computational prediction of muscle synergy using a finite element framework for a musculoskeletal model on lower limb

Previous studies have demonstrated that the central nervous system activates muscles in module patterns to reduce the complexity needed to control each muscle while producing a movement, which is referred to as muscle synergy. In previous musculoskeletal modeling-based muscle synergy analysis studies, as a result of simplification of the joints, a conventional rigid-body link musculoskeletal model failed to represent the physiological interactions of muscle activation and joint kinematics. However, the interaction between the muscle level and joint level that exists in vivo is an important relationship that influences the biomechanics and neurophysiology of the musculoskeletal system. In the present, a lower limb musculoskeletal model coupling a detailed representation of a joint including complex contact behavior and material representations was used for muscle synergy analysis using a decomposition method of non-negative matrix factorization (NMF). The complexity of the representation of a joint in a musculoskeletal system allows for the investigation of the physiological interactions in vivo on the musculoskeletal system, thereby facilitating the decomposition of the muscle synergy. Results indicated that, the activities of the 20 muscles on the lower limb during the stance phase of gait could be controlled by three muscle synergies, and total variance accounted for by synergies was 86.42%. The characterization of muscle synergy and musculoskeletal biomechanics is consistent with the results, thus explaining the formational mechanism of lower limb motions during gait through the reduction of the dimensions of control issues by muscle synergy and the central nervous system.

Muscle synergies for evaluating upper limb in clinical applications: A systematic review

INTRODUCTION

Muscle synergies have been proposed as a strategy employed by the central nervous system to control movements. Muscle synergy analysis is a well-established framework to examine the pathophysiological basis of neurological diseases and has been applied for analysis and assessment in clinical applications in the last decades, even if it has not yet been widely used in clinical diagnosis, rehabilitative treatment and interventions. Even if inconsistencies in the outputs among studies and lack of a normative pipeline including signal processing and synergy analysis limit the progress, common findings and results are identifiable as a basis for future research. Therefore, a literature review that summarizes methods and main findings of previous works on upper limb muscle synergies in clinical environment is needed to i) summarize the main findings so far, ii) highlight the barriers limiting their use in clinical applications, and iii) suggest future research directions needed for facilitating translation of experimental research to clinical scenarios.

METHODS

Articles in which muscle synergies were used to analyze and assess upper limb function in neurological impairments were reviewed. The literature research was conducted in Scopus, PubMed, and Web of Science. Experimental protocols (e.g., the aim of the study, number and type of participants, number and type of muscles, and tasks), methods (e.g., muscle synergy models and synergy extraction methods, signal processing methods), and the main findings of eligible studies were reported and discussed.

RESULTS

383 articles were screened and 51 were selected, which involved a total of 13 diseases and 748 patients and 1155 participants. Each study investigated on average 15 ± 10 patients. Four to forty-one muscles were included in the muscle synergy analysis. Point-to-point reaching was the most used task. The preprocessing of EMG signals and algorithms for synergy extraction varied among studies, and non-negative matrix factorization was the most used method. Five EMG normalization methods and five methods for identifying the optimal number of synergies were used in the selected papers. Most of the studies report that analyses on synergy number, structure, and activations provide novel insights on the physiopathology of motor control that cannot be gained with standard clinical assessments, and suggest that muscle synergies may be useful to personalize therapies and to develop new therapeutic strategies. However, in the selected studies synergies were used only for assessment; different testing procedures were used and, in general, study-specific modifications of muscle synergies were observed; single session or longitudinal studies mainly aimed at assessing stroke (71% of the studies), even though other pathologies were also investigated. Synergy modifications were either study-specific or were not observed, with few analyses available for temporal coefficients. Thus, several barriers prevent wider adoption of muscle synergy analysis including a lack of standardized experimental protocols, signal processing procedures, and synergy extraction methods. A compromise in the design of the studies must be found to combine the systematicity of motor control studies and the feasibility of clinical studies. There are however several potential developments that might promote the use of muscle synergy analysis in clinical practice, including refined assessments based on synergistic approaches not allowed by other methods and the availability of novel models. Finally, neural substrates of muscle synergies are discussed, and possible future research directions are proposed.

CONCLUSIONS

This review provides new perspectives about the challenges and open issues that need to be addressed in future work to achieve a better understanding of motor impairments and rehabilitative therapy using muscle synergies. These include the application of the methods on wider scales, standardization of procedures, inclusion of synergies in the clinical decisional process, assessment of temporal coefficients and temporal-based models, extensive work on the algorithms and understanding of the physio-pathological mechanisms of pathology, as well as the application and adaptation of synergy-based approaches to various rehabilitative scenarios for increasing the available evidence.

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.

Spatial and Temporal Muscle Synergies Provide a Dual Characterization of Low-dimensional and Intermittent Control of Upper-limb Movements

Muscle synergy analysis investigates the neurophysiological mechanisms that the central nervous system employs to coordinate muscles. Several models have been developed to decompose electromyographic (EMG) signals into spatial and temporal synergies. However, using multiple approaches can complicate the interpretation of results. Spatial synergies represent invariant muscle weights modulated with variant temporal coefficients; temporal synergies are invariant temporal profiles that coordinate variant muscle weights. While non-negative matrix factorization allows to extract both spatial and temporal synergies, the comparison between the two approaches was rarely investigated targeting a large set of multi-joint upper-limb movements. Spatial and temporal synergies were extracted from two datasets with proximal (16 subjects, 10M, 6F) and distal upper-limb movements (30 subjects, 21M, 9F), focusing on their differences in reconstruction accuracy and inter-individual variability. We showed the existence of both spatial and temporal structure in the EMG data, comparing synergies with those from a surrogate dataset in which the phases were shuffled preserving the frequency content of the original data. The two models provide a compact characterization of motor coordination at the spatial or temporal level, respectively. However, a lower number of temporal synergies are needed to achieve the same reconstruction R²: spatial and temporal synergies may capture different hierarchical levels of motor control and are dual approaches to the characterization of low-dimensional coordination of the upper-limb. Last, a detailed characterization of the structure of the temporal synergies suggested that they can be related to intermittent control of the movement, allowing high flexibility and dexterity. These results improve neurophysiology understanding in several fields such as motor control, rehabilitation, and prosthetics.

Motor and cognitive deficits limit the ability to flexibly modulate spatiotemporal gait features in older adults with mild cognitive impairment

Introduction: Dance-based therapies are an emerging form of movement therapy aiming to improve motor and cognitive function in older adults with mild cognitive impairments (MCIs). Despite the promising effects of dance-based therapies on function, it remains unclear how age-related declines in motor and cognitive function affect movement capacity and influence which movements and rhythms maximize dance therapy efficacy. Here, we evaluated the effects of age and MCI on the ability to accurately modulate spatial (i.e., joint kinematics), temporal (i.e., step timing), and spatiotemporal features of gait to achieve spatial and temporal targets during walking. Methods: We developed novel rhythmic movement sequences-nine spatial, nine temporal, and four spatiotemporal-that deviated from typical spatial and temporal features of walking. Healthy young adults (HYA), healthy older adults (HOA), and adults with MCI were trained on each gait modification before performing the modification overground, with kinematic data recorded using wearable sensors. Results: HOA performed spatial (p = 0.010) and spatiotemporal (p = 0.048) gait modifications less accurately than HYA. Individuals with MCI performed spatiotemporal gait modifications less accurately than HOA (p = 0.017). Spatial modifications to the swing phase of gait (p = 0.006, Cohen's d = -1.3), and four- and six-step Duple rhythms during temporal modifications (p ≤ 0.030, Cohen's d ≤ 0.9) elicited the largest differences in gait performance in HYA vs. HOA and HOA vs. MCI, respectively. Discussion: These findings suggest that age-related declines in strength and balance reduce the ability to accurately modulate spatial gait features, while declines in working memory in individuals with MCI may reduce the ability to perform longer temporal gait modification sequences. Differences in rhythmic movement sequence performance highlight motor and cognitive factors potentially underlying deficits in gait modulation capacity, which may guide therapy personalization and provide more sensitive indices to track intervention efficacy.

Effects of orthoses on muscle activity and synergy during gait

An orthosis is often used in rehabilitation to improve kinetic and kinematic parameters during gait. However, whether changes in neural control depend on wearing an orthosis during gait is unclear. We measured the muscle activity and synergy of the lower limb muscles without orthosis and with two types of orthoses: ankle-foot orthosis (AFO) and knee-ankle-foot orthosis (KAFO). Muscle activity during gait was measured in 15 healthy adults, and muscle synergies were extracted using non-negative matrix factorization. The results revealed that some muscle activities were significantly different among the three conditions. Post-hoc analysis indicated differences between each condition. Knee extensor muscle activity related to the loading response was significantly increased by wearing the AFO. In the KAFO condition, hip abductor muscle activity related to weight bearing was significantly decreased, and ankle dorsiflexor muscle activity was increased to secure clearance during the swing phase. However, the number of muscle synergies and complexity of muscle synergy did not significantly change among these conditions. However, along with changes in muscle activity, the activation pattern and weightings of muscle synergies tended to change with the use of orthoses. Each muscle activity was changed by wearing the orthosis; however, the immediate mechanical constraint did not change the framework of muscle synergy.

Automated estimation of ankle muscle EMG envelopes and resulting plantar-dorsi flexion torque from 64 garment-embedded electrodes uniformly distributed around the human leg

The design of personalized movement training and rehabilitation pipelines relies on the ability of assessing the activation of individual muscles concurrently with the resulting joint torques exerted during functional movements. Despite advances in motion capturing, force sensing and bio-electrical recording technologies, the estimation of muscle activation and resulting force still relies on lengthy experimental and computational procedures that are not clinically viable. This work proposes a wearable technology for the rapid, yet quantitative, assessment of musculoskeletal function. It comprises of (1) a soft leg garment sensorized with 64 uniformly distributed electromyography (EMG) electrodes, (2) an algorithm that automatically groups electrodes into seven muscle-specific clusters, and (3) a EMG-driven musculoskeletal model that estimates the resulting force and torque produced about the ankle joint sagittal plane. Our results show the ability of the proposed technology to automatically select a sub-set of muscle-specific electrodes that enabled accurate estimation of muscle excitations and resulting joint torques across a large range of biomechanically diverse movements, underlying different excitation patterns, in a group of eight healthy individuals. This may substantially decrease time needed for localization of muscle sites and electrode placement procedures, thereby facilitating applicability of EMG-driven modelling pipelines in standard clinical protocols.

The Number and Structure of Muscle Synergies Depend on the Number of Recorded Muscles: A Pilot Simulation Study with OpenSim

The muscle synergy approach is used to evaluate motor control and to quantitatively determine the number and structure of the modules underlying movement. In experimental studies regarding the upper limb, typically 8 to 16 EMG probes are used depending on the application, although the number of muscles involved in motor generation is higher. Therefore, the number of motor modules may be underestimated and the structure altered with the standard spatial synergy model based on the non-negative matrix factorization (NMF). In this study, we compared the number and structure of muscle synergies when considering 12 muscles (an "average" condition that represents previous studies) and 32 muscles of the upper limb, also including multiple muscle heads and deep muscles. First, we estimated the muscle activations with an upper-limb model in OpenSim using data from multi-directional reaching movements acquired in experimental sessions; then, spatial synergies were extracted from EMG activations from 12 muscles and from 32 muscles and their structures were compared. Finally, we compared muscle synergies obtained from OpenSim and from real experimental EMG signals to assess the reliability of the results. Interestingly, we found that on average, an additional synergy is needed to reconstruct the same R² level with 32 muscles with respect to 12 muscles; synergies have a very similar structure, although muscles with comparable physiological functions were added to the synergies extracted with 12 muscles. The additional synergies, instead, captured patterns that could not be identified with only 12 muscles. We concluded that current studies may slightly underestimate the number of controlled synergies, even though the main structure of synergies is not modified when adding more muscles. We also show that EMG activations estimated with OpenSim are in partial (but not complete) agreement with experimental recordings. These findings may have significative implications for motor control and clinical studies.

Toward a unifying framework for the modeling and identification of motor primitives

A large body of evidence suggests that human and animal movements, despite their apparent complexity and flexibility, are remarkably structured. Quantitative analyses of various classes of motor behaviors consistently identify spatial and temporal features that are invariant across movements. Such invariant features have been observed at different levels of organization in the motor system, including the electromyographic, kinematic, and kinetic levels, and are thought to reflect fixed modules-named motor primitives-that the brain uses to simplify the construction of movement. However, motor primitives across space, time, and organization levels are often described with ad-hoc mathematical models that tend to be domain-specific. This, in turn, generates the need to use model-specific algorithms for the identification of both the motor primitives and additional model parameters. The lack of a comprehensive framework complicates the comparison and interpretation of the results obtained across different domains and studies. In this work, we take the first steps toward addressing these issues, by introducing a unifying framework for the modeling and identification of qualitatively different classes of motor primitives. Specifically, we show that a single model, the anechoic mixture model, subsumes many popular classes of motor primitive models. Moreover, we exploit the flexibility of the anechoic mixture model to develop a new class of identification algorithms based on the Fourier-based Anechoic Demixing Algorithm (FADA). We validate our framework by identifying eight qualitatively different classes of motor primitives from both simulated and experimental data. We show that, compared to established model-specific algorithms for the identification of motor primitives, our flexible framework reaches overall comparable and sometimes superior reconstruction performance. The identification framework is publicly released as a MATLAB toolbox (FADA-T, https://tinyurl.com/compsens) to facilitate the identification and comparison of different motor primitive models.

EMG-driven musculoskeletal model calibration with estimation of unmeasured muscle excitations via synergy extrapolation

Subject-specific electromyography (EMG)-driven musculoskeletal models that predict muscle forces have the potential to enhance our knowledge of internal biomechanics and neural control of normal and pathological movements. However, technical gaps in experimental EMG measurement, such as inaccessibility of deep muscles using surface electrodes or an insufficient number of EMG channels, can cause difficulties in collecting EMG data from muscles that contribute substantially to joint moments, thereby hindering the ability of EMG-driven models to predict muscle forces and joint moments reliably. This study presents a novel computational approach to address the problem of a small number of missing EMG signals during EMG-driven model calibration. The approach (henceforth called "synergy extrapolation" or SynX) linearly combines time-varying synergy excitations extracted from measured muscle excitations to estimate 1) unmeasured muscle excitations and 2) residual muscle excitations added to measured muscle excitations. Time-invariant synergy vector weights defining the contribution of each measured synergy excitation to all unmeasured and residual muscle excitations were calibrated simultaneously with EMG-driven model parameters through a multi-objective optimization. The cost function was formulated as a trade-off between minimizing joint moment tracking errors and minimizing unmeasured and residual muscle activation magnitudes. We developed and evaluated the approach by treating a measured fine wire EMG signal (iliopsoas) as though it were "unmeasured" for walking datasets collected from two individuals post-stroke-one high functioning and one low functioning. How well unmeasured muscle excitations and activations could be predicted with SynX was assessed quantitatively for different combinations of SynX methodological choices, including the number of synergies and categories of variability in unmeasured and residual synergy vector weights across trials. The two best methodological combinations were identified, one for analyzing experimental walking trials used for calibration and another for analyzing experimental walking trials not used for calibration or for predicting new walking motions computationally. Both methodological combinations consistently provided reliable and efficient estimates of unmeasured muscle excitations and activations, muscle forces, and joint moments across both subjects. This approach broadens the possibilities for EMG-driven calibration of muscle-tendon properties in personalized neuromusculoskeletal models and may eventually contribute to the design of personalized treatments for mobility impairments.

Analysis of Muscle Activity in the Sit-to-Stand Motion When Knee Movability is Disturbed

Sit-to-stand motion is an important daily activity, and disability of motion can significantly reduce quality of life. Therefore, it is important to understand the mechanism of sit-to-stand motion in order to prevent such scenarios. The sit-to-stand motion was found to be generated by four muscle groups, through muscle synergy. However, it is unclear how muscle synergy can be controlled. Human sit-to-stand motion may be planned based on body condition before motion. In this study, we aimed to clarify the relationship between body condition and muscle activity during the sit-to-stand motion. Accordingly, we measured the muscle activity when knee movability was disturbed as a condition of body change. We also measured the muscle activity during normal sit-to-stand motion and sit-to-stand motion with disturbed knee movability using surface electromyography. Subsequently, we extracted the muscle synergy from the measured muscle activity and compared the activity levels of muscle synergy. The results revealed that muscle activity contributing to forward bending increased and that contributing to the rise of the hip and stabilization decreased when knee movability was disturbed. These results suggest that humans compensate for disturbed knee movability with forward momentum and bending motion. Moreover, this implies that humans adjust their motion to various environments or body conditions by adjusting the level of forward bending activity.

Evaluation of Methods for the Extraction of Spatial Muscle Synergies

Muscle synergies have been largely used in many application fields, including motor control studies, prosthesis control, movement classification, rehabilitation, and clinical studies. Due to the complexity of the motor control system, the full repertoire of the underlying synergies has been identified only for some classes of movements and scenarios. Several extraction methods have been used to extract muscle synergies. However, some of these methods may not effectively capture the nonlinear relationship between muscles and impose constraints on input signals or extracted synergies. Moreover, other approaches such as autoencoders (AEs), an unsupervised neural network, were recently introduced to study bioinspired control and movement classification. In this study, we evaluated the performance of five methods for the extraction of spatial muscle synergy, namely, principal component analysis (PCA), independent component analysis (ICA), factor analysis (FA), nonnegative matrix factorization (NMF), and AEs using simulated data and a publicly available database. To analyze the performance of the considered extraction methods with respect to several factors, we generated a comprehensive set of simulated data (ground truth), including spatial synergies and temporal coefficients. The signal-to-noise ratio (SNR) and the number of channels (NoC) varied when generating simulated data to evaluate their effects on ground truth reconstruction. This study also tested the efficacy of each synergy extraction method when coupled with standard classification methods, including K-nearest neighbors (KNN), linear discriminant analysis (LDA), support vector machines (SVM), and Random Forest (RF). The results showed that both SNR and NoC affected the outputs of the muscle synergy analysis. Although AEs showed better performance than FA in variance accounted for and PCA in synergy vector similarity and activation coefficient similarity, NMF and ICA outperformed the other three methods. Classification tasks showed that classification algorithms were sensitive to synergy extraction methods, while KNN and RF outperformed the other two methods for all extraction methods; in general, the classification accuracy of NMF and PCA was higher. Overall, the results suggest selecting suitable methods when performing muscle synergy-related analysis.

Central Commands to the Elbow and Shoulder Muscles During Circular Planar Movements of Hand With Simultaneous Generation of Tangential Forces

This study examines some of the non-linear effects of signal transduction in the human motor system, with particular emphasis on muscle hysteresis. The movement tests were analyzed in a group of eight subjects, which were asked to develop tangential force using visual biofeedback while performing slow, externally imposed, circular movements of right hand holding a moving handle operated by a computerized mechatronic system. The positional changes in the averaged EMGs of the elbow and shoulder muscles were compared for all combinations of direction of movement and generated force. Additionally, for one of the subjects, there was carried out MRI identification and 3D printing of the bones of the forelimb, shoulder, scapula and collarbone, which made it possible to reconstruct for him the length and force traces of all the muscles under study. The averaged EMG traces in muscles of both joints show their close correspondence to the related force traces, however, the co-activation patterns of activity in agonists and antagonists were also often encountered. The EMG waves related to the respective force waves were strongly dependent on the predominant direction of the muscle length changes within the correspondent force wave locations: the EMG intensities were higher for the shortening muscle movements (concentric contractions) and lower during muscle lengthening (eccentric contractions). The data obtained allows to suggest that for two-joint movements of the forelimbs, it is sufficient to consider the force and activation synergies (patterns of simultaneous activity in different muscles), ignoring at the first stage the effects associated with kinematic synergy. On the other hand, the data obtained indicate that the movement kinematics has a strong modulating effect on the activation synergy, dividing it into concentric and eccentric subtypes, in accordance with the known non-linear features of the muscle dynamics. It has been shown that the concentric and eccentric differences in the responses of the shoulder muscles are more clearly distinguishable than those in the elbow muscles. The shoulder muscles also have a more pronounced symmetry of the averaged EMG responses with respect to the ascending and descending phases of force waves, while demonstrating a lower degree of antagonist cocontraction. The data obtained suggest that the central commands in two-joint movements are determined mainly by the interdependence of force and activation synergies including both intra- and inter-joint components, while kinematic synergy can be interpreted as a potent modulator of activation synergy.

Clarify Sit-to-Stand Muscle Synergy and Tension Changes in Subacute Stroke Rehabilitation by Musculoskeletal Modeling

Post-stroke patients exhibit distinct muscle activation electromyography (EMG) features in sit-to-stand (STS) due to motor deficiency. Muscle activation amplitude, related to muscle tension and muscle synergy activation levels, is one of the defining EMG features that reflects post-stroke motor functioning and motor impairment. Although some qualitative findings are available, it is not clear if and how muscle activation amplitude-related biomechanical attributes may quantitatively reflect during subacute stroke rehabilitation. To better enable a longitudinal investigation into a patient's muscle activation changes during rehabilitation or an inter-subject comparison, EMG normalization is usually applied. However, current normalization methods using maximum voluntary contraction (MVC) or within-task peak/mean EMG may not be feasible when MVC cannot be obtained from stroke survivors due to motor paralysis and the subject of comparison is EMG amplitude. Here, focusing on the paretic side, we first propose a novel, joint torque-based normalization method that incorporates musculoskeletal modeling, forward dynamics simulation, and mathematical optimization. Next, upon method validation, we apply it to quantify changes in muscle tension and muscle synergy activation levels in STS motor control units for patients in subacute stroke rehabilitation. The novel method was validated against MVC-normalized EMG data from eight healthy participants, and it retained muscle activation amplitude differences for inter- and intra-subject comparisons. The proposed joint torque-based method was also compared with the common static optimization based on squared muscle activation and showed higher simulation accuracy overall. Serial STS measurements were conducted with four post-stroke patients during their subacute rehabilitation stay (137 ± 22 days) in the hospital. Quantitative results of patients suggest that maximum muscle tension and activation level of muscle synergy temporal patterns may reflect the effectiveness of subacute stroke rehabilitation. A quality comparison between muscle synergies computed with the conventional within-task peak/mean EMG normalization and our proposed method showed that the conventional was prone to activation amplitude overestimation and underestimation. The contributed method and findings help recapitulate and understand the post-stroke motor recovery process, which may facilitate developing more effective rehabilitation strategies for future stroke survivors.

A new biological central pattern generator model and its relationship with the motor units

The central pattern generator (CPG) is a key neural-circuit component of the locomotion control system. Recently, numerous molecular and genetic approaches have been proposed for investigating the CPG mechanisms. The rhythm in the CPG locomotor circuits comes from the activity in the ipsilateral excitatory neurons whose output is controlled by inter-neuron inhibitory connections. Conventional models for simulating the CPG mechanism are complex Hodgkin-Huxley-type models. Inspired by biological investigations and the continuous-time Matsuoka model, we propose new integral-order and fractional-order CPG models, which consider time delays and synaptic interfaces. The phase diagrams exhibit limit cycles and periodic solutions, in agreement with the CPG biological characteristics. As well, the fractional-order model shows state transitions with order variations. In addition, we investigate the relationship between the CPG and the motor units through the construction of integral-order and fractional-order coupling models. Simulations of these coupling models show that the states generated by the three motor units are in accordance with the experimentally-obtained states in previous studies. The proposed models reveal that the CPG can regulate limb locomotion patterns through connection weights and synaptic interfaces. Moreover, in comparison to the integral-order models, the fractional-order ones appear to be more effective, and hence more suitable for describing the dynamics of the CPG biological system.

Body Weight Control Is a Key Element of Motor Control for Toddlers' Walking

New-borns can step when supported for about 70-80% of their own body weight. Gravity-related sensorimotor information might be an important factor in developing the ability to walk independently. We explored how body weight support alters motor control in toddlers during the first independent steps and in toddlers with about half a year of walking experience. Sixteen different typically developing children were assessed during (un)supported walking on a running treadmill. Electromyography of 18-24 bilateral leg and back muscles and vertical ground reaction forces were recorded. Strides were grouped into four levels of body weight support ranging from no (<10%), low (10-35%), medium (35-55%), and high (55-95%) support. We constructed muscle synergies and muscle networks and assessed differences between levels of support and between groups. In both groups, muscle activities could be described by four synergies. As expected, the mean activity decreased with body weight support around foot strikes. The younger first-steps group showed changes in the temporal pattern of the synergies when supported for more than 35% of their body weight. In this group, the muscle network was dense with several interlimb connections. Apparently, the ability to process gravity-related information is not fully developed at the onset of independent walking causing motor control to be fairly disperse. Synergy-specific sensitivity for unloading implies distinct neural mechanisms underlying (the emergence of) these synergies.

Control of Mammalian Locomotion by Somatosensory Feedback

When animals walk overground, mechanical stimuli activate various receptors located in muscles, joints, and skin. Afferents from these mechanoreceptors project to neuronal networks controlling locomotion in the spinal cord and brain. The dynamic interactions between the control systems at different levels of the neuraxis ensure that locomotion adjusts to its environment and meets task demands. In this article, we describe and discuss the essential contribution of somatosensory feedback to locomotion. We start with a discussion of how biomechanical properties of the body affect somatosensory feedback. We follow with the different types of mechanoreceptors and somatosensory afferents and their activity during locomotion. We then describe central projections to locomotor networks and the modulation of somatosensory feedback during locomotion and its mechanisms. We then discuss experimental approaches and animal models used to investigate the control of locomotion by somatosensory feedback before providing an overview of the different functional roles of somatosensory feedback for locomotion. Lastly, we briefly describe the role of somatosensory feedback in the recovery of locomotion after neurological injury. We highlight the fact that somatosensory feedback is an essential component of a highly integrated system for locomotor control. © 2021 American Physiological Society. Compr Physiol 11:1-71, 2021.

Comparison of forward versus backward walking on spatiotemporal and kinematic parameters on sand: A preliminary study

The purpose of this study was to investigate the spatiotemporal and kinematic parameters of backward walking (BW) and forward walking (FW) on sand. Randomly selected subjects (n = 28) were categorized into a sand group (SG, n = 14) and an overground group (OG, n = 14). SG was directed to perform both FW and BW on sand, while OG performed the same on the overground. Spatiotemporal and kinematic parameters were measured using the LegSys + device. The comparative findings of both the groups showed that the spatiotemporal parameters of SG varied significantly from those of OG in both FW and BW conditions (p < 0.05). The kinematic parameters varied significantly between the two groups only in the FW condition (p < 0.05). When compared within each group, spatiotemporal and kinematic parameters in the BW condition were significantly different from those in the FW condition. However, the percentages of stance, swing, and double support were not significantly different between FW and BW conditions (p > 0.05). This study suggests that sand walking is associated with a different gait pattern than overground walking, as evident from the analysis of the results of spatiotemporal and kinematic parameters in both FW and BW conditions. Therefore, sand walking can be used as a new approach to gait and balance training in clinical practice.

Gait Training after Stroke with a Wearable Robotic Device: A Case Report of Further Improvements in Walking Ability after a Recovery Plateau

Background:

Conventional rehabilitation is known to improve walking ability after stoke, but its effectiveness is often limited. Recent studies have shown that gait training combining conventional rehabilitation and robotic devices in stroke patients provides better results than conventional rehabilitation alone, suggesting that gait training with a robotic device may lead to further improvements in the walking ability recovered by conventional rehabilitation. Therefore, the aim of this report was to highlight the changes in kinematic and electromyographic data recorded during walking before and after gait training with the Honda Walking Assist Device^® (HWAT) in a male patient whose walking speed had reached a recovery plateau under conventional rehabilitation.

Case:

The patient was a 42-year-old man with severe hemiplegia caused by right putaminal hemorrhage. He underwent conventional rehabilitation for 20 weeks following the onset of stroke, after which his walking speed reached a recovery plateau. Subsequently, we added robotic rehabilitation using HWAT to his regular rehabilitation regimen, which resulted in improved step length symmetry and gait endurance. We also noted changes in muscle activity patterns during walking.

Discussion:

HWAT further improved the walking ability of a patient who had recovered with conventional rehabilitation; this improvement was accompanied by changes in muscle activity patterns during walking. The improvement in gait endurance exceeded the smallest meaningful change in stroke patients, suggesting that this improvement represented a noticeable enhancement in the quality of life in relation to mobility in the community. Further clinical trials are needed to confirm the results of the present case study.

Young adults recruit similar motor modules across walking, turning, and chair transfers

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

Modulation of spatial and temporal modules in lower limb muscle activations during walking with simulated reduced gravity

Gravity plays a crucial role in shaping patterned locomotor output to maintain dynamic stability during locomotion. The present study aimed to clarify the gravity-dependent regulation of modules that organize multiple muscle activities during walking in humans. Participants walked on a treadmill at seven speeds (1-6 km h-1 and a subject- and gravity-specific speed determined by the Froude number (Fr) corresponding to 0.25) while their body weight was partially supported by a lift to simulate walking with five levels of gravity conditions from 0.07 to 1 g. Modules, i.e., muscle-weighting vectors (spatial modules) and phase-dependent activation coefficients (temporal modules), were extracted from 12 lower-limb electromyographic (EMG) activities in each gravity (Fr ~ 0.25) using nonnegative matrix factorization. Additionally, a tensor decomposition model was fit to the EMG data to quantify variables depending on the gravity conditions and walking speed with prescribed spatial and temporal modules. The results demonstrated that muscle activity could be explained by four modules from 1 to 0.16 g and three modules at 0.07 g, and the modules were shared for both spatial and temporal components among the gravity conditions. The task-dependent variables of the modules acting on the supporting phase linearly decreased with decreasing gravity, whereas that of the module contributing to activation prior to foot contact showed nonlinear U-shaped modulation. Moreover, the profiles of the gravity-dependent modulation changed as a function of walking speed. In conclusion, reduced gravity walking was achieved by regulating the contribution of prescribed spatial and temporal coordination in muscle activities.

Effects of body weight support and guidance force settings on muscle synergy during Lokomat walking

BACKGROUND

The Lokomat is a robotic device that has been suggested to make gait therapy easier, more comfortable, and more efficient. In this study, we asked whether the Lokomat promotes physiological muscle activation patterns, a fundamental question when considering motor learning and adaptation.

METHODS

We investigated lower limb muscles coordination in terms of muscle activity level, muscle activity pattern similarity, and muscle synergy in 15 healthy participants walking at 3 km/h on either a treadmill or in a Lokomat at various guidance forces (GF: 30, 50 or 70%) and body weight supports (BWS: 30, 50 or 70% of participant's body weight).

RESULTS

Walking in the Lokomat was associated with a greater activation level of the rectus femoris and vastus medialis (×2-3) compared to treadmill walking. The level of activity tended to be diminished in gastrocnemius and semi-tendinosus, which particularly affected the similarity with treadmill walking (normalized scalar product NSP = 0.7-0.8). GF and BWS independently altered the muscle activation pattern in terms of amplitude and shape. Increasing BWS decreased the level of activity in all but one muscle (the soleus). Increasing GF slightly improved the similarity with treadmill walking for the tibialis anterior and vastus medialis muscles. The muscle synergies (N = 4) were similar (NSP = 0.93-0.97), but a cross-validation procedure revealed an alteration by the Lokomat. The activation of these synergies differed (NSP = 0.74-0.82).

CONCLUSION

The effects of GF and BWS are modest compared to the effect of the Lokomat itself, suggesting that Lokomat design should be improved to promote more typical muscle activity patterns.

Common and distinct muscle synergies during level and slope locomotion in the cat

Although it is well established that the motor control system is modular, the organization of muscle synergies during locomotion and their change with ground slope are not completely understood. For example, typical reciprocal flexor-extensor muscle synergies of level walking in cats break down in downslope: one-joint hip extensors are silent throughout the stride cycle, whereas hindlimb flexors demonstrate an additional stance phase-related electromyogram (EMG) burst (Smith JL, Carlson-Kuhta P, Trank TV. J Neurophysiol 79: 1702-1716, 1998). Here, we investigated muscle synergies during level, upslope (27°), and downslope (-27°) walking in adult cats to examine common and distinct features of modular organization of locomotor EMG activity. Cluster analysis of EMG burst onset-offset times of 12 hindlimb muscles revealed five flexor and extensor burst groups that were generally shared across slopes. Stance-related bursts of flexor muscles in downslope were placed in a burst group from level and upslope walking formed by the rectus femoris. Walking upslope changed swing/stance phase durations of level walking but not the cycle duration. Five muscle synergies computed using non-negative matrix factorization accounted for at least 95% of variance in EMG patterns in each slope. Five synergies were shared between level and upslope walking, whereas only three of those were shared with downslope synergies; these synergies were active during the swing phase and phase transitions. Two stance-related synergies of downslope walking were distinct; they comprised a mixture of flexors and extensors. We suggest that the modular organization of muscle activity during level and slope walking results from interactions between motion-related sensory feedback, CPG, and supraspinal inputs.NEW & NOTEWORTHY We demonstrated that the atypical EMG activities during cat downslope walking, silent one-joint hip extensors and stance-related EMG bursts in flexors, have many features shared with activities of level and upslope walking. Majority of EMG burst groups and muscle synergies were shared among these slopes, and upslope modulated the swing/stance phase duration but not cycle duration. Thus, synergistic EMG activities in all slopes might result from a shared CPG receiving somatosensory and supraspinal inputs.

Effects of an exoskeleton-assisted gait training on post-stroke lower-limb muscle coordination

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).

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.

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.

Greater Reliance on Cerebral Palsy-Specific Muscle Synergies During Gait Relates to Poorer Temporal-Spatial Performance Measures

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.

Simulated muscle activity in locomotion: implications of co-occurrence between effort minimisation and gait modularity for robot-assisted rehabilitation therapy

Evolution of gait rehabilitation robotic devices for stroke survivors has aimed at providing transparency to user's efforts and implementing 'assist-as-needed' paradigm. Alteration of muscle activity and synergies recruitment has been noticed in trials involving healthy subjects but no analytic tool has been proposed to understand root causes. In this paper, a simplified neuro-mechanical model is introduced for simulating lower limbs' muscle activity during unrestrained and device-constrained gait, taking into consideration exoskeleton-plus-treadmill and end-effector categories. Muscle control is based on the key hypothesis that optimality criterion pursues co-occurrence between effort minimisation and modularity during regular gait. Results highlight that modelised motion constraints on lower body raise additional redundancies which alter muscle activity and increase intervention external to unrestrained gait synergies. Accordingly, the developed simulations help to identify the inherent limitations of current technology: further degree of freedom addition to exoskeleton-plus-treadmill device could be useful but impractical, while end-effector devices would benefit significantly from an improved interaction management.

How to improve the muscle synergy analysis methodology?

Muscle synergy analysis is increasingly used in domains such as neurosciences, robotics, rehabilitation or sport sciences to analyze and better understand motor coordination. The analysis uses dimensionality reduction techniques to identify regularities in spatial, temporal or spatio-temporal patterns of multiple muscle activation. Recent studies have pointed out variability in outcomes associated with the different methodological options available and there was a need to clarify several aspects of the analysis methodology. While synergy analysis appears to be a robust technique, it remain a statistical tool and is, therefore, sensitive to the amount and quality of input data (EMGs). In particular, attention should be paid to EMG amplitude normalization, baseline noise removal or EMG filtering which may diminish or increase the signal-to-noise ratio of the EMG signal and could have major effects on synergy estimates. In order to robustly identify synergies, experiments should be performed so that the groups of muscles that would potentially form a synergy are activated with a sufficient level of activity, ensuring that the synergy subspace is fully explored. The concurrent use of various synergy formulations-spatial, temporal and spatio-temporal synergies- should be encouraged. The number of synergies represents either the dimension of the spatial structure or the number of independent temporal patterns, and we observed that these two aspects are often mixed in the analysis. To select a number, criteria based on noise estimates, reliability of analysis results, or functional outcomes of the synergies provide interesting substitutes to criteria solely based on variance thresholds.

Critical Issues and Imminent Challenges in the Use of sEMG in Return-To-Work Rehabilitation of Patients Affected by Neurological Disorders in the Epoch of Human-Robot Collaborative Technologies

Patients affected by neurological pathologies with motor disorders when they are of working age have to cope with problems related to employability, difficulties in working, and premature work interruption. It has been demonstrated that suitable job accommodation plans play a beneficial role in the overall quality of life of pathological subjects. A well-designed return-to-work program should consider several recent innovations in the clinical and ergonomic fields. One of the instrument-based methods used to monitor the effectiveness of ergonomic interventions is surface electromyography (sEMG), a multi-channel, non-invasive, wireless, wearable tool, which allows in-depth analysis of motor coordination mechanisms. Although the scientific literature in this field is extensive, its use remains significantly underexploited and the state-of-the-art technology lags expectations. This is mainly attributable to technical and methodological (electrode-skin impedance, noise, electrode location, size, configuration and distance, presence of crosstalk signals, comfort issues, selection of appropriate sensor setup, sEMG amplitude normalization, definition of correct sEMG-related outcomes and normative data) and cultural limitations. The technical and methodological problems are being resolved or minimized also thanks to the possibility of using reference books and tutorials. Cultural limitations are identified in the traditional use of qualitative approaches at the expense of quantitative measurement-based monitoring methods to design and assess ergonomic interventions and train operators. To bridge the gap between the return-to-work rehabilitation and other disciplines, several teaching courses, accompanied by further electrodes and instrumentations development, should be designed at all Bachelor, Master and PhD of Science levels to enhance the best skills available among physiotherapists, occupational health and safety technicians and ergonomists.

Evaluation of Synergy Extrapolation for Predicting Unmeasured Muscle Excitations from Measured Muscle Synergies

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 channels. Muscle synergy analysis (MSA) is a dimensionality reduction approach that decomposes 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 synergy excitation to all muscle excitations. This study evaluates how well missing muscle excitations can be predicted using synergy excitations extracted from muscles with available EMG data (henceforth called "synergy extrapolation" or SynX). The method was evaluated using a gait data set 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 measured EMG channels (collected using surface and fine wire electrodes) per leg. One fine wire EMG channel (either iliopsoas or adductor longus) was then treated as unmeasured. The synergy weights associated with the unmeasured muscle excitation were predicted by solving a nonlinear optimization problem where the errors between inverse dynamics and EMG-driven joint moments were minimized. The prediction process was performed for different synergy analysis algorithms (principal component analysis and non-negative matrix factorization), EMG normalization methods, and numbers of synergies. SynX performance was most influenced by the choice of synergy analysis algorithm and number of synergies. Principal component analysis with five or six synergies consistently predicted unmeasured muscle excitations the most accurately and with the greatest robustness to EMG normalization method. Furthermore, the associated joint moment matching accuracy was comparable to that produced by initial EMG-driven model calibration using all 16 EMG channels per leg. SynX may facilitate the assessment of human neuromuscular control and biomechanics when important EMG signals are missing.

Assessment of turning performance and muscle coordination in individuals post-stroke

Turning is an important activity of daily living and often compromised post-stroke. The fall rate for individuals post-stroke while turning is nearly four times as high compared to healthy adults, with most falls resulting in injury. Thus, there is a need for evidence-based rehabilitation targets to improve turning performance for individuals post-stroke. To produce well-coordinated movements, muscles can be organized into muscle modules (i.e., groups of co-excited muscles). Post-stroke these modules can be merged, leading to impaired muscle coordination and walking performance. However, the relationship between impaired coordination and turning performance is not well understood. Thus, the purpose of this study was to analyze the influence of impaired muscle coordination (i.e., merged modules) on turning performance (i.e., time and number of steps required to complete a turn, and smoothness and balance control during the turn). Individuals post-stroke and healthy controls performed three tasks including overground straight-line walking, a 90-degree turn, and a 180-degree turn. The number of muscle modules during straight-line walking were determined using non-negative matrix factorization. During 180-degree turning, those with two modules took longer to turn, used more steps and had less smooth movement. Those with reduced module complexity exhibited diminished balance control during both 90-degree and 180-degree turning. These results suggest obtaining independent modules should be an important aim in locomotor therapies aimed at improving turning performance. In addition, the time it takes to complete a 180-degree turn may provide useful clinical insight into impaired muscle coordination post-stroke.

SWEAT2 study: effectiveness of trunk training on muscle activity after stroke. A randomized controlled trial

BACKGROUND

Trunk training after stroke is an effective method for improving trunk control, standing balance and mobility. The SWEAT² study attempts to discover the underlying mechanisms leading to the observed mobility carry-over effects after trunk training.

AIM

A secondary analysis investigating the effect of trunk training on muscle activation patterns, muscle synergies and motor unit recruitment of trunk and lower limbs muscles, aimed to provide new insights in gait recovery after stroke.

DESIGN

Randomized controlled trial.

SETTING

Monocentric study performed in the RevArte Rehabilitation Hospital (Antwerp, Belgium).

POPULATION

Forty-five adults diagnosed with first stroke within five months, of which 39 completed treatment and were included in the analysis.

METHODS

Participants received 16 hours of additional trunk training (N.=19) or cognitive training (N.=20) over the course of four weeks (1 hour, 4 times a week). They were assessed by an instrumented gait analysis with electromyography of trunk and lower limb muscles. Outcome measures were linear integrated normalized envelopes of the electromyography signal, the amount and composition of muscle synergies calculated by nonnegative matrix factorization and motor unit recruitment calculated, by mean center wavelet frequencies. Multivariate analysis with post-hoc analysis and statistical parametric mapping of the continuous curves were performed.

RESULTS

No significant differences were found in muscle activation patterns and the amount of muscle synergies. In 42% of the subjects, trunk training resulted in an additional muscle synergy activating trunk muscles in isolation, as compared to 5% in the control group. Motor unit recruitment of the of trunk musculature showed decreased fast-twitch motor recruitment in the erector spinae muscle after trunk training: for the hemiplegic (t[37]=2.44, P=0.021) and non-hemiplegic erector spinae muscle (t[37]=2.36, P=0.024).

CONCLUSIONS

Trunk training improves selective control and endurance of trunk musculature after sub-acute stroke.

CLINICAL REHABILITATION IMPACT

What is new to the actual clinical rehabilitation knowledge is that: trunk training does not alter muscle activation patterns or the amount of muscle synergies over time; a decrease in fast-twitch motor recruitment in the erector spinae muscle was found during walking after trunk training; trunk training seems to increase the fatigue-resistance of the back muscles and enables more isolated activation.

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.

Muscle modes of the equestrian rider at walk, rising trot and canter

Equestrian sports have been a source of numerous studies throughout the past two decades, however, few scientists have focused on the biomechanical effects, including muscle activation, that the horse has on the rider. Because equitation is a sport of two (the horse-human dyad), we believe there is a need to fill in the knowledge gap in human biomechanics during riding. To investigate the differences between novice and advanced riders at a neuromuscular level we characterized the motor output of a set of riders’ key muscles during horse riding. Six recreational riders (24 ± 7 years) and nine professional riders (31 ± 5 years) from the Spanish Classical School of Riding (Lipica) volunteered to take part in this study. Riders’ upper body, core and lower limb muscles were monitored and synchronized with inertial data from the left horse’s leg at walk, rising trot and canter. We used principal component analysis to extract muscle modes. Three modes were identified in the advanced group whereas five modes were identified in the novice group. From the novice group, one mode united dorsal and ventral muscles of the body (reciprocal mode). Advanced riders showed higher core muscles engagement and better intermuscular coordination. We concluded that advanced horse riding is characterized by an ability to activate muscles contralaterally but not reciprocally (dorsal-ventral contraction). In addition, activating each muscle independently with different levels of activation, and the ability to quickly decrease overall muscle activity is distinctive of advanced riders.

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.

Muscle Synergies and Coherence Networks Reflect Different Modes of Coordination During Walking

When walking speed is increased, the frequency ratio between the arm and leg swing switches spontaneously from 2:1 to 1:1. We examined whether these switches are accompanied by changes in functional connectivity between multiple muscles. Subjects walked on a treadmill with their arms swinging along their body while kinematics and surface electromyography (EMG) of 26 bilateral muscles across the body were recorded. Walking speed was varied from very slow to normal. We decomposed EMG envelopes and intermuscular coherence spectra using non-negative matrix factorization (NMF), and the resulting modes were combined into multiplex networks and analyzed for their community structure. We found five relevant muscle synergies that significantly differed in activation patterns between 1:1 and 2:1 arm-leg coordination and the transition period between them. The corresponding multiplex network contained a single module indicating pronounced muscle co-activation patterns across the whole body during a gait cycle. NMF of the coherence spectra distinguished three EMG frequency bands: 4-8, 8-22, and 22-60 Hz. The community structure of the multiplex network revealed four modules, which clustered functional and anatomical linked muscles across modes of coordination. Intermuscular coherence at 4-22 Hz between upper and lower body and within the legs was particularly pronounced for 1:1 arm-leg coordination and was diminished when switching between modes of coordination. These findings suggest that the stability of arm-leg coordination is associated with modulations in long-distant neuromuscular connectivity.