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

Characterizing upper limb motor dysfunction with temporal and spatial distribution of muscle synergy extracted from high-density surface electromyography

Objective.To promote the development of objective and comprehensive motion function assessment for patients, based on high-density surface electromyography (HD-sEMG), this study investigates the temporal and spatial variations of neuromuscular activities related to upper limb motor dysfunction.Approach.Patients with unilateral upper limb motor dysfunction and healthy controls were enrolled in the study. HD-sEMG was collected from both arms while they were performing eight hand and wrist movements. Muscle synergies were extracted from the HD-sEMG. Symmetry of bilateral upper limb synergies and synergy differences between motions were proposed as spatial indicators to measure alterations in synergy spatial distribution. Additionally, as a temporal characteristic, the correlation of bilateral upper limb activation coefficient was proposed to describe the coordination control of the central nervous system. All temporal and spatial indicators were compared between patients and healthy subjects.Main results.The patients showed a significant decrease (p< 0.05) in the symmetry of bilateral upper limb synergy spatial distribution and correlation of bilateral upper limb activation coefficient. Patients with motor dysfunction also showed an increase in synergy similarity between motions, indicating altered spatial distribution of muscle synergies.Significance.These findings provide valuable insights into specific patterns associated with motor dysfunction, informing motor function assessment, and guiding targeted interventions and rehabilitation strategies for neurologically disordered patients.

Inhibitory circuits generate rhythms for leg movements during Drosophila grooming

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

Human tactile sensing and sensorimotor mechanism: from afferent tactile signals to efferent motor control

In tactile sensing, decoding the journey from afferent tactile signals to efferent motor commands is a significant challenge primarily due to the difficulty in capturing population-level afferent nerve signals during active touch. This study integrates a finite element hand model with a neural dynamic model by using microneurography data to predict neural responses based on contact biomechanics and membrane transduction dynamics. This research focuses specifically on tactile sensation and its direct translation into motor actions. Evaluations of muscle synergy during in -vivo experiments revealed transduction functions linking tactile signals and muscle activation. These functions suggest similar sensorimotor strategies for grasping influenced by object size and weight. The decoded transduction mechanism was validated by restoring human-like sensorimotor performance on a tendon-driven biomimetic hand. This research advances our understanding of translating tactile sensation into motor actions, offering valuable insights into prosthetic design, robotics, and the development of next-generation prosthetics with neuromorphic tactile feedback.

Universal optimal design in the vertebrate limb pattern and lessons for bioinspired design

This paper broadly summarizes the variation of design features found in vertebrate limbs and analyses the resultant versatility and multifunctionality in order to make recommendations for bioinspired robotics. The vertebrate limb pattern (e.g. shoulder, elbow, wrist and digits) has been proven to be very successful in many different applications in the animal kingdom. However, the actual level of optimality of the limb for each animal application is not clear because for some cases (e.g. whale flippers and bird wings), the basic skeletal layout is assumed to be highly constrained by evolutionary ancestry. This paper addresses this important and fundamental question of optimality by analysing six limbs with contrasting functions: human arm, whale flipper, bird wing, human leg, feline hindlimb and frog hindlimb. A central finding of this study is that the vertebrate limb pattern is highly versatile and optimal not just for arms and legs but also for flippers and wings. One key design feature of the vertebrate limb pattern is that of networks of segmented bones that enable smooth morphing of shapes as well as multifunctioning structures. Another key design feature is that of linkage mechanisms that fine-tune motions and mechanical advantage. A total of 52 biomechanical design features of the vertebrate limb are identified and tabulated for these applications. These tables can be a helpful reference for designers of bioinspired robotic and prosthetic limbs. The vertebrate limb has significant potential for the bioinspired design of robotic and prosthetic limbs, especially because of progress in the development of soft actuators.

Muscle Synergy Analysis as a Tool for Assessing the Effectiveness of Gait Rehabilitation Therapies: A Methodological Review and Perspective

According to the modular hypothesis for the control of movement, muscles are recruited in synergies, which capture muscle coordination in space, time, or both. In the last two decades, muscle synergy analysis has become a well-established framework in the motor control field and for the characterization of motor impairments in neurological patients. Altered modular control during a locomotion task has been often proposed as a potential quantitative metric for characterizing pathological conditions. Therefore, the purpose of this systematic review is to analyze the recent literature that used a muscle synergy analysis of neurological patients' locomotion as an indicator of motor rehabilitation therapy effectiveness, encompassing the key methodological elements to date. Searches for the relevant literature were made in Web of Science, PubMed, and Scopus. Most of the 15 full-text articles which were retrieved and included in this review identified an effect of the rehabilitation intervention on muscle synergies. However, the used experimental and methodological approaches varied across studies. Despite the scarcity of studies that investigated the effect of rehabilitation on muscle synergies, this review supports the utility of muscle synergies as a marker of the effectiveness of rehabilitative therapy and highlights the challenges and open issues that future works need to address to introduce the muscle synergies in the clinical practice and decisional process.

Neonatal resveratrol treatment in cerebral palsy model recovers neurodevelopment impairments by restoring the skeletal muscle morphology and decreases microglial activation in the cerebellum

Cerebral Palsy (CP) is the main motor disorder in childhood resulting from damage to the developing brain. Treatment perspectives are required to reverse the primary damage caused by the early insult and consequently to recover motor skills. Resveratrol has been shown to act as neuroprotection with benefits to skeletal muscle. This study aimed to investigate the effects of neonatal resveratrol treatment on neurodevelopment, skeletal muscle morphology, and cerebellar damage in CP model. Wistar rat pups were allocated to four experimental groups (n = 15/group) according CP model and treatment: Control+Saline (CS), Control+Resveratrol (CR), CP + Saline (CPS), and CP + Resveratrol (CPR). CP model associated anoxia and sensorimotor restriction. CP group showed delay in the disappearance of the palmar grasp reflex (p < 0.0001) and delay in the appearance of reflexes of negative geotaxis (p = 0.01), and free-fall righting (p < 0.0001), reduced locomotor activity and motor coordination (p < 0.05) than CS group. These motor skills impairments were associated with a reduction in muscle weight (p < 0.001) and area and perimeter of soleus end extensor digitorum longus muscle fibers (p < 0.0001), changes in muscle fibers typing pattern (p < 0.05), and the cerebellum showed signs of neuroinflammation due to elevated density and percentage of activated microglia in the CPS group compared to CS group (p < 0.05). CP animals treated with resveratrol showed anticipation of the appearance of negative geotaxis and free-fall righting reflexes (p < 0.01), increased locomotor activity (p < 0.05), recovery muscle fiber types pattern (p < 0.05), and reversal of the increase in density and the percentage of activated microglia in the cerebellum (p < 0.01). Thus, we conclude that neonatal treatment with resveratrol can contribute to the recovery of the delay neurodevelopment resulting from experimental CP due to its action in restoring the skeletal muscle morphology and reducing neuroinflammation from cerebellum.

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.

Decoding temporal muscle synergy patterns based on brain activity for upper extremity in ADL movements

Muscle synergies have been hypothesized as specific predefined motor primitives that the central nervous system can reduce the complexity of motor control by using them, but how these are expressed in brain activity is ambiguous yet. The main purpose of this paper is to develop synergy-based neural decoding of motor primitives, so for the first time, brain activity and muscle synergy map of the upper extremity was investigated in the activity of daily living movements. To find the relationship between brain activities and muscle synergies, electroencephalogram (EEG) and electromyogram (EMG) signals were acquired simultaneously during activities of daily living. To extract the maximum correlation of neural commands with muscle synergies, application of a combined partial least squares and canonical correlation analysis (PLS-CCA) method was proposed. The Elman neural network was used to decode the relationship between extracted motor commands and muscle synergies. The performance of proposed method was evaluated with tenfold cross-validation and muscle synergy estimation of brain activity with R, VAF, and MSE of 84 ± 2.6%, 70 ± 4.7%, and 0.00011 ± 0.00002 were quantified respectively. Furthermore, the similarity between actual and reconstructed muscle activations was achieved more than 92% for correlation coefficient. To compare with the existing methods, our results showed significantly more accuracy of the model performance. Our results confirm that use of the expression of muscle synergies in brain activity can estimate the neural decoding performance for motor control that can be used to develop neurorehabilitation tools such as neuroprosthesis.

Towards Human-like Walking with Biomechanical and Neuromuscular Control Features: Personalized Attachment Point Optimization Method of Cable-Driven Exoskeleton

The cable-driven exoskeleton can avoid joint misalignment, and is substantial alterations in the pattern of muscle synergy coordination, which arouse more attention in recent years to facilitate exercise for older adults and improve their overall quality of life. This study leverages principles from neuroscience and biomechanical analysis to select attachment points for cable-driven soft exoskeletons. By extracting key features of human movement, the objective is to develop a subject-specific design methodology that provides precise and personalized support in the attachment points optimization of cable-driven exoskeleton to achieve natural gait, energy efficiency, and muscle coordination controllable in the domain of human mobility and rehabilitation. To achieve this, the study first analyzes human walking experimental data and extracts biomechanical features. These features are then used to generate trajectories, allowing better natural movement under complete cable-driven exoskeleton control. Next, a genetic algorithm-based method is employed to minimize energy consumption and optimize the attachment points of the cable-driven system. This process identifies connections that are better suited for the human model, leading to improved efficiency and natural movement. By comparing the calculated elderly human model driven by exoskeleton with experimental subject in terms of joint angles, joint torques and muscle forces, the human model can successfully replicate subject movement and the cable output forces can mimic human muscle coordination. The optimized cable attachment points facilitate more natural and efficient collaboration between humans and the exoskeleton, making significant contributions to the field of assisting the elderly in rehabilitation.

Time-delay estimation in biomechanical stability: a scoping review

Despite its high-level of robustness and versatility, the human sensorimotor control system regularly encounters and manages various noises, non-linearities, uncertainties, redundancies, and delays. These delays, which are critical to biomechanical stability, occur in various parts of the system and include sensory, signal transmission, CNS processing, as well as muscle activation delays. Despite the relevance of accurate estimation and prediction of the various time delays, the current literature reflects major discrepancy with regards to existing prediction and estimation methods. This scoping review was conducted with the aim of characterizing and categorizing various approaches for estimation of physiological time delays based on PRISMA guidelines. Five data bases (EMBASE, PubMed, Scopus, IEEE and Web of Science) were consulted between the years of 2000 and 2022, with a combination of four related categories of keywords. Scientific articles estimating at least one physiological time delay, experimentally or through simulations, were included. Eventually, 46 articles were identified and analyzed with 20 quantification and 16 qualification questions by two separate reviewers. Overall, the reviewed studies, experimental and analytical, employing both linear and non-linear models, reflected heterogeneity in the definition of time delay and demonstrated high variability in experimental protocols as well as the estimation of delay values. Most of the summarized articles were classified in the high-quality category, where multiple sound analytical approaches, including optimization, regression, Kalman filter and neural network in time domain or frequency domain were used. Importantly, more than 50% of the reviewed articles did not clearly define the nature of the estimated delays. This review presents and summarizes these issues and calls for a standardization of future scientific works for estimation of physiological time-delay.

Progressive unsupervised control of myoelectric upper limbs

Objective.Unsupervised myocontrol methods aim to create control models for myoelectric prostheses while avoiding the complications of acquiring reliable, regular, and sufficient labeled training data. A limitation of current unsupervised methods is that they fix the number of controlled prosthetic functions a priori, thus requiring an initial assessment of the user's motor skills and neglecting the development of novel motor skills over time.Approach.We developed a progressive unsupervised myocontrol (PUM) paradigm in which the user and the control model coadaptively identify distinct muscle synergies, which are then used to control arbitrarily associated myocontrol functions, each corresponding to a hand or wrist movement. The interaction starts with learning a single function and the user may request additional functions after mastering the available ones, which aligns the evolution of their motor skills with an increment in system complexity. We conducted a multi-session user study to evaluate PUM and compare it against a state-of-the-art non-progressive unsupervised alternative. Two participants with congenital upper-limb differences tested PUM, while ten non-disabled control participants tested either PUM or the non-progressive baseline. All participants engaged in myoelectric control of a virtual hand and wrist.Main results.PUM enabled autonomous learning of three myocontrol functions for participants with limb differences, and of all four available functions for non-disabled subjects, using both existing or newly identified muscle synergies. Participants with limb differences achieved similar success rates to non-disabled ones on myocontrol tests, but faced greater difficulties in internalizing new motor skills and exhibited slightly inferior movement quality. The performance was comparable with either PUM or the non-progressive baseline for the group of non-disabled participants.Significance.The PUM paradigm enables users to autonomously learn to operate the myocontrol system, adapts to the users' varied preexisting motor skills, and supports the further development of those skills throughout practice.

The Study of Complex Manipulation via Kinematic Hand Synergies: The Effects of Data Pre-Processing

The study of kinematic hand synergies through matrix decomposition techniques, such as singular value decomposition, supports the theory that humans might control a subspace of predefined motions during manipulation tasks. These subspaces are often referred to as synergies. However, different data pre-processing methods lead to quantitatively different conclusions about these synergies. In this work, we shed light on the role of data pre-processing on the study of hand synergies by analyzing both numerical simulation and real kinematic data from a complex manipulation task, i.e., piano playing. The results obtained suggest that centering the data, by removing the mean, appears to be the most appropriate preprocessing technique for studying kinematic hand synergies.

Classification of gait phases based on a machine learning approach using muscle synergy

The accurate detection of the gait phase is crucial for monitoring and diagnosing neurological and musculoskeletal disorders and for the precise control of lower limb assistive devices. In studying locomotion mode identification and rehabilitation of neurological disorders, the concept of modular organization, which involves the co-activation of muscle groups to generate various motor behaviors, has proven to be useful. This study aimed to investigate whether muscle synergy features could provide a more accurate and robust classification of gait events compared to traditional features such as time-domain and wavelet features. For this purpose, eight healthy individuals participated in this study, and wireless electromyography sensors were attached to four muscles in each lower extremity to measure electromyography (EMG) signals during walking. EMG signals were segmented and labeled as 2-class (stance and swing) and 3-class (weight acceptance, single limb support, and limb advancement) gait phases. Non-negative matrix factorization (NNMF) was used to identify specific muscle groups that contribute to gait and to provide an analysis of the functional organization of the movement system. Gait phases were classified using four different machine learning algorithms: decision tree (DT), k-nearest neighbors (KNN), support vector machine (SVM), and neural network (NN). The results showed that the muscle synergy features had a better classification accuracy than the other EMG features. This finding supported the hypothesis that muscle synergy enables accurate gait phase classification. Overall, the study presents a novel approach to gait analysis and highlights the potential of muscle synergy as a tool for gait phase detection.

Epidural stimulation restores muscle synergies by modulating neural drives in participants with sensorimotor complete spinal cord injuries

Multiple studies have corroborated the restoration of volitional motor control after motor-complete spinal cord injury (SCI) through the use of epidural spinal cord stimulation (eSCS), but rigorous quantitative descriptions of muscle coordination have been lacking. Six participants with chronic, motor and sensory complete SCI underwent a brain motor control assessment (BMCA) consisting of a set of structured motor tasks with and without eSCS. We investigated how muscle activity complexity and muscle synergies changed with and without stimulation. We performed this analysis to better characterize the impact of stimulation on neuromuscular control. We also recorded data from nine healthy participants as controls. Competition exists between the task origin and neural origin hypotheses underlying muscle synergies. The ability to restore motor control with eSCS in participants with motor and sensory complete SCI allows us to test whether changes in muscle synergies reflect a neural basis in the same task. Muscle activity complexity was computed with Higuchi Fractal Dimensional (HFD) analysis, and muscle synergies were estimated using non-negative matrix factorization (NNMF) in six participants with American Spinal Injury Association (ASIA) Impairment Score (AIS) A. We found that the complexity of muscle activity was immediately reduced by eSCS in the SCI participants. We also found that over the follow-up sessions, the muscle synergy structure of the SCI participants became more defined, and the number of synergies decreased over time, indicating improved coordination between muscle groups. Lastly, we found that the muscle synergies were restored with eSCS, supporting the neural hypothesis of muscle synergies. We conclude that eSCS restores muscle movements and muscle synergies that are distinct from those of healthy, able-bodied controls.

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.

Effects of Bilateral Extracephalic Transcranial Direct Current Stimulation on Lower Limb Kinetics in Countermovement Jumps

OBJECTIVE

Transcranial direct current stimulation (tDCS) is an effective method for improving sports/exercise performance in humans. However, studies examining the effects of tDCS on jumping performance have reported inconsistent findings, and there is a paucity of studies investigating the effects of tDCS on lower limb energy and kinetics in countermovement jumps (CMJs). Thus, we investigated the effects of tDCS on countermovement jump (CMJ) performance and analysed kinetic variations in the ankle, knee, and hip joints.

METHODS

In total, 15 healthy young participants randomly received anodal or sham bilateral stimulation of the primary motor cortex (M1). The bilateral tDCS (Bi-tDCS) montage used an intensity of 2 mA for a 20 min monophasic continuous current. Jump height, energy, and lower limb kinetic data in CMJs were collected at pre-stimulation (Pre), post-0 min (Post-0), and post-30 min (Post-30) using a motion capture system and two 3D force plates. Jump height, lower extremity energy, and kinetic variables in CMJs were analysed with two-way repeated-measures ANOVA.

RESULTS

(1) Compared to the baseline and sham conditions, the jump height increased except that at Post-30 relative to the sham condition, and the total net energy of lower limbs increased at Post-30 relative to the baseline. (2) Compared to the baseline, the ankle positive energy and net energy decreased in the sham condition; Compared to the baseline and values at Post-0, the maximum ankle torque at Post-30 decreased in both stimulation conditions. (3) The maximum knee power increased compared to the baseline and sham conditions. (4) Regardless of time points, the maximum hip torque in the tDCS condition was higher than it was in the sham condition.

CONCLUSION

Bi-tDCS is an effective method for improving jump height by modulating ankle and knee net energy. The net energy improvement of the lower extremities may be due to variation in the kinetic chain resulting from tDCS-enhanced knee exploration force and maximum hip strength in CMJs. The effects of Bi-tDCS gradually decrease.

Applying muscle synergy analysis to forearm high-density electromyography of healthy people

Introduction

Muscle synergy is regarded as a motor control strategy deployed by the central nervous system (CNS). Clarifying the modulation of muscle synergies under different strength training modes is important for the rehabilitation of motor-impaired patients.

Methods

To represent the subtle variation of neuromuscular activities from the smaller forearm muscles during wrist motion, we proposed to apply muscle synergy analysis to preprocessed high-density electromyographic data (HDEMG). Here, modulation of muscle synergies within and across the isometric and isotonic training modes for strengthening muscles across the wrist were investigated. Surface HDEMGs were recorded from healthy subjects (N = 10). Three different HDEMG electrode configurations were used for comparison and validation of the extracted muscle synergies. The cosine of principal angles (CPA) and the Euclidian distance (ED) between synergy vectors were used to evaluate the intra- and inter-mode similarity of muscle synergies. Then, how the activation coefficients modulate the excitation of specific synergy under each mode was examined by pattern recognition. Next, for a closer look at the mode-specific synergies and the synergies shared by the two training modes, k-means clustering was applied.

Results

We observed high similarity of muscle synergies across different tasks within each training mode, but decreased similarity of muscle synergies across different training modes. Both intra- and intermode similarity of muscle synergies were consistently robust to electrode configurations regardless of the similarity metric used.

Discussion

Overall, our findings suggest that applying muscle synergy analysis to HDEMG is feasible, and that the traditional muscle synergies defined by whole-muscle components may be broadened to include sub-muscle components represented by the HDEMG channels. This work may lead to an appropriate neuromuscular analysis method for motor function evaluation in clinical settings and provide valuable insights for the prescription of rehabilitation training therapies.

Design of an Isometric End-Point Force Control Task for Electromyography Normalization and Muscle Synergy Extraction From the Upper Limb Without Maximum Voluntary Contraction

Muscle synergy analysis via surface electromyography (EMG) is useful to study muscle coordination in motor learning, clinical diagnosis, and neurorehabilitation. However, current methods to extract muscle synergies in the upper limb suffer from two major issues. First, the necessary normalization of EMG signals is performed via maximum voluntary contraction (MVC), which requires maximal isometric force production in each muscle. However, some individuals with motor impairments have difficulties producing maximal effort in the MVC task. In addition, the MVC is known to be highly unreliable, with widely different forces produced in repeated measures. Second, synergy extraction in the upper limb is typically performed with a multidirection reaching task. However, some participants with motor impairments cannot perform this task because it requires precise motor control. In this study, we proposed a new isometric rotating task that does not require precise motor control or large forces. In this task, participants maintain a cursor controlled by the arm end-point force on a target that rotates at a constant angular velocity at a designated force level. To relax constraints on motor control precision, the target is widened and blurred. To obtain a reference EMG value for normalization without requiring maximal effort, we estimated a linear relationship between joint torques and muscle activations. We assessed the reliability of joint torque normalization and synergy extraction in the rotating task in young neurotypical individuals. Compared with normalization with MVC, joint torque normalization allowed reliable EMG normalization at low force levels. In addition, the extraction of synergies was as reliable and more stable than with the multidirection reaching task. The proposed rotating task can, therefore, be used in future motor learning, clinical diagnosis, and neurorehabilitation studies.

Temporal Synergies Detection in Gait Cyclograms Using Wearable Technology

The human gait can be described as the synergistic activity of all individual components of the sensory–motor system. The central nervous system (CNS) develops synergies to execute endpoint motion by coordinating muscle activity to reflect the global goals of the endpoint trajectory. This paper proposes a new method for assessing temporal dynamic synergies. Principal component analysis (PCA) has been applied on the signals acquired by wearable sensors (inertial measurement units, IMU and ground reaction force sensors, GRF mounted on feet) to detect temporal synergies in the space of two-dimensional PCA cyclograms. The temporal synergy results for different gait speeds in healthy subjects and stroke patients before and after the therapy were compared. The hypothesis of invariant temporal synergies at different gait velocities was statistically confirmed, without the need to record and analyze muscle activity. A significant difference in temporal synergies was noticed in hemiplegic gait compared to healthy gait. Finally, the proposed PCA-based cyclogram method provided the therapy follow-up information about paretic leg gait in stroke patients that was not available by observing conventional parameters, such as temporal and symmetry gait measures.

Modification of Hand Muscular Synergies in Stroke Patients after Robot-Aided Rehabilitation

The central nervous system (CNS) is able to control a very high number of degrees of freedom to perform complex movements of both upper and lower limbs. However, what strategies the CNS adopts to perform complex tasks are not completely clear and are still being studied. Recent studies confirm that stroke subjects with mild and moderate impairment show altered upper limb muscle patterns, but the muscular patterns of the hand have not completely investigated, although the hand represents a paramount tool for performing activities of daily living (ADLs) and stroke can significantly alter the mobilization of this part of the body. In this context, this study aims at investigating hand muscular synergies in chronic stroke patients and evaluating some possible benefits in the robot-aided rehabilitation treatment of the hand in these subjects. Seven chronic stroke patients with mild-to-moderate impairment (FM>30) were involved in this study. They received a 5-week robot-aided rehabilitation treatment with the Gloreha hand exoskeleton, and muscle synergies of both the healthy and injured hand were evaluated at the beginning and at the end of the treatment. The performed analysis showed a very high degree of similarity of the involved synergies between the healthy and the injured limb both before and after the rehabilitation treatment (mean similarity index values: H-BR: 0.88±0.03, H-AR: 0.94±0.03, BR-AR: 0.89±0.05). The increasing similarity is regarded as an effect of the robot-aided rehabilitation treatment and future activities will be performed to increase the population involved in the study.

The Effect of Core Stabilization Exercise with the Abdominal Drawing-in Maneuver Technique on Stature Change during Prolonged Sitting in Sedentary Workers with Chronic Low Back Pain

To enhance stature recovery, lumbar spine stabilization by stimulating the deep trunk muscle activation for compensation forces originating from the upper body was introduced. The abdominal drawing-in maneuver (ADIM) technique has been found mainly to activate deep trunk muscles. The purpose of the current study was to determine whether 5 weeks of training of deep trunk muscles using the ADIM technique could improve stature recovery, delay trunk muscle fatigue, and decrease pain intensity during prolonged sitting. Thirty participants with chronic low back pain (CLBP) conducted a core stabilization exercise (CSE) with the ADIM technique for 5 weeks. Participants were required to sit for 41 min before and after the exercise intervention. Stature change was measured using a seated stadiometer with a resolution of ±0.006 mm. During sitting, the stature change, pain intensity, and trunk muscle fatigue were recorded. A comparison between measurements at baseline and after 5 weeks of training demonstrated: (i) stature recovery and pain intensity significantly improved throughout the 41 min sitting condition; (ii) the bilaterally trunk muscle showed significantly decreased fatigue. The CSE with the ADIM technique was shown to provide a protective effect on detrimental reductions in stature change and trunk muscle fatigue during prolonged sitting in young participants under controlled conditions in a laboratory. This information may help to prevent the risk of LBP from prolonged sitting activities in real life situations.

Organic Electrochemical Transistors for In Vivo Bioelectronics

Organic electrochemical transistors (OECTs) are presently a focus of intense research and hold great potential in expanding the horizons of the bioelectronics industry. The notable characteristics of OECTs, including their electrolyte-gating, which offers intimate interfacing with biological environments, and aqueous stability, make them particularly suitable to be operated within a living organism (in vivo). Unlike the existing in vivo bioelectronic devices, mostly based on rigid metal electrodes, OECTs form a soft mechanical contact with the biological milieu and ensure a high signal-to-noise ratio because of their powerful amplification capability. Such features make OECTs particularly desirable for a wide range of in vivo applications, including electrophysiological recordings, neuron stimulation, and neurotransmitter detection, and regulation of plant processes in vivo. In this review, a systematic compilation of the in vivo applications is presented that are addressed by the OECT technology. First, the operating mechanisms, and the device design and materials design principles of OECTs are examined, and then multiple examples are provided from the literature while identifying the unique device properties that enable the application progress. Finally, one critically looks at the future of the OECT technology for in vivo bioelectronic applications.

Muscle Synergies and Clinical Outcome Measures Describe Different Factors of Upper Limb Motor Function in Stroke Survivors Undergoing Rehabilitation in a Virtual Reality Environment

Recent studies have investigated muscle synergies as biomarkers for stroke, but it remains controversial if muscle synergies and clinical observation convey the same information on motor impairment. We aim to identify whether muscle synergies and clinical scales convey the same information or not. Post-stroke patients were administered an upper limb treatment. Before (T0) and after (T1) treatment, we assessed motor performance with clinical scales and motor output with EMG-derived muscle synergies. We implemented an exploratory factor analysis (EFA) and a confirmatory factor analysis (CFA) to identify the underlying relationships among all variables, at T0 and T1, and a general linear regression model to infer any relationships between the similarity between the affected and unaffected synergies (Median-sp) and clinical outcomes at T0. Clinical variables improved with rehabilitation whereas muscle-synergy parameters did not show any significant change. EFA and CFA showed that clinical variables and muscle-synergy parameters (except Median-sp) were grouped into different factors. Regression model showed that Median-sp could be well predicted by clinical scales. The information underlying clinical scales and muscle synergies are therefore different. However, clinical scales well predicted the similarity between the affected and unaffected synergies. Our results may have implications on personalizing rehabilitation protocols.

Effects of Force Modulation on Large Muscles during Human Cycling

Voluntary force modulation is defined as the ability to tune the application of force during motion. However, the mechanisms behind this modulation are not yet fully understood. In this study, we examine muscle activity under various resistance levels at a fixed cycling speed. The main goal of this research is to identify significant changes in muscle activation related to the real-time tuning of muscle force. This work revealed significant motor adaptations of the main muscles utilized in cycling as well as positive associations between the force level and the temporal and spatial inter-cycle stability in the distribution of sEMG activity. From these results, relevant biomarkers of motor adaptation could be extracted for application in clinical rehabilitation to increase the efficacy of physical therapy.

Muscle synergies in archery: an explorative study on experienced athletes with and without physical disability. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021;2021:6220-6223. [PMID: 34892536 DOI: 10.1109/embc46164.2021.9630307]

Archery technique requires a coordinated activation of shoulder girdle and upper extremity muscles to perform a successful shot. The analysis of muscle synergies can provide information about the motor strategy that underlies the shooting performance, also supporting the investigation of motor impairments in athletes with disability. For this purpose, electromyographic (EMG) data from five muscles were collected from a non-disabled and a W1 category Paralympic athlete, and muscle synergies were extracted from EMG envelopes using non-negative matrix factorization. Muscle synergies analysis revealed features of the motor strategy specific to the athletes' shooting technique, such as the contribution of the biceps muscle instead of the posterior deltoid during the arrow drawing and target aiming in the Paralympic athlete compared to the non-disabled athlete. It is concluded that the evaluation of the muscle synergies may be a valuable tool for exploring the motor strategies adopted by athletes with disability, providing useful information to improve athletic performance and possibly prevent the risk of injury.

A Perspective on Muscle Synergies and Different Theories Related to Their Adaptation

The human motor system is a complex neuro-musculo sensory system that needs further investigations of neuro-muscular commands and sensory-motor coupling to decode movement execution. Some researchers suggest that the central nervous system (CNS) activates a small set of modules termed muscle synergies to simplify motor control. Further, these modules form functional building blocks of movement as they can explain the neurophysiological characteristics of movements. We can identify and extract these muscle synergies from electromyographic signals (EMG) recorded in the laboratory by using linear decomposition algorithms, such as principal component analysis (PCA) and non-Negative Matrix Factorization Algorithm (NNMF). For the past three decades, the hypothesis of muscle synergies has received considerable attention as we attempt to understand and apply the concept of muscle synergies in clinical settings and rehabilitation. In this article, we first explore the concept of muscle synergies. We then present different strategies of adaptation in these synergies that the CNS employs to accomplish a movement goal.

The Muscle Activation Differences in Post-Stroke Upper Limb Flexion Synergy Based on Spinal Cord Segments: A Preliminary Proof-of-Concept Study

Objective: This study examined the activation difference of muscles innervated by cervical cord 5-6 (C5-C6) and cervical cord 8- thoracic cord 1 (C8-T1) in upper limb flexion synergy after stroke.

Methods: Surface electromyography (sEMG) signals were collected during elbow flexion in stroke patients and healthy controls. The study compared normalized activation of two pairs of muscles that could cause similar joint movement but which dominated different spinal cord segments (clavicular part of the pectoralis major, PC vs. Sternocostal part of the pectoralis major, PS; Flexor carpi radialis, FCR vs. Flexor carpi ulnaris, FCU). In each muscle pair, one muscle was innervated by the same spinal cord segment (C5-C6), dominating the elbow flexion and the other was not. The comparison of the activation of the same muscle between patients and healthy controls was undertaken after standardization based on the activation of the biceps brachii in elbow flexion.

Results: There was no difference between the PC and PS's normalized activation in healthy controls while the PC's normalized activation was higher than PS in stroke patients during elbow flexion. Similarly, there was no significant difference in normalized activation between FCR and FCU in healthy controls, and the same is true for stroke patients. However, the standardized activation of both FCR and FCU in stroke patients was significantly lower than that in healthy controls.

Conclusion: After stroke, the activation of the distal muscles of the upper limb decreased significantly regardless of the difference of spinal cord segments; while the activation of the proximal muscles innervated by the same spinal cord segment (C5-C6) dominating the elbow flexion showed higher activation during flexion synergy. The difference in muscle activation based on spinal cord segments may be the reason for the stereotyped joint movement of upper limb flexion synergy.

Investigation of Power Specific Motor Primitives in an Upper Limb Rotational Motion

The purpose of this study was to investigate muscle synergies (MS) during upper limb cycling motion across power levels (20, 40, 60, 80, 100, and 120 watts). The MS hypothesis is important to the understanding of modular control for human movements. In this study, we explore its importance in execution of phasic movements at various power levels. Electromyographic (EMG) signals were recorded from 7 upper limb muscles during cycling for 30s on a hand-cycle ergometer. A Non-Negative Matrix factorization (NNMF) algorithm was used to extract MS. Cosine similarity was used to compare the MS and cross-correlation was used to compare activation coefficients. We found that the number and structure of synergies were consistent across power levels while admitting modulation in their activation coefficients. A total of three shared MS explaining ≥95% of the variance accounted for (VAF) represented push and pull mechanism during cyclic motion.

Temporal control of muscle synergies is linked with alpha-band neural drive

KEY POINTS

It is theorized that the nervous system controls groups of muscles together as functional units, or 'synergies', resulting in correlated electromyographic (EMG) signals among muscles. However, such correlation does not necessarily imply group-level neural control. Oscillatory synchronization (coherence) among EMG signals implies neural coupling, but it is not clear how this relates to control of muscle synergies. EMG was recorded from seven arm muscles of 10 adult participants rotating an upper limb ergometer, and EMG-EMG coherence, EMG amplitude correlations and their relationship with each other were characterized. A novel method to derive multi-muscle synergies from EMG-EMG coherence is presented and these are compared with classically defined synergies. Coherent alpha-band (8-16 Hz) drive was strongest among muscles whose gross activity levels are well correlated within a given task. The cross-muscle distribution and temporal modulation of coherent alpha-band drive suggests a possible role in the neural coordination/monitoring of synergies.

ABSTRACT

During movement, groups of muscles may be controlled together by the nervous system as an adaptable functional entity, or 'synergy'. The rules governing when (or if) this occurs during voluntary behaviour in humans are not well understood, at least in part because synergies are usually defined by correlated patterns of muscle activity without regard for the underlying structure of their neural control. In this study, we investigated the extent to which comodulation of muscle output (i.e. correlation of electromyographic (EMG) amplitudes) implies that muscles share intermuscular neural input (assessed via EMG-EMG coherence analysis). We first examined this relationship among pairs of upper limb muscles engaged in an arm cycling task. We then applied a novel multidimensional EMG-EMG coherence analysis allowing synergies to be characterized on the basis of shared neural drive. We found that alpha-band coherence (8-16 Hz) is related to the degree to which overall muscle activity levels correlate over time. The extension of this coherence analysis to describe the cross-muscle distribution and temporal modulation of alpha-band drive revealed a close match to the temporal and structural features of traditionally defined muscle synergies. Interestingly, the coherence-derived neural drive was inversely associated with, and preceded, changes in EMG amplitudes by ∼200 ms. Our novel characterization of how alpha-band neural drive is dynamically distributed among muscles is a fundamental step forward in understanding the neural origins and correlates of muscle synergies.

Muscle Synergies in Children Walking and Running on a Treadmill

Muscle synergies reflect the presence of a common neural input to multiple muscles. Steering small sets of synergies is commonly believed to simplify the control of complex motor tasks like walking and running. When these locomotor patterns emerge, it is likely that synergies emerge as well. We hence hypothesized that in children learning to run the number of accompanying synergies increases and that some of the synergies' activities display a temporal shift related to a reduced stance phase as observed in adults. We investigated the development of locomotion in 23 children aged 2-9 years of age and compared them with seven young adults. Muscle activity of 15 bilateral leg, trunk, and arm muscles, ground reaction forces, and kinematics were recorded during comfortable treadmill walking and running, followed by a muscle synergy analysis. We found that toddlers (2-3.5 years) and preschoolers (3.5-6.5 years) utilize a "walk-run strategy" when learning to run: they managed the fastest speeds on the treadmill by combining double support (DS) and flight phases (FPs). In particular the activity duration of the medial gastrocnemius muscle was weakly correlated with age. The number of synergies across groups and conditions needed to cover sufficient data variation ranged between four and eight. The number of synergies tended to be smaller in toddlers than it did in preschoolers and school-age children but the adults had the lowest number for both conditions. Against our expectations, the age groups did not differ significantly in the timing or duration of synergies. We believe that the increase in the number of muscle synergies in older children relates to motor learning and exploration. The ability to run with a FP is clearly associated with an increase in the number of muscle synergies.

Relationship between gait quality measures and modular neuromuscular control parameters in chronic post-stroke individuals

Background

Recent evidence suggests that disinhibition and/or hyperexcitation of the brainstem descending pathways and intraspinal motor network diffuse spastic synergistic activation patterns after stroke. This results in simplified or merged muscle sets (i.e., muscle modules or synergies) compared to non-impaired individuals and this leads to poor walking performance. However, the relations of how these neuromuscular deficits influence gait quality (e.g., symmetry or natural walking patterns) are still unclear. The objective of this exploratory study was to investigate the relations of modular neuromuscular framework and gait quality measures in chronic stroke individuals.

Methods

Sixteen chronic post-stroke individuals participated in this study. Full lower body three-dimensional kinematics and electromyography (EMG) were concurrently measured during overground walking at a comfortable speed. We first examined changes in gait quality measures across the number of muscle modules using linear regression model. Then, a stepwise multiple regression was used to investigate the optimal combination of the neuromuscular parameters that associates with gait quality measures.

Results

We observed that subjects who had a lower number of muscle modules revealed reduced function (i.e., speed) and greater asymmetry in the kinematic parameters including limb length, footpath area, knee flexion/extension, and hip abduction/adduction (all p < 0.05). We also found that the combination of input variables from the modular neuromuscular control framework significantly associated with gait quality measures (average \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${R}^{2}=42.5\mathrm{\%}$$\end{document}R2=42.5%). Those variables included variability accounted for (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$VAF$$\end{document}VAF) information from the muscle modules and area under the EMG envelope curves of the quadriceps (i.e., rectus femoris and vastus lateralis) and tibialis anterior muscles.

Conclusions

The results suggest that there exists a significant correlation between the neuromuscular control framework and the gait quality measures. This study helps to understand the underlying mechanism of disturbances in gait quality and provides insight for a more comprehensive outcome measure to assess gait impairment after stroke.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12984-021-00860-0.

Effects of Varying Overground Walking Speeds on Lower-Extremity Muscle Synergies in Healthy Individuals

The effects of walking speeds on lower-extremity muscle synergies (MSs) were investigated among 20 adults who walked 20 m at SLOW (0.6 ± 0.2 m/s), natural (NAT; 1.4 ± 0.1 m/s), and FAST (1.9 ± 0.1 m/s) speeds. Surface electromyography of eight lower-extremity muscles was recorded before extracting MSs using a nonnegative matrix factorization algorithm. Increasing walking speed tended to merge MSs associated with weight acceptance and limb deceleration, whereas reducing walking speed does not change the number and composition of MSs. Varying gait speed, particularly decreasing speed, may represent a gait training strategy needing additional attention given its effects on MSs.

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.

Surface Electromyography Meets Biomechanics: Correct Interpretation of sEMG-Signals in Neuro-Rehabilitation Needs Biomechanical Input

Coordinated activation of muscles is the basis for human locomotion. Impaired muscular activation is related to poor movement performance and disability. To restore movement performance, information about the subject's individual muscular activation is of high relevance. Surface electromyography (sEMG) allows the pain-free assessment of muscular activation and many ready-to-use technologies are available. They enable the usage of sEMG measurements in several applications. However, due to the fact that in most rehabilitation applications dynamic conditions are analyzed, the correct interpretation of sEMG signals remains difficult which hinders the spread of sEMG in clinical applications. From biomechanics it is well-known that the sEMG signal depends on muscle fiber length, contraction velocity, contraction type and on the muscle's biomechanical moment. In non-isometric conditions these biomechanical factors have to be considered when analyzing sEMG signals. Additionally, the central nervous system control strategies used to activate synergistic and antagonistic muscles have to be taken into consideration. These central nervous system activation strategies are rarely known in physiology and are hard to manage in pathology. In this perspective report we discuss how the consideration of biomechanical factors leads to more reliable information extraction from sEMG signals and how the limitations of sEMG can be overcome in dynamic conditions. This is a prerequisite if the use of sEMG in rehabilitation applications is to extend. Examples will be given showing how the integration of biomechanical knowledge into the interpretation of sEMG helps to identify the central nervous system activation strategies involved and leads to relevant clinical information.

Muscle Synergies Reliability in the Power Clean Exercise

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

Surface EMG in Clinical Assessment and Neurorehabilitation: Barriers Limiting Its Use

This article addresses the potential clinical value of techniques based on surface electromyography (sEMG) in rehabilitation medicine with specific focus on neurorehabilitation. Applications in exercise and sport pathophysiology, in movement analysis, in ergonomics and occupational medicine, and in a number of related fields are also considered. The contrast between the extensive scientific literature in these fields and the limited clinical applications is discussed. The "barriers" between research findings and their application are very broad, and are longstanding, cultural, educational, and technical. Cultural barriers relate to the general acceptance and use of the concept of objective measurement in a clinical setting and its role in promoting Evidence Based Medicine. Wide differences between countries exist in appropriate training in the use of such quantitative measurements in general, and in electrical measurements in particular. These differences are manifest in training programs, in degrees granted, and in academic/research career opportunities. Educational barriers are related to the background in mathematics and physics for rehabilitation clinicians, leading to insufficient basic concepts of signal interpretation, as well as to the lack of a common language with rehabilitation engineers. Technical barriers are being overcome progressively, but progress is still impacted by the lack of user-friendly equipment, insufficient market demand, gadget-like devices, relatively high equipment price and a pervasive lack of interest by manufacturers. Despite the recommendations provided by the 20-year old EU project on "Surface EMG for Non-Invasive Assessment of Muscles (SENIAM)," real international standards are still missing and there is minimal international pressure for developing and applying such standards. The need for change in training and teaching is increasingly felt in the academic world, but is much less perceived in the health delivery system and clinical environments. The rapid technological progress in the fields of sensor and measurement technology (including sEMG), assistive devices, and robotic rehabilitation, has not been driven by clinical demands. Our assertion is that the most important and urgent interventions concern enhanced education, more effective technology transfer, and increased academic opportunities for physiotherapists, occupational therapists, and kinesiologists.

Improved Gait of Persons With Multiple Sclerosis After Rehabilitation: Effects on Lower Limb Muscle Synergies, Push-Off, and Toe-Clearance

Introduction: Persons with MS (PwMS) have markedly reduced push-off and toe-clearance during gait compared to healthy subjects (HS). These deficits may result from alterations in neuromotor control at the ankle. To optimize rehabilitation interventions for PwMS, a crucial step is to evaluate if and how altered neuromotor control, as represented by muscle synergies, improves with rehabilitation. In this study we investigated changes in ankle motor control and associated biomechanical parameters during gait in PwMS, occurring with increase in speed after gait rehabilitation. Methods: 3D motion and EMG data were collected while 11 PwMS (age 50.3 + 11.1; EDSS 5.2 + 1.2) walked overground at self-selected speed before (T0) and after 20 sessions (T1) of intensive treadmill training. Muscle synergies were extracted using non-negative matrix factorization. Gait parameters were computed according to the LAMB protocol. Pearson's correlation coefficient was used to evaluate the similarity of motor modules between PwMS and HS. To assess differences in distal module activations representing neuromotor control at the ankle [Forward Propulsion (FPM) and Ground Clearance modules (GCM)], each module's activation timing was integrated over 100% of the gait cycle and the activation percentage index (API) was computed in six phases. Ten age matched HS provided two separate speed-matched normative datasets for T0 and T1. For speed independent comparison for the PwMs Z scores were calculated for all their gait variables. Results: In PwMS velocity increased significantly from T0 to T1 (0.74-0.90 m/s, p < 0.05). The activation profiles (API) of FPM and GCM of PwMS improved in pre-swing (p < 0.05): FPM (Mean [95% CI] [%]: T0: 12.5 [5.7-19.3] vs. T1: 9.0 [2.7-15.3]); GCM (T0: 26.7 [18.2-35.3] vs. T1: 24.5 [18.2-30.7]). This was associated with an increase in toe clearance (80.3 to 103.6 mm, p < 0.05) and a higher ankle power peak in pre-swing (1.53-1.93 W/kg, p < 0.05). Conclusion: Increased gait speed of PwMS after intensive gait training was consistent with improvements in spatio-temporal gait parameters. The most important finding of this study was the re-organization of distal leg modules related to neurophysiological changes induced by rehabilitation. This was associated with an improved ankle performance.

Automatic Myoelectric Control Site Detection Using Candid Covariance-Free Incremental Principal Component Analysis

The unknown composition of residual muscles surrounding the stump of an amputee makes optimal electrode placement challenging. This often causes the experimental set-up and calibration of upper-limb prostheses to be time consuming. In this work, we propose the use of existing dimensionality reduction techniques, typically used for muscle synergy analysis, to provide meaningful real-time functional information of the residual muscles during the calibration period. Two variations of principal component analysis (PCA) were applied to electromyography (EMG) data collected during a myoelectric task. Candid covariance-free incremental PCA (CCIPCA) detected task-specific muscle synergies with high accuracy using minimal amounts of data. Our findings offer a real-time solution towards optimizing calibration periods.

Muscle Synergies in Parkinson's Disease

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

Effects of robotic exoskeleton control options on lower limb muscle synergies during overground walking: An exploratory study among able-bodied adults

BACKGROUND

The effects of lower limb (L/L) control options, developed for overground walking with a wearable robotic exoskeleton (WRE), on the neuromotor control of L/L muscles [i.e., muscle synergies (MSs)] during walking remain uncertain.

OBJECTIVE

To gain initial insights regarding the effects of different control options on the number of MSs at the L/L and on their muscle weighting within each MS when walking with a WRE.

METHODS

Twenty able-bodied adults walked overground without and with the WRE set at two control options with a predetermined foot pathway imposed by the WRE, and at three other control options with free L/L kinematics in the sagittal plane. Surface electromyography of eight right L/L muscles was recorded. MSs were extracted using a non-negative matrix factorisation algorithm. Cosine similarity and correlation coefficients characterised similarities between the MSs characteristics.

RESULTS

Freely moving the L/L in the sagittal plane (i.e., non-trajectory controlled options) during WRE walking best duplicated typical MSs extracted when walking without WRE. Conversely, WRE walking while fully controlling the L/L trajectory presented the lowest correlations to all MSs extracted when walking without WRE, especially during early swing and L/L deceleration.

CONCLUSION

Neuromotor control of L/L muscles is affected by the selected control option during WRE walking, particularly when a predetermined foot pathway is imposed.

SIGNIFICANCE

This exploratory study represents the first step in informing the decision-making process regarding the use of different L/L control options when using WRE and calls for further research among adults with sensorimotor impairments.

Characterization of Forearm Muscle Activation in Duchenne Muscular Dystrophy via High-Density Electromyography: A Case Study on the Implications for Myoelectric Control

Duchenne muscular dystrophy (DMD) is a genetic disorder that results in progressive muscular degeneration. Although medical advances increased their life expectancy, DMD individuals are still highly dependent on caregivers. Hand/wrist function is central for providing independence, and robotic exoskeletons are good candidates for effectively compensating for deteriorating functionality. Robotic hand exoskeletons require the accurate decoding of motor intention typically via surface electromyography (sEMG). Traditional low-density sEMG was used in the past to explore the muscular activations of individuals with DMD; however, it cannot provide high spatial resolution. This study characterized, for the first time, the forearm high-density (HD) electromyograms of three individuals with DMD while performing seven hand/wrist-related tasks and compared them to eight healthy individuals (all data available online). We looked into the spatial distribution of HD-sEMG patterns by using principal component analysis (PCA) and also assessed the repeatability and the amplitude distributions of muscle activity. Additionally, we used a machine learning approach to assess DMD individuals' potentials for myocontrol. Our analysis showed that although participants with DMD were able to repeat similar HD-sEMG patterns across gestures (similarly to healthy participants), a fewer number of electrodes was activated during their gestures compared to the healthy participants. Additionally, participants with DMD activated their muscles close to maximal contraction level (0.63 ± 0.23), whereas healthy participants had lower normalized activations (0.26 ± 0.2). Lastly, participants with DMD showed on average fewer PCs (3), explaining 90% of the complete gesture space than the healthy (5). However, the ability of the DMD participants to produce repeatable HD-sEMG patterns was unexpectedly comparable to that of healthy participants, and the same holds true for their offline myocontrol performance, disproving our hypothesis and suggesting a clear potential for the myocontrol of wearable exoskeletons. Our findings present evidence for the first time on how DMD leads to progressive alterations in hand/wrist motor control in DMD individuals compared to healthy. The better understanding of these alterations can lead to further developments for the intuitive and robust myoelectric control of active hand exoskeletons for individuals with DMD.

On Primitives in Motor Control

The concept of primitives has been used in motor control both as a theoretical construct and as a means of describing the results of experimental studies involving multiple moving elements. This concept is close to Bernstein’s notion of engrams and level of synergies. Performance primitives have been explored in spaces of peripheral variables but interpreted in terms of neural control primitives. Performance primitives reflect a variety of mechanisms ranging from body mechanics to spinal mechanisms and to supraspinal circuitry. This review suggests that primitives originate at the task level as preferred time functions of spatial referent coordinates or at mappings from higher level referent coordinates to lower level, frequently abundant, referent coordinate sets. Different patterns of performance primitives can emerge depending, in particular, on the external force field.

Flow as an Embodied State. Informed Awareness of Slackline Walking

Flow during exercise has been theorized and studied solely through subjective-retrospective methods as a “scull bound” construct. Recent advances of the radical embodied perspectives on conscious mind and cognition pose challenges to such understanding, particularly because flow during exercise is associated with properties of performer’s movement behavior. In this paper we use the concept of informed awareness to reconceptualize flow experience as a property of the performer-environment coupling, and study it during a slackline walking task. To empirically check the possible relatedness of the behavior-experience complementary pair, two measures were considered. The experiential realm was quantified by the flow short scale and the behavioral realm by the Hurst (H) exponent obtained through accelerometry time series of the legs and the center of body mass (CoM). In order to obtain a coarse-grained insight about the degree of co-varying within the perception-action flow of performers, we conducted correlational and multiple regression analyses. Measures of behavioral variables (H exponents of the dominant, subdominant leg and the CoM, were treated as explanatory, and the flow scale and its subscale (fluency of movements and absorption) scores asresponse variables containing summarized information about perceptual experiences of performers. In order to check for possible mediating or confounding effects of training parameters on the action-perception variables’ covariance, we included two additional variables which measured the degree of engagement of participants with the task. Results revealed that the temporal structure of fluctuations of the dominant leg, as measured by the Hurst exponent, was a strong mediator of effects of training variables and the subdominant leg fluctuations, on the flow scale and the subscale scores. The magnitude of Hurst exponents of both legs was informative about the degree of stability within the performer-environment system. The degree of critical slowing down, as measured by Hurst exponents, consistently co-varied with the flow scale and subscales. The experience of flow during the slackline walking task was dominantly saturated by the perceived fluency of movements and less so by the absorption experience. The stable co-variance of perception-action variables signified the embodied nature of the flow experience.

Comparative Analysis of Wearable A-Mode Ultrasound and sEMG for Muscle-Computer Interface

OBJECTIVE

While surface electromyography (sEMG) is still dominant in the field of muscle-computer interface, ultrasound (US) sensing has been regarded as a promising alternative to sEMG, owing to its ability to precisely monitor muscle deformations. Among different US modalities, A-mode US is more compact and cost-effective for wearable applications against its cumbersome B-mode counterpart. In this article, we conduct a comprehensive comparison of wearable A-mode US and sEMG on gesture recognition and isometric muscle contraction force estimation.

METHODS

We experimented with eight types of gesture, with a range of 0-60% maximum voluntary contraction for each motion.

RESULTS

Results show that A-mode US outperforms sEMG on gesture recognition accuracy, robustness, and discrete force estimation accuracy, while sEMG is superior to US on continuous force estimation accuracy and ease of use in force estimation. Moreover, an extended online experiment demonstrates that the complementary advantages of US and sEMG on gesture recognition and continuous force estimation can be combined for the achievement of multi-class proportional gesture control.

SIGNIFICANCE

This article demonstrates the potential of A-mode US in automated gesture recognition, and the prospect of sEMG/US fusion for proportional gesture interaction.

Modular Organization of Muscle Synergies to Achieve Movement Behaviors

Muscle synergy has been applied to comprehend how the central nervous system (CNS) controls movements for decades. However, it is not clear about the motion control mechanism and the relationship between motions and muscle synergies. In this paper, we designed two experiments to corroborate the hypothesis: (1) motions can be decomposed to motion primitives, which are driven by muscle synergy primitives and (2) variations of motion primitives in direction and scale are modulated by activation coefficients rather than muscle synergy primitives. Surface electromyographic (EMG) signals were recorded from nine muscles of the upper limb. Nonnegative matrix factorization (NMF) was applied to extract muscle synergy vectors and corresponding activation coefficients. We found that synergy structures of different movement patterns were similar (α=0.05). The motion modulation indexes (MMI) among movement patterns in reaching movements showed apparent differences. Merging coefficients and reconstructed similarity of synergies between simple motions and complex motions were significant. This study revealed the motion control mechanism of the CNS and provided a rehabilitation and evaluation method for patients with motor dysfunction in exercise and neuroscience.

Paving the way for a better understanding of the pathophysiology of gait impairment in myotonic dystrophy: a pilot study focusing on muscle networks

BACKGROUND

A proper rehabilitation program targeting gait is mandatory to maintain the quality of life of patients with Myotonic dystrophy type 1 (DM1). Assuming that gait and balance impairment simply depend on the degree of muscle weakness is potentially misleading. In fact, the involvement of the Central Nervous System (CNS) in DM1 pathophysiology calls into account the deterioration of muscle coordination in gait impairment. Our study aimed at demonstrating the presence and role of muscle connectivity deterioration in patients with DM1 by a CNS perspective by investigating signal synergies using a time-frequency spectral coherence and multivariate analyses on lower limb muscles while walking upright. Further, we sought at determining whether muscle networks were abnormal secondarily to the muscle impairment or primarily to CNS damage (as DM1 is a multi-system disorder also involving the CNS). In other words, muscle network deterioration may depend on a weakening in signal synergies (that express the neural drive to muscles deduced from surface electromyography data).

METHODS

Such an innovative approach to estimate muscle networks and signal synergies was carried out in seven patients with DM1 and ten healthy controls (HC).

RESULTS

Patients with DM1 showed a commingling of low and high frequencies among muscle at both within- and between-limbs level, a weak direct neural coupling concerning inter-limb coordination, a modest network segregation, high integrative network properties, and an impoverishment in the available signal synergies, as compared to HCs. These network abnormalities were independent from muscle weakness and myotonia.

CONCLUSIONS

Our results suggest that gait impairment in patients with DM1 depends also on a muscle network deterioration that is secondary to signal synergy deterioration (related to CNS impairment). This suggests that muscle network deterioration may be a primary trait of DM1 rather than a maladaptive mechanism to muscle degeneration. This information may be useful concerning the implementation of proper rehabilitative strategies in patients with DM1. It will be indeed necessary not only addressing muscle weakness but also gait-related muscle connectivity to improve functional ambulation in such patients.

The Understanding Capacity and Information Dynamics in the Human Brain

This article proposes a theory of neuronal processes underlying cognition, focusing on the mechanisms of understanding in the human brain. Understanding is a product of mental modeling. The paper argues that mental modeling is a form of information production inside the neuronal system extending the reach of human cognition "beyond the information given" (Bruner, J.S., Beyond the Information Given, 1973). Mental modeling enables forms of learning and prediction (learning with understanding and prediction via explanation) that are unique to humans, allowing robust performance under unfamiliar conditions having no precedents in the past history. The proposed theory centers on the notions of self-organization and emergent properties of collective behavior in the neuronal substrate. The theory motivates new approaches in the design of intelligent artifacts (machine understanding) that are complementary to those underlying the technology of machine learning.