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

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

A Review of EMG Techniques for Detection of Gait Disorders

Electromyography (EMG) is a commonly used technique to record myoelectric signals, i.e., motor neuron signals that originate from the central nervous system (CNS) and synergistically activate groups of muscles resulting in movement. EMG patterns underlying movement, recorded using surface or needle electrodes, can be used to detect movement and gait abnormalities. In this review article, we examine EMG signal processing techniques that have been applied for diagnosing gait disorders. These techniques span from traditional statistical tests to complex machine learning algorithms. We particularly emphasize those techniques are promising for clinical applications. This study is pertinent to both medical and engineering research communities and is potentially helpful in advancing diagnostics and designing rehabilitation devices

Electromyography Data Processing Impacts Muscle Synergies during Gait for Unimpaired Children and Children with Cerebral Palsy

Muscle synergies calculated from electromyography (EMG) data identify weighted groups of muscles activated together during functional tasks. Research has shown that fewer synergies are required to describe EMG data of individuals with neurologic impairments. When considering potential clinical applications of synergies, understanding how EMG data processing impacts results and clinical interpretation is important. The aim of this study was to evaluate how EMG signal processing impacts synergy outputs during gait. We evaluated the impacts of two common processing steps for synergy analyses: low pass (LP) filtering and unit variance scaling. We evaluated EMG data collected during barefoot walking from five muscles of 113 children with cerebral palsy (CP) and 73 typically-developing (TD) children. We applied LP filters to the EMG data with cutoff frequencies ranging from 4 to 40 Hz (reflecting the range reported in prior synergy research). We also evaluated the impact of normalizing EMG amplitude by unit variance. We found that the total variance accounted for (tVAF) by a given number of synergies was sensitive to LP filter choice and decreased in both TD and CP groups with increasing LP cutoff frequency (e.g., 9.3 percentage points change for one synergy between 4 and 40 Hz). This change in tVAF can alter the number of synergies selected for further analyses. Normalizing tVAF to a z-score (e.g., dynamic motor control index during walking, walk-DMC) reduced sensitivity to LP cutoff. Unit variance scaling caused comparatively small changes in tVAF. Synergy weights and activations were impacted less than tVAF by LP filter choice and unit variance normalization. These results demonstrate that EMG signal processing methods impact outputs of synergy analysis and z-score based measures can assist in reporting and comparing results across studies and clinical centers

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

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

Modular control of human movement during running: An open access data set

The human body is an outstandingly complex machine including around 1000 muscles and joints acting synergistically. Yet, the coordination of the enormous amount of degrees of freedom needed for movement is mastered by our one brain and spinal cord. The idea that some synergistic neural components of movement exist was already suggested at the beginning of the 20th century. Since then, it has been widely accepted that the central nervous system might simplify the production of movement by avoiding the control of each muscle individually. Instead, it might be controlling muscles in common patterns that have been called muscle synergies. Only with the advent of modern computational methods and hardware it has been possible to numerically extract synergies from electromyography (EMG) signals. However, typical experimental setups do not include a big number of individuals, with common sample sizes of 5 to 20 participants. With this study, we make publicly available a set of EMG activities recorded during treadmill running from the right lower limb of 135 healthy and young adults (78 males and 57 females). Moreover, we include in this open access data set the code used to extract synergies from EMG data using non-negative matrix factorization (NMF) and the relative outcomes. Muscle synergies, containing the time-invariant muscle weightings (motor modules) and the time-dependent activation coefficients (motor primitives), were extracted from 13 ipsilateral EMG activities using NMF. Four synergies were enough to describe as many gait cycle phases during running: weight acceptance, propulsion, early swing, and late swing. We foresee many possible applications of our data that we can summarize in three key points. First, it can be a prime source for broadening the representation of human motor control due to the big sample size. Second, it could serve as a benchmark for scientists from multiple disciplines such as musculoskeletal modeling, robotics, clinical neuroscience, sport science, etc. Third, the data set could be used both to train students or to support established scientists in the perfection of current muscle synergies extraction methods. All the data is available at Zenodo (doi: 10.5281/zenodo.1254380). © 2018 Frontiers Media S.A.All right reserved

The influence of musculoskeletal pain disorders on muscle synergies—A systematic review

Background Musculoskeletal (MSK) pain disorders represent a group of highly prevalent and often disabling conditions. Investigating the structure of motor variability in response to pain may reveal novel motor impairment mechanisms that may lead to enhanced management of motor dysfunction associated with MSK pain disorders. This review aims to systematically synthesize the evidence on the influence of MSK pain disorders on muscle synergies. Methods Nine electronic databases were searched using Medical Subject Headings and keywords describing pain, electromyography and synergies. Relevant characteristics of included studies were extracted and assessed for generalizability and risk of bias. Due to the significant heterogeneity, a qualitative synthesis of the results was performed. Results The search resulted in a total of 1312 hits, of which seven articles were deemed eligible. There was unclear consistency that pain reduced the number of muscle synergies. There were low consistencies of evidence that the synergy vector (W weights) and activation coefficient (C weights) differed in painful compared to asymptomatic conditions. There was a high consistency that muscle synergies were dissimilar between painful and asymptomatic conditions. Conclusions MSK pain alters the structure of variability in muscle control, although its specific nature remains unclear. Greater consistency in muscle synergy analysis may be achieved with appropriate selection of muscles assessed and ensuring consistent achievement of motor task outcomes. Synergy analysis is a promising method to reveal novel understandings of altered motor control, which may facilitate the assessment and treatment of MSK pain disorders

Neural control of gait in people with haemophilic arthropathy

La hemofilia es un trastorno hemorrágico causado por una deficiencia de los factores VIII o IX de la coagulación. Las personas con hemofilia grave pueden tener hemorragias espontáneas o hemorragias en respuesta a traumatismos menores; la mayoría de los eventos ocurren en las articulaciones y los músculos. La manifestación clínica más frecuente es la artropatía hemofílica, que resulta del sangrado intraarticular repetitivo y de la membrana sinovial inflamada, lo que puede resultar en dolor crónico y deterioro articular. El objetivo general de mi tesis fue investigar el control neural de la marcha en personas con artropatía hemofílica (PCAH). La hipótesis de mi tesis fue que control neural de la marcha se ve afectado en PCAH, y los cambios en el control neural de la marcha están asociados con el daño articular y la cronicidad de la restricción articular. Se seleccionó la marcha, ya que las rodillas y los tobillos son las articulaciones que más se afectan en adultos PCAH. El núcleo de mi tesis fue investigar el control neural mediante el estudio de patrones de actividad de electromiografía (EMG) de músculos individuales y/o sinergias musculares, así como su interacción con la cinemática articular y evaluaciones clínicas. En el capítulo 1, ofrezco una perspectiva general sobre el impacto de la hemofilia en el sistema musculoesquelético, las lagunas actuales en el conocimiento sobre el control neural de la marcha en la artropatía hemofílica y cómo evaluar el control neural de la marcha. En los Capítulos 2 y 4, a través de las evaluaciones de los patrones de activación muscular de músculos individuales, la coordinación entre pares de músculos antagonistas y el análisis de sinergia muscular, confirmamos la hipótesis de que el control neural de la marcha se ve afectado en PCAH. En los capítulos 3 y 5, confirmamos que el control neural alterado de la marcha en PCAH está asociado con la gravedad del daño articular y la cronicidad de la restricción articular. En el capítulo 6, discutimos los resultados de los capítulos centrados en las perspectivas clínicas y fisiológicas del control neural alterado de la marcha en PCAH. Además, discutimos cómo la evaluación del control neuronal a través del índice dynamic motor control index during walking (Walk-DMC) puede ser una alternativa para monitorear el deterioro motor en PCAH. Con base en nuestros resultados, también discutimos cómo mejorar los resultados de la fisioterapia y las intervenciones quirúrgicas que tienen como objetivo mejorar la locomoción en PCAH. Mi tesis contribuye a comprender las consecuencias de la artropatía hemofílica, en especial en la neuromecánica de la marcha. Los hallazgos de mi tesis indican que el control neural de la marcha se ve afectado en PCAH, y los cambios en el control neural de la marcha están asociados con el daño articular, el dolor y cronicidad de la restricción articular. Desde una perspectiva científica, los cambios en el control neural de la marcha en PCAH implican patrones de actividad alterados de los músculos del tren inferior y una reorganización modular de la marcha. Desde una perspectiva clínica, mi tesis brinda una nueva mirada sobre cómo monitorear la progresión de la enfermedad en PCAH utilizando el índice Walk-DMC, brindando nuevas perspectivas para mejorar las intervenciones terapéuticas que apuntan a recuperar la marcha en PCAH.Haemophilia is a bleeding disorder caused by a deficiency of coagulation factors VIII or factor IX. People with severe haemophilia may have spontaneous bleeding events or bleeding in response to minor trauma; most of the events occur in the joints and muscles. The most frequent clinical manifestation is haemophilic arthropathy, which results from repetitive intraarticular bleeding and inflamed synovial membrane, which may result in chronic pain and joint impairment. The overall aim of my thesis was to investigate the neural control of gait in people with haemophilic arthropathy (PWHA). I hypothesized that neural gait control is affected in PWHA, and the changes in neural control of gait are associated with joint damage and chronicity of the joint constraint. Gait was selected because the knees and ankles are the most prevalent affected joints in adults PWHA. The core of my thesis is investigating neural control by studying electromyography (EMG) activity patterns of single muscles and/or muscle synergies, as well as their interaction with joint kinematics and clinical outcomes. In chapter 1, I provide a general perspective about the impact of haemophilia on the musculoskeletal system, the current gaps in knowledge in the neural control of gait in haemophilic arthropathy, and how to assess the neural control of gait. In Chapters 2 and 4, through the assessments of muscle activation patterns of single muscles, coordination between antagonistic muscle pairs, and muscle synergy analysis, we confirmed the hypothesis that the neural control of gait is affected in PWHA. In chapters 3 and 5, we confirm that the altered neural control of gait in PWHA is associated with the severity of joint damage and chronicity of joint constraint. In chapter 6, we discussed the results of chapters focused on clinical and physiological perspectives of the altered neural control of gait in PWHA. In addition, we discuss how the evaluation of neural control through the Walk-DMC index can be an alternative to monitoring the motor impairment in PWHA. Based on our results, we also discussed on how to improve the outcomes of physical therapy and surgical interventions that aimed to improve the locomotion in PWHA. My thesis contributes to understanding the consequences of haemophilic arthropathy for the neuromechanics of gait. The findings of my thesis indicate that neural control of gait is affected in PWHA, and the changes in the neural control of gait are associated with joint damage, pain and chronicity of the joint constraint. From a scientific perspective, the changes in the neural control of gait in PWHA implicate altered activity patterns of single leg muscles and a modular reorganization of gait. From a clinical perspective, my thesis gives a new perspective on how to monitor disease progression in PWHA using the Walk-DMC index—providing new perspectives to improve the therapeutic interventions that aim to recover gait in PWHA

Superficial shoulder muscle synergy analysis in Facioscapulohumeral Dystrophy during humeral elevation tasks

Facioscapulohumeral Dystrophy (FSHD) is a progressive muscle-wasting disease which leads to a decline in upper extremity functionality. Although the scapulohumeral joint's stability and functionality are affected, evidence on the synergetic control of the shoulder muscles in FSHD individuals is still lacking. The aim of this study is to understand the neuromuscular changes in shoulder muscle control in people with FSHD. Upper arm kinematics and electromyograms (EMG) of eight upper extremity muscles were recorded during shoulder abduction-adduction and flexion-extension tasks in eleven participants with FSHD and eleven healthy participants. Normalized muscle activities were extracted from EMG signals. Non-negative matrix factorization was used to compute muscle synergies. Maximum muscle activities were compared using non-parametric analysis of variance. Similarities between synergies were also calculated using correlation. The Biceps Brachii was significantly more active in the FSHD group (25±2%) while Trapezius Ascendens and Serratus Anterior were less active (32±7% and 39±4% respectively). Muscle synergy weights were altered in FSHD individuals and showed greater diversity while controls mostly used one synergy for both tasks. The decreased activity by selected scapula rotator muscles and muscle synergy weight alterations show that neuromuscular control of the scapulohumeral joint is less consistent in people with FSHD compared to healthy participants. Assessments of muscle coordination strategies can be used to evaluate motor output variability and assist in management of the disease

Nonlinear and factorization methods for the non-invasive investigation of the central nervous system

This thesis focuses on the functional study of the Central Nervous System (CNS) with non-invasive techniques. Two different aspects are investigated: nonlinear aspects of the cerebrovascular system, and the muscle synergies model for motor control strategies. The main objective is to propose novel protocols, post-processing procedures or indices to enhance the analysis of cerebrovascular system and human motion analysis with noninvasive devices or wearable sensors in clinics and rehabilitation. We investigated cerebrovascular system with Near-infrared Spectroscopy (NIRS), a technique measuring blood oxygenation at the level of microcirculation, whose modification reflects cerebrovascular response to neuronal activation. NIRS signal was analyzed with nonlinear methods, because some physiological systems, such as neurovascular coupling, are characterized by nonlinearity. We adopted Empirical Mode Decomposition (EMD) to decompose signal into a finite number of simple functions, called Intrinsic Mode Functions (IMF). For each IMF, we computed entropy-based features to characterize signal complexity and variability. Nonlinear features of the cerebrovascular response were employed to characterize two treatments. Firstly, we administered a psychotherapy called eye movement desensitization and reprocessing (EMDR) to two groups of patients. The first group performed therapy with eye movements, the second without. NIRS analysis with EMD and entropy-based features revealed a different cerebrovascular pattern between the two groups, that may indicate the efficacy of the psychotherapy when administered with eye movements. Secondly, we administered ozone autohemotherapy to two groups of subjects: a control group of healthy subjects and a group of patients suffering by multiple sclerosis (MS). We monitored the microcirculation with NIRS from oxygen-ozone injection up 1.5 hours after therapy, and 24 hours after therapy. We observed that, after 1.5 hours after the ozonetherapy, oxygenation levels improved in both groups, that may indicate that ozonetherapy reduced oxidative stress level in MS patients. Furthermore, we observed that, after ozonetherapy, autoregulation improved in both groups, and that the beneficial effects of ozonetherapy persisted up to 24 hours after the treatment in MS patients. Due to the complexity of musculoskeletal system, CNS adopts strategies to efficiently control the execution of motor tasks. A model of motor control are muscle synergies, defined as functional groups of muscles recruited by a unique central command. Human locomotion was the object of investigation, due to its importance for daily life and the cyclicity of the movement. Firstly, by exploiting features provided from statistical gait analysis, we investigated consistency of muscle synergies. We demonstrated that synergies are highly repeatable within-subjects, reinforcing the hypothesis of modular control in motor performance. Secondly, in locomotion, we distinguish principal from secondary activations of electromyography. Principal activations are necessary for the generation of the movement. Secondary activations generate supplement movements, for instance slight balance correction. We investigated the difference in the motor control strategies underlying muscle synergies of principal (PS) and secondary (SS) activations. We found that PS are constituted by a few modules with many muscles each, whereas SS are described by more modules than PS with one or two muscles each. Furthermore, amplitude of activation signals of PS is higher than SS. Finally, muscle synergies were adopted to investigate the efficacy of rehabilitation of stiffed-leg walking in lower back pain (LBP). We recruited a group of patients suffering from non-specific LBP stiffening the leg at initial contact. Muscle synergies during gait were extracted before and after rehabilitation. Our results showed that muscles recruitment and consistency of synergies improved after the treatment, showing that the rehabilitation may affect motor control strategies