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

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

A model-based approach to predict muscle synergies using optimization: application to feedback control

This Document is Protected by copyright and was first published by Frontiers. All rights reserved. it is reproduced with permission.This paper presents a new model-based method to define muscle synergies. Unlike the conventional factorization approach, which extracts synergies from electromyographic data, the proposed method employs a biomechanical model and formally defines the synergies as the solution of an optimal control problem. As a result, the number of required synergies is directly related to the dimensions of the operational space. The estimated synergies are posture-dependent, which correlate well with the results of standard factorization methods. Two examples are used to showcase this method: a two-dimensional forearm model, and a three-dimensional driver arm model. It has been shown here that the synergies need to be task-specific (i.e., they are defined for the specific operational spaces: the elbow angle and the steering wheel angle in the two systems). This functional definition of synergies results in a low-dimensional control space, in which every force in the operational space is accurately created by a unique combination of synergies. As such, there is no need for extra criteria (e.g., minimizing effort) in the process of motion control. This approach is motivated by the need for fast and bio-plausible feedback control of musculoskeletal systems, and can have important implications in engineering, motor control, and biomechanics.The authors wish to thank the Natural Sciences and Engineering Research Council of Canada (NSERC) for funding this study

Design and effectiveness evaluation of mirror myoelectric interfaces: a novel method to restore movement in hemiplegic patients

The motor impairment occurring after a stroke is characterized by pathological muscle activation patterns or synergies. However, while robot-aided myoelectric interfaces have been proposed for stroke rehabilitation, they do not address this issue, which might result in inefficient interventions. Here, we present a novel paradigm that relies on the correction of the pathological muscle activity as a way to elicit rehabilitation, even in patients with complete paralysis. Previous studies demonstrated that there are no substantial inter-limb differences in the muscle synergy organization of healthy individuals. We propose building a subject-specific model of muscle activity from the healthy limb and mirroring it to use it as a learning tool for the patient to reproduce the same healthy myoelectric patterns on the paretic limb during functional task training. Here, we aim at understanding how this myoelectric model, which translates muscle activity into continuous movements of a 7-degree of freedom upper limb exoskeleton, could transfer between sessions, arms and tasks. The experiments with 8 healthy individuals and 2 chronic stroke patients proved the feasibility and effectiveness of such myoelectric interface. We anticipate the proposed method to become an efficient strategy for the correction of maladaptive muscle activity and the rehabilitation of stroke patients.This study was funded by the Baden-Württemberg Stiftung (GRUENS ROB-1), the Deutsche Forschungsgemeinschaft (DFG, Koselleck), the Fortüne-Program of the University of Tübingen (2422-0-0), and the Bundes Ministerium für Bildung und Forschung BMBF MOTORBIC (FKZ 13GW0053), AMORSA (FKZ 16SV7754), Gipuzkoa Regional Government (INKRATEK), Ministry of Science of the Basque Country (Elkartek: EXOTEK). A. Sarasola-Sanz’s work was supported by La Caixa-DAAD scholarship and N. Irastorza-Landa’s work by the Basque Government and IKERBASQUE, Basque Foundation for Science, Bilbao, Spain

Differences between kinematic synergies and muscle synergies during two-digit grasping

International audienceThe large number of mechanical degrees of freedom of the hand is not fully exploited during actual movements such as grasping. Usually, angular movements in various joints tend to be coupled, and EMG activities in different hand muscles tend to be correlated. The occurrence of covariation in the former was termed kinematic synergies, in the latter muscle synergies. This study addresses two questions: (i) Whether kinematic and muscle synergies can simultaneously accommodate for kinematic and kinetic constraints. (ii) If so, whether there is an interrelation between kinematic and muscle synergies. We used a reach-grasp-and-pull paradigm and recorded the hand kinematics as well as eight surface EMGs. Subjects had to either perform a precision grip or side grip and had to modify their grip force in order to displace an object against a low or high load. The analysis was subdivided into three epochs: reach, grasp-and-pull, and static hold. Principal component analysis (PCA, temporal or static) was performed separately for all three epochs, in the kinematic and in the EMG domain. PCA revealed that (i) Kinematic-and muscle-synergies can simultaneously accommodate kinematic (grip type) and kinetic task constraints (load condition). (ii) Upcoming grip and load conditions of the grasp are represented in kinematic-and muscle-synergies already during reach. Phase plane plots of the principal muscle-synergy against the principal kinematic synergy revealed (iii) that the muscle-synergy is linked (correlated, and in phase advance) to the kinematic synergy during reach and during grasp-and-pull. Furthermore (iv), pair-wise correlations of EMGs during hold suggest that muscle-synergies are (in part) implemented by coactivation of muscles through common input. Together, these results suggest that kinematic synergies have (at least in part) their origin not just in muscular activation, but in synergistic muscle activation. In short: kinematic synergies may result from muscle synergies

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

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

Evaluation of Matrix Factorisation Approaches for Muscle Synergy Extraction

The muscle synergy concept provides a widely-accepted paradigm to break down the complexity of motor control. In order to identify the synergies, different matrix factorisation techniques have been used in a repertoire of fields such as prosthesis control and biomechanical and clinical studies. However, the relevance of these matrix factorisation techniques is still open for discussion since there is no ground truth for the underlying synergies. Here, we evaluate factorisation techniques and investigate the factors that affect the quality of estimated synergies. We compared commonly used matrix factorisation methods: Principal component analysis (PCA), Independent component analysis (ICA), Non-negative matrix factorization (NMF) and second-order blind identification (SOBI). Publicly available real data were used to assess the synergies extracted by each factorisation method in the classification of wrist movements. Synthetic datasets were utilised to explore the effect of muscle synergy sparsity, level of noise and number of channels on the extracted synergies. Results suggest that the sparse synergy model and a higher number of channels would result in better-estimated synergies. Without dimensionality reduction, SOBI showed better results than other factorisation methods. This suggests that SOBI would be an alternative when a limited number of electrodes is available but its performance was still poor in that case. Otherwise, NMF had the best performance when the number of channels was higher than the number of synergies. Therefore, NMF would be the best method for muscle synergy extraction.Comment: Keywords: Muscle synergy; Matrix factorisation; Surface electromyogram; Non-negative matrix factorisation; Second-order blind identification; Principal component analysis; Independent component analysi

A tensor decomposition reveals ageing-induced differences in muscle and grip-load force couplings during object lifting

Do motor patterns of object lifting movements change as a result of ageing? Here we propose a methodology for the characterization of these motor patterns across individuals of different age groups. Specifically, we employ a bimanual grasp-lift-replace protocol with younger and older adults and combine measurements of muscle activity with grip and load forces to provide a window into the motor strategies supporting effective object lifts. We introduce a tensor decomposition to identify patterns of muscle activity and grip-load force ratios while also characterizing their temporal profiles and relative activation across object weights and participants of different age groups. We then probe age-induced changes in these components. A classification analysis reveals three motor components that are differentially recruited between the two age groups. Linear regression analyses further show that advanced age and poorer manual dexterity can be predicted by the coupled activation of forearm and hand muscles which is associated with high levels of grip force. Our findings suggest that ageing may induce stronger muscle couplings in distal aspects of the upper limbs, and a less economic grasping strategy to overcome age-related decline in manual dexterity

Feasibility Theory Reconciles and Informs Alternative Approaches to Neuromuscular Control

We present Feasibility Theory, a conceptual and computational framework to unify today's theories of neuromuscular control. We begin by describing how the musculoskeletal anatomy of the limb, the need to control individual tendons, and the physics of a motor task uniquely specify the family of all valid muscle activations that accomplish it (its ‘feasible activation space’). For our example of producing static force with a finger driven by seven muscles, computational geometry characterizes—in a complete way—the structure of feasible activation spaces as 3-dimensional polytopes embedded in 7-D. The feasible activation space for a given task is the landscape where all neuromuscular learning, control, and performance must occur. This approach unifies current theories of neuromuscular control because the structure of feasible activation spaces can be separately approximated as either low-dimensional basis functions (synergies), high-dimensional joint probability distributions (Bayesian priors), or fitness landscapes (to optimize cost functions)

Muscle synergy analysis of lower-limb movements

Dissertação de mestrado integrado em Biomedical Engineering (área de especialização em Medical Electronics)Neurological disorders and trauma often lead to impaired lower-limb motor coordination. Understanding how muscles combine to produce movement can directly benefit assistive solutions to those afflicted with these impairments. A theory in neuromusculoskeletal research, known as muscle synergies, has shown promising results in applications for this field. This hypothesis postulates that the Central Nervous System controls motor tasks through the time-variant combinations of modules (or synergies), each representing the co-activation of a group of muscles. There is, however, no unifying, evidence-based framework to ascertain muscle synergies, as synergy extraction methods vary greatly in the literature. Publications also focus on gait analysis, leaving a knowledge gap when concerning motor tasks important to daily life such as sitting and standing. The purpose of this dissertation is the development of a robust, evidence-based, task-generic synergy extraction framework unifying the divergent methodologies of this field of study, and to use this framework to study healthy muscle synergies on several activities of daily living: walking, sit-to-stand, stand-to-sit and knee flexion and extension. This was achieved by designing and implementing a cross-validated Non-Negative Matrix Factorization process and applying it to muscle electrical activity data. A preliminary study was undertaken to tune this configuration regarding cross-validating proportions, data structuring prior to factorization and evaluating criteria quantifying accuracy in modularity findings. Muscle synergies results were then investigated for different performing speeds to determine if their structure differed, and for consistency across subjects, to ascertain if a common set of muscle synergies underlay control on all subjects equally. Results revealed that the implemented framework was consistent in its ability to capture modularity (p < 0:05). The movements’ synergies also did not differ across the studied range of speeds (except one module in Knee Flexion) (p < 0:05). Additionally, a common set of muscle synergies was present across several subjects (p < 0:05), but shared commonality across every participant was only observed for the walking trials, for which much larger amounts of data were collected. Overall, the established framework is versatile and applicable for different lower-limb movements; muscle synergies findings for the examined movements may also be used as control references in assistive devices.As perturbações e traumas neurológicos afetam frequentemente a coordenação motora dos membros inferiores. Uma teoria recente em investigação neuromusculo-esquelética, denominada de sinergias musculares, tem demonstrado resultados promissores em soluções de assistência à população afetada por estes distúrbios. Esta teoria propõe que o Sistema Nervoso Central controla as tarefas motoras através de combinações variantes no tempo de módulos (ou sinergias), sendo que cada um representa a co-ativação de um grupo de músculos. No entanto, não existe nenhum processo uniformizante, empiricamente justificado para determinar sinergias musculares, porque os métodos de extração de sinergias variam muito na literatura. Para além disso, as publicações normalmente focam-se em análise da marcha, deixando uma lacuna de conhecimento em tarefas motoras do dia-a-dia, tais como sentar e levantar. O objetivo desta dissertação é o desenvolvimento de um processo robusto, genérico e empiricamente justificado de extração de sinergias em várias tarefas motoras, unindo as metodologias divergentes neste campo de estudo, e subsequentemente utilizar este processo para estudar sinergias musculares de sujeitos saudáveis em várias atividades do dia-a-dia: marcha, erguer-se de pé partir de uma posição sentada, sentar-se a partir de uma posição de pé e extensão e flexão do joelho. Isto foi alcançado através da implementação de um processo de cross-validated Non-Negative Matrix Factorization e subsequente aplicação em dados de atividade elétrica muscular. Um estudo preliminar foi realizado para configurar este processo relativamente às proporções de cross-validation, estruturação de dados antes da fatorização e seleção de critério que quantifique o sucesso da representação modular dos dados. Os resultados da extração de sinergias de diferentes velocidades de execução foram depois examinados no sentido de descobrir se este fator influenciava a estrutura dos módulos motores, assim como se semelhanças entre as sinergias de diferentes sujeitos apontavam para um conjunto comum de sinergias musculares subjacente ao controlo do movimento. Os resultados revelaram que o processo implementado foi consistente na sua capacidade de capturar a modularidade nos dados recolhidos (p < 0:05). As sinergias de todos os movimentos também não diferiram para toda a gama de velocidades estudada (exceto um módulo na flexão do joelho) (p < 0:05). Por fim, um conjunto comum de sinergias musculares esteve presente em vários sujeitos (p < 0:05), mas só esteve presente em todos os sujeitos de igual forma para a marcha, para a qual a quantidade de dados recolhida foi muito maior. Globalmente, o processo implementado é versátil e aplicável a diferentes movimentos dos membros inferiores; os resultados das sinergias musculares para os movimentos examinados podem também ser utilizado como referências de controlo para dispositivos de assistência