Predictive modulation of muscle coordination pattern magnitude scales fingertip force magnitude over the voluntary range

Metabolic cost for isometric force scales nonlinearly and predicts how humans distribute forces across limbs

Muscles consume metabolic energy for force production and movement. A mathematical model of metabolic energy cost will be useful in predicting instantaneous costs during human exercise and in computing effort-minimizing movements via simulations. Previous in vivo data-derived models usually assumed either zero or linearly increasing cost with force, but a nonlinear relation could have significant metabolic or behavioural implications. Here, we show that metabolic cost scales nonlinearly with joint torque with an exponent of about 1.64, using calorimetric measurements of isometric squats. We then demonstrate that this metabolic nonlinearity is reflected in human behaviour: minimizing this nonlinear cost predicts how humans share forces between limbs in additional experiments involving arms and legs. This shows the utility of the nonlinear energy cost in predictive models and its generalizability across limbs. Finally, we show mathematical evidence that the same nonlinear metabolic objective may underlie force sharing at the muscle level.

Effects of wrist posture and stabilization on precision grip force production and muscle activation patterns

Most of the power for generating forces in the fingers arises from muscles located in the forearm. This configuration maximizes finger joint range of motion while minimizing finger mass and inertia. The resulting multiarticular arrangement of the tendons, however, complicates independent control of the wrist and the digits. Actuating the wrist impacts sensorimotor control of the fingers and vice versa. The goal of this study was to systematically investigate interactions between isometric wrist and digit control. Specifically, we examined how the need to maintain a specified wrist posture influences precision grip. Fifteen healthy adults produced maximum precision grip force at 11 different wrist flexion/extension angles, with the arm supported, under two conditions: 1) the participant maintained the desired wrist angle while performing the precision grip and 2) a robot maintained the specified wrist angle. Wrist flexion/extension posture significantly impacted maximum precision grip force (P < 0.001), with the greatest grip force achieved when the wrist was extended 30° from neutral. External wrist stabilization by the robot led to a 20% increase in precision grip force across wrist postures. Increased force was accompanied by increased muscle activation but with an activation pattern similar to the one used when the participant had to stabilize their wrist. Thus, simultaneous wrist and finger requirements impacted performance of an isometric finger task. External wrist stabilization can promote increased precision grip force resulting from increased muscle activation. These findings have potential clinical significance for individuals with neurologically driven finger weakness, such as stroke survivors.NEW & NOTEWORTHY We explored the interdependence between wrist and fingers by assessing the influence of wrist posture and external stabilization on precision grip force generation. We found that maximum precision grip force occurred at an extended wrist posture and was 20% greater when the wrist was Externally Stabilized. The latter resulted from amplification of muscle activation patterns from the Self-Stabilized condition rather than adoption of new patterns exploiting external wrist stabilization.

Neuromuscular control: from a biomechanist's perspective

Understanding neural control of movement necessitates a collaborative approach between many disciplines, including biomechanics, neuroscience, and motor control. Biomechanics grounds us to the laws of physics that our musculoskeletal system must obey. Neuroscience reveals the inner workings of our nervous system that functions to control our body. Motor control investigates the coordinated motor behaviours we display when interacting with our environment. The combined efforts across the many disciplines aimed at understanding human movement has resulted in a rich and rapidly growing body of literature overflowing with theories, models, and experimental paradigms. As a result, gathering knowledge and drawing connections between the overlapping but seemingly disparate fields can be an overwhelming endeavour. This review paper evolved as a need for us to learn of the diverse perspectives underlying current understanding of neuromuscular control. The purpose of our review paper is to integrate ideas from biomechanics, neuroscience, and motor control to better understand how we voluntarily control our muscles. As biomechanists, we approach this paper starting from a biomechanical modelling framework. We first define the theoretical solutions (i.e., muscle activity patterns) that an individual could feasibly use to complete a motor task. The theoretical solutions will be compared to experimental findings and reveal that individuals display structured muscle activity patterns that do not span the entire theoretical solution space. Prevalent neuromuscular control theories will be discussed in length, highlighting optimality, probabilistic principles, and neuromechanical constraints, that may guide individuals to families of muscle activity solutions within what is theoretically possible. Our intention is for this paper to serve as a primer for the neuromuscular control scientific community by introducing and integrating many of the ideas common across disciplines today, as well as inspire future work to improve the representation of neural control in biomechanical models.

Motor cortex outputs evoked by long-duration microstimulation encode synergistic muscle activation patterns not controlled movement trajectories

The effects of intracortical microstimulation (ICMS) parameters on the evoked electromyographic (EMG) responses and resulting limb movement were investigated. In ketamine-anesthetized cats, paw movement kinematics in 3D and EMG activity from 8 to 12 forelimb muscles evoked by ICMS applied to the forelimb area of the cat motor cortex (MCx) were recorded. The EMG responses evoked by ICMS were also compared to those evoked by focal ictal bursts induced by the iontophoretic ejection of the GABA_A receptor antagonist bicuculline methochloride (BIC) at the same cortical point. The effects of different initial limb starting positions on movement trajectories resulting from long-duration ICMS were also studied. The ICMS duration did not affect the evoked muscle activation pattern (MAP). Short (50 ms) and long (500 ms) stimulus trains activated the same muscles in the same proportions. MAPs could, however, be modified by gradually increasing the stimulus intensity. MAPs evoked by focal ictal bursts were also highly correlated with those obtained by ICMS at the same cortical point. Varying the initial position of the forelimb did not change the MAPs evoked from a cortical point. Consequently, the evoked movements reached nearly the same final end point and posture, with variability. However, the movement trajectories were quite different depending on the initial limb configuration and starting position of the paw. The evoked movement trajectory was most natural when the forelimb lay pendant ~ perpendicular to the ground (i.e., in equilibrium with the gravitational force). From other starting positions, the movements did not appear natural. These observations demonstrate that while the output of the cortical point evokes a seemingly coordinated limb movement from a rest position, it does not specify a particular movement direction or a controlled trajectory from other initial positions.

Force and electromyography reflections of sensory action-effect weighting during pinching

Ideomotor theories suggest that different action-effects are not equally important in goal-directed actions, and that task-relevant information are weighted stronger during the representation of actions. This stronger weighting of task-relevant action-effects might also enable to utilize them as retrieval cues of the corresponding motor patterns. The aim of the present study was to investigate how the consistent presence or absence of a sound action-effect influenced the retrieval of the motor components of a simple, everyday action (pinching) as reflected by the pattern of force application and surface electromyogram (sEMG) recorded from the abductor pollicis brevis (APB) and first dorsal interosseous (FDI). Participants applied pairs of pinch impulses to a force sensitive resistor (FSR). The presence or absence of a sound action-effect and the between-action interval (BAI, 2 or 4 s) were manipulated blockwise, whereas the target force level (low or high) was randomly cued from trial to trial. When actions resulted in a sound, force and sEMG activity were reduced. This effect was more pronounced for low target force level trials, which is compatible with a stronger weighting of the sound action-effect when the intensity of the tactile and proprioceptive action-effects is low. Surprisingly, the FDI activity was more variable within actions pairs in the 2 s BAI conditions, which suggests that action pairs separated by the longer time interval might have been represented differently from those separated by the shorter interval.

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

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

Finger stability in precision grips

Stable precision grips using the fingertips are a cornerstone of human hand dexterity. However, our fingers become unstable sometimes and snap into a hyperextended posture. This is because multilink mechanisms like our fingers can buckle under tip forces. Suppressing this instability is crucial for hand dexterity, but how the neuromuscular system does so is unknown. Here we show that people rely on the stiffness from muscle contraction for finger stability. We measured buckling time constants of 50 ms or less during maximal force application with the index finger—quicker than feedback latencies—which suggests that muscle-induced stiffness may underlie stability. However, a biomechanical model of the finger predicts that muscle-induced stiffness cannot stabilize at maximal force unless we add springs to stiffen the joints or people reduce their force to enable cocontraction. We tested this prediction in 38 volunteers. Upon adding stiffness, maximal force increased by 34 ± 3%, and muscle electromyography readings were 21 ± 3% higher for the finger flexors (mean ± SE). Muscle recordings and mathematical modeling show that adding stiffness offloads the demand for muscle cocontraction, thus freeing up muscle capacity for fingertip force. Hence, people refrain from applying truly maximal force unless an external stabilizing stiffness allows their muscles to apply higher force without losing stability. But more stiffness is not always better. Stiff fingers would affect the ability to adapt passively to complex object geometries and precisely regulate force. Thus, our results show how hand function arises from neurally tuned muscle stiffness that balances finger stability with compliance.

The neural mechanisms of manual dexterity

The hand endows us with unparalleled precision and versatility in our interactions with objects, from mundane activities such as grasping to extraordinary ones such as virtuoso pianism. The complex anatomy of the human hand combined with expansive and specialized neuronal control circuits allows a wide range of precise manual behaviours. To support these behaviours, an exquisite sensory apparatus, spanning the modalities of touch and proprioception, conveys detailed and timely information about our interactions with objects and about the objects themselves. The study of manual dexterity provides a unique lens into the sensorimotor mechanisms that endow the nervous system with the ability to flexibly generate complex behaviour.

Multiplex Recurrence Network Analysis of Inter-Muscular Coordination During Sustained Grip and Pinch Contractions at Different Force Levels

Production of functional forces by human motor systems require coordination across multiple muscles. Grip and pinch are two prototypes for grasping force production. Each grasp plays a role in a range of hand functions and can provide an excellent paradigm for studying fine motor control. Despite previous investigations that have characterized muscle synergies during general force production, it is still unclear how intermuscular coordination differs between grip and pinch and across different force outputs. Traditional muscle synergy analyses, such as non-negative matrix factorization or principal component analysis, utilize dimensional reduction without consideration of nonlinear characteristics of muscle co-activations. In this study, we investigated the novel method of multiplex recurrence networks (MRN) to assess the inter-muscular coordination for both grip and pinch at different force levels. Unlike traditional methods, the MRN can leverage intrinsic similarities in muscle contraction dynamics and project its layers to the corresponding weighted network (WN) to better model muscle interactions. Twenty-four healthy volunteers were instructed to grip and pinch an apparatus with force production at 30%, 50%, and 70% of their respective maximal voluntary contraction (MVC). The surface electromyography (sEMG) signals were recorded from eight muscles, including intrinsic and extrinsic muscles spanning the hand and forearm. The sEMG signals were then analyzed using MRNs and WNs. Interlayer mutual information ( I ) and average edge overlap ( ω ) of MRNs and average shortest path length ( L ) of WNs were computed and compared across groups for grasp types (grip vs. pinch) and force levels (30%, 50% and 70% MVC). Results showed that the extrinsic, rather than the intrinsic muscles, had significant differences in network parameters between both grasp types ( ), and force levels ( ), and especially at higher force levels. Furthermore, I and ω were strengthened over time ( ) except with pinch at 30% MVC. Results suggest that the central nervous system (CNS) actively increases cortical oscillations over time in response to increasing force levels and changes in force production with different sustained grasping types. Muscle coupling in extrinsic muscles was higher than in intrinsic muscles for both grip and pinch. The MRNs may be a valuable tool to provide greater insights into inter-muscular coordination patterns of clinical populations, assess neuromuscular function, or stabilize force control in prosthetic hands.

A Systematic Review of EMG Applications for the Characterization of Forearm and Hand Muscle Activity during Activities of Daily Living: Results, Challenges, and Open Issues

The role of the hand is crucial for the performance of activities of daily living, thereby ensuring a full and autonomous life. Its motion is controlled by a complex musculoskeletal system of approximately 38 muscles. Therefore, measuring and interpreting the muscle activation signals that drive hand motion is of great importance in many scientific domains, such as neuroscience, rehabilitation, physiotherapy, robotics, prosthetics, and biomechanics. Electromyography (EMG) can be used to carry out the neuromuscular characterization, but it is cumbersome because of the complexity of the musculoskeletal system of the forearm and hand. This paper reviews the main studies in which EMG has been applied to characterize the muscle activity of the forearm and hand during activities of daily living, with special attention to muscle synergies, which are thought to be used by the nervous system to simplify the control of the numerous muscles by actuating them in task-relevant subgroups. The state of the art of the current results are presented, which may help to guide and foster progress in many scientific domains. Furthermore, the most important challenges and open issues are identified in order to achieve a better understanding of human hand behavior, improve rehabilitation protocols, more intuitive control of prostheses, and more realistic biomechanical models.

Force Steadiness: From Motor Units to Voluntary Actions

Voluntary actions are controlled by the synaptic inputs that are shared by pools of spinal motor neurons. The slow common oscillations in the discharge times of motor units due to these synaptic inputs are strongly correlated with the fluctuations in force during submaximal isometric contractions (force steadiness) and moderately associated with performance scores on some tests of motor function. However, there are key gaps in knowledge that limit the interpretation of differences in force steadiness.

Usefulness of Muscle Synergy Analysis in Individuals With Knee Osteoarthritis During Gait

OBJECTIVE

To clarify whether there are any muscle synergy changes in individuals with knee osteoarthritis, and to determine whether muscle synergy analysis could be applied to other musculoskeletal diseases.

METHODS

Subjects in this study included 11 young controls (YC), 10 elderly controls (EC), and 10 knee osteoarthritis patients (KOA). Gait was assessed on a split-belt treadmill at 3 km/h. A non-negative matrix factorization (NNMF) was applied to the electromyogram data matrix to extract muscle synergies. To assess the similarity of each module, we performed the NNMF analysis assuming four modules for all of the participants. Further, we calculated joint angles to compare the kinematic data between the module groups.

RESULTS

The number of muscle modules was significantly lower in the EC (2-3) and KOA (2-3) groups than in the YC group (3-4), which reflects the merging of late swing and early stance modules. The EC and KOA groups also showed greater knee flexion angles in the early stance phase. Contrarily, by focusing on the module structure, we found that the merging of early and late stance modules is characteristic in KOA.

CONCLUSION

The lower number of modules in the EC and KOA groups was due to the muscle co-contraction with increased knee flexion angle. Contrarily, the merging of early and late stance modules are modular structures specific to KOA and may be biomarkers for detecting KOA.

SIGNIFICANCE

Describing the changes in multiple muscle control associated with musculoskeletal degeneration can serve as a fundamental biomarker in joint disease.

The effect of wrist posture on extrinsic finger muscle activity during single joint movements

Wrist posture impacts the muscle lengths and moment arms of the extrinsic finger muscles that cross the wrist. As a result, the electromyographic (EMG) activity associated with digit movement at different wrist postures must also change. We sought to quantify the posture-dependence of extrinsic finger muscle activity using bipolar fine-wire electrodes inserted into the extrinsic finger muscles of able-bodied subjects during unrestricted wrist and finger movements across the entire range of motion. EMG activity of all the recorded finger muscles were significantly different (p < 0.05, ANOVA) when performing the same digit movement in five different wrist postures. Depending on the wrist posture, EMG activity changed by up to 70% in individual finger muscles for the same movement, with the highest levels of activity observed in finger extensors when the wrist was extended. Similarly, finger flexors were most active when the wrist was flexed. For the finger flexors, EMG variations with wrist posture were most prominent for index finger muscles, while the EMG activity of all finger extensor muscles were modulated in a similar way across all digits. In addition to comprehensively quantifying the effect of wrist posture on extrinsic finger EMG activity in able-bodied subjects, these results may contribute to designing control algorithms for myoelectric prosthetic hands in the future.

Effects of task dynamics on coordination of the hand muscles and their adaptation to targeted muscle assistance

Dynamic characteristics of a manual task can affect the control of hand muscles due to the difference in biomechanical/physiological characteristics of the muscles and sensory afferents in the hand. We aimed to examine the effects of task dynamics on the coordination of hand muscles, and on the motor adaptation to external assistance. Twenty-four healthy subjects performed one of the two types of a finger extension task, isometric dorsal fingertip force production (static) or isokinetic finger extension (dynamic). Subjects performed the tasks voluntarily without assistance, or with a biomimetic exotendon providing targeted assistance to their extrinsic muscles. In unassisted conditions, significant between-task differences were found in the coordination of the extrinsic and intrinsic hand muscles, while the extrinsic muscle activities were similar between the tasks. Under assistance, while the muscle coordination remained relatively unaffected during the dynamic task, significant changes in the coordination between the extrinsic and intrinsic muscles were observed during the static task. Intermuscular coherence values generally decreased during the static task under assistance, but increased during the dynamic task (all p-values < 0.01). Additionally, a significant change in the task dynamics was induced by assistance only during static task. Our study showed that task type significantly affect coordination between the extrinsic and intrinsic hand muscles. During the static task, a lack of sensory information from musculotendons and joint receptors (more sensitive to changes in length/force) is postulated to have resulted in a neural decoupling between muscles and a consequent isolated modulation of the intrinsic muscle activity.

Effects of kinematic complexity and number of muscles on musculoskeletal model robustness to muscle dysfunction

The robustness of motor outputs to muscle dysfunction has been investigated using musculoskeletal modeling, but with conflicting results owing to differences in model complexity and motor tasks. Our objective was to systematically study how the number of kinematic degrees of freedom, and the number of independent muscle actuators alter the robustness of motor output to muscle dysfunction. We took a detailed musculoskeletal model of the human leg and systematically varied the model complexity to create six models with either 3 or 7 kinematic degrees of freedom and either 14, 26, or 43 muscle actuators. We tested the redundancy of each model by quantifying the reduction in sagittal plane feasible force set area when a single muscle was removed. The robustness of feasible force set area to the loss of any single muscle, i.e. general single muscle loss increased with the number of independent muscles and decreased with the number of kinematic degrees of freedom, with the robust area varying from 1% and 52% of the intact feasible force set area. The maximum sensitivity of the feasible force set to the loss of any single muscle varied from 75% to 26% of the intact feasible force set area as the number of muscles increased. Additionally, the ranges of feasible muscle activation for maximum force production were largely unconstrained in many cases, indicating ample musculoskeletal redundancy even for maximal forces. We propose that ratio of muscles to kinematic degrees of freedom can be used as a rule of thumb for estimating musculoskeletal redundancy in both simulated and real biomechanical systems.

Improving Reliability of Myocontrol Using Formal Verification

In the context of assistive robotics, myocontrol is one of the so-far unsolved problems of upper-limb prosthetics. It consists of swiftly, naturally, and reliably converting biosignals, non-invasively gathered from an upper-limb disabled subject, into control commands for an appropriate self-powered prosthetic device. Despite decades of research, traditional surface electromyography cannot yet detect the subject's intent to an acceptable degree of reliability, that is, enforce an action exactly when the subject wants it to be enforced.. In this paper, we tackle one such kind of mismatch between the subject's intent and the response by the myocontrol system, and show that formal verification can indeed be used to mitigate it. Eighteen intact subjects were engaged in two target achievement control tests in which a standard myocontrol system was compared to two "repaired" ones, one based on a non-formal technique, thus enforcing no guarantee of safety, and the other using the satisfiability modulo theories (SMT) technology to rigorously enforce the desired property. The experimental results indicate that both repaired systems exhibit better reliability than the non-repaired one. The SMT-based system causes only a modest increase in the required computational resources with respect to the non-formal technique; as opposed to this, the non-formal technique can be easily implemented in existing myocontrol systems, potentially increasing their reliability.

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).

A Classification Method for Myoelectric Control of Hand Prostheses Inspired by Muscle Coordination

Dexterous upper limb myoelectric prostheses can, to some extent, restore the motor functions lost after an amputation. However, ensuring the reliability of myoelectric control is still an open challenge. In this paper, we propose a classification method that exploits the regularity in muscle activation patterns (uniform scaling) across different force levels within a given movement class. This assumption leads to a simple training procedure, using training data collected at single contraction intensity for each movement class. The proposed method was compared to the widely accepted benchmark [linear discriminant analysis (LDA) classifier] using off-line and online evaluation. The off-line classification errors obtained with the new method were either lower or higher than LDA depending upon the chosen feature set. In the online evaluation, the new classification method was operated using amplitude-EMG features and compared to the state-of-the-art LDA classifier combined with the time domain feature set. The online evaluation was performed in 11 able-bodied and one amputee subject using a set of four functional tasks mimicking daily-life activities. The tasks assessed the dexterity (e.g., switching between functions) and robustness of control (e.g., handling heavy objects). With the new classification scheme, the amputee performed better in all functional tasks, whereas the able-bodied subjects performed significantly better in three out of four functional tasks. Overall, the novel method outperformed the state-of-the-art approach (LDA) while utilizing less training data and a smaller feature set. The proposed method is, therefore, a simple but effective and robust classification scheme, convenient for online implementation and clinical use.

Neck muscle biomechanics and neural control

The mechanics, morphometry, and geometry of our joints, segments, and muscles are fundamental biomechanical properties intrinsic to human neural control. The goal of our study was to investigate whether the biomechanical actions of individual neck muscles predict their neural control. Specifically, we compared the moment direction and variability produced by electrical stimulation of a neck muscle (biomechanics) to the preferred activation direction and variability (neural control). Subjects sat upright with their head fixed to a six-axis load cell and their torso restrained. Indwelling wire electrodes were placed into the sternocleidomastoid (SCM), splenius capitis (SPL), and semispinalis capitis (SSC) muscles. The electrically stimulated direction was defined as the moment direction produced when a current (2-19 mA) was passed through each muscle's electrodes. Preferred activation direction was defined as the vector sum of the spatial tuning curve built from root mean squared electromyogram when subjects produced isometric moments at 7.5% and 15% of their maximum voluntary contraction (MVC) in 26 three-dimensional directions. The spatial tuning curves at 15% MVC were well defined (unimodal, P < 0.05), and their preferred directions were 23°, 39°, and 21° different from their electrically stimulated directions for the SCM, SPL, and SSC, respectively ( P < 0.05). Intrasubject variability was smaller in electrically stimulated moment directions compared with voluntary preferred directions, and intrasubject variability decreased with increased activation levels. Our findings show that the neural control of neck muscles is not based solely on optimizing individual muscle biomechanics but, as activation increases, biomechanical constraints in part dictate the activation of synergistic neck muscles. NEW & NOTEWORTHY Biomechanics are an intrinsic part of human neural control. In this study, we found that the biomechanics of individual neck muscles cannot fully predict their neural control. Consequently, physiologically based computational neck muscle controllers cannot calculate muscle activation schemes based on the isolated biomechanics of muscles. Furthermore, by measuring biomechanics we showed that the intrasubject variability of the neural control was lower for electrical vs. voluntary activation of the neck muscles.

Impact of Targeted Assistance of Multiarticular Finger Musculotendons on the Coordination of Finger Muscles During Isometric Force Production

Neurological injuries often cause degraded motor control. While rehabilitation efforts typically focus on movement kinematics, abnormal muscle activation patterns are often the primary source of impairment. Muscle-based therapies are likely more effective than joint-based therapy. In this paper, we examined the feasibility of biomimetic input mimicking the action of human musculotendons in altering hand muscle coordination. Twelve healthy subjects produced a submaximal isometric dorsal fingertip force, while a custom actuator provided assistance mirroring the actions of either the extrinsic extensor or the intrinsic muscles of the index finger. The biomimetic inputs reduced the activation level of all task-related muscles, but the degree of change was different across the muscles, resulting in significant changes in their coordination (co-contraction ratios) and force-electromyography correlations. Each biomimetic assistance particularly increased the neural coupling between its targeted muscle and the antagonist muscle. Subjects appeared to fully take advantage of the assistance, as they provided minimal level of effort to achieve the task goal. The targeted biomimetic assistance may be used to retrain activation patterns post-stroke by effectively modulating connectivity between the muscles in the functional context and could be beneficial to restore hand function and reduce disability.

Modular Organization of Exploratory Force Development Under Isometric Conditions in the Human Arm

Muscle coordination of isometric force production can be explained by a smaller number of modules. Variability in force output, however, is higher during exploratory/transient force development phases than force maintenance phase, and it is not clear whether the same modular structure underlies both phases. In this study, eight neurologically-intact adults isometrically performed target force matches in 54 directions at hands, and electromyographic (EMG) data from eight muscles were parsed into four sequential phases. Despite the varying degree of motor complexity across phases (significant between-phase differences in EMG-force correlation, angular errors, and between-force correlations), the number/composition of motor modules were found equivalent across phases, suggesting that the CNS systematically modulated activation of the same set of motor modules throughout sequential force development.

Intermuscular coherence reflects functional coordination

Coherence analysis has the ability to identify the presence of common descending drive shared by motor unit pools and reveals its spectral properties. However, the link between spectral properties of shared neural drive and functional interactions among muscles remains unclear. We assessed shared neural drive between muscles of the thumb and index finger while participants executed two mechanically distinct precision pinch tasks, each requiring distinct functional coordination among muscles. We found that shared neural drive was systematically reduced or enhanced at specific frequencies of interest (~10 and ~40 Hz). While amplitude correlations between surface EMG signals also exhibited changes across tasks, only their coherence has strong physiological underpinnings indicative of neural binding. Our results support the use of intermuscular coherence as a tool to detect when coactivated muscles are members of a functional group or synergy of neural origin. Furthermore, our results demonstrate the advantages of considering neural binding at 10, ~20, and >30 Hz, as indicators of task-dependent neural coordination strategies.NEW & NOTEWORTHY It is often unclear whether correlated activity among muscles reflects their neural binding or simply reflects the constraints defining the task. Using the fact that high-frequency coherence between EMG signals (>6 Hz) is thought to reflect shared neural drive, we demonstrate that coherence analysis can reveal the neural origin of distinct muscle coordination patterns required by different tasks.

Hand Posture Prediction Using Neural Networks within a Biomechanical Model

This paper proposes the use of artificial neural networks (ANNs) in the framework of a biomechanical hand model for grasping. ANNs enhance the model capabilities as they substitute estimated data for the experimental inputs required by the grasping algorithm used. These inputs are the tentative grasping posture and the most open posture during grasping. As a consequence, more realistic grasping postures are predicted by the grasping algorithm, along with the contact information required by the dynamic biomechanical model (contact points and normals). Several neural network architectures are tested and compared in terms of prediction errors, leading to encouraging results. The performance of the overall proposal is also shown through simulation, where a grasping experiment is replicated and compared to the real grasping data collected by a data glove device.

Beta Band Corticomuscular Drive Reflects Muscle Coordination Strategies

During force production, hand muscle activity is known to be coherent with activity in primary motor cortex, specifically in the beta-band (15–30 Hz) frequency range. It is not clear, however, if this coherence reflects the control strategy selected by the nervous system for a given task, or if it instead reflects an intrinsic property of cortico-spinal communication. Here, we measured corticomuscular and intermuscular coherence between muscles of index finger and thumb while a two-finger pinch grip of identical net force was applied to objects which were either stable (allowing synergistic activation of finger muscles) or unstable (requiring individuated finger control). We found that beta-band corticomuscular coherence with the first dorsal interosseous (FDI) and abductor pollicis brevis (APB) muscles, as well as their beta-band coherence with each other, was significantly reduced when individuated control of the thumb and index finger was required. We interpret these findings to show that beta-band coherence is reflective of a synergistic control strategy in which the cortex binds task-related motor neurons into functional units.

Visual and Tactile Guidance of Dexterous Manipulation Tasks: An fMRI Study

Models of motor guidance that dynamically adjust to the availability and quality of sensory information are based on the observation that dexterous tasks are routinely performed using various combinations of visual and tactile inputs. However, a dynamic neural system that acquires and processes relevant visual and tactile information remains relatively uncharacterized in humans. In this study, whole-brain functional magnetic resonance images were acquired during a dexterous manipulation task, compression of the end caps of a slender spring prone to buckling, to investigate the neural systems associated with motor guidance under four visual and tactile guidance conditions: (1) eyes closed (no visual input), smooth end caps, (2) eyes closed, rough end caps, (3) eyes open and watching hand, smooth end caps, and (4) eyes open and watching hand, rough end caps. Performance of the dexterous task remained constant in all conditions. Variations in the two levels of visual input resulted in modulation of activity in the middle and inferior occipital gyrii and inferior parietal lobule, and variation in the two levels of tactile input during the task resulted in modulation of activity in the precentral (primary motor) gyrus. Although significantly active in all conditions, cingulate gyrus, medial frontal gyrus, postcentral gyrus, and cerebellum activities were not modulated by levels of either visual or somatosensory input, and no interaction effects were observed. Together, these data indicate that a fine-tuned motor task guided by varying visual and tactile information engages a distributed and integrated neural complex consisting of control and executive functions and regions that process dynamic sensory information related to guidance functions.

The Dynamics of Voluntary Force Production in Afferented Muscle Influence Involuntary Tremor

Voluntary control of force is always marked by some degree of error and unsteadiness. Both neural and mechanical factors contribute to these fluctuations, but how they interact to produce them is poorly understood. In this study, we identify and characterize a previously undescribed neuromechanical interaction where the dynamics of voluntary force production suffice to generate involuntary tremor. Specifically, participants were asked to produce isometric force with the index finger and use visual feedback to track a sinusoidal target spanning 5-9% of each individual's maximal voluntary force level. Force fluctuations and EMG activity over the flexor digitorum superficialis (FDS) muscle were recorded and their frequency content was analyzed as a function of target phase. Force variability in either the 1-5 or 6-15 Hz frequency ranges tended to be largest at the peaks and valleys of the target sinusoid. In those same periods, FDS EMG activity was synchronized with force fluctuations. We then constructed a physiologically-realistic computer simulation in which a muscle-tendon complex was set inside of a feedback-driven control loop. Surprisingly, the model sufficed to produce phase-dependent modulation of tremor similar to that observed in humans. Further, the gain of afferent feedback from muscle spindles was critical for appropriately amplifying and shaping this tremor. We suggest that the experimentally-induced tremor may represent the response of a viscoelastic muscle-tendon system to dynamic drive, and therefore does not fall into known categories of tremor generation, such as tremorogenic descending drive, stretch-reflex loop oscillations, motor unit behavior, or mechanical resonance. Our findings motivate future efforts to understand tremor from a perspective that considers neuromechanical coupling within the context of closed-loop control. The strategy of combining experimental recordings with physiologically-sound simulations will enable thorough exploration of neural and mechanical contributions to force control in health and disease.

Assessing Finger Joint Biomechanics by Applying Equal Force to Flexor Tendons In Vitro Using a Novel Simultaneous Approach

Background

The flexor digitorum superficialis (FDS) and flexor digitorum profundus (FDP) are critical for finger flexion. Although research has recently focused on these tendons’ coactivity, their contributions in different tasks remain unclear. This study created a novel simultaneous approach to investigate the coactivity between the tendons and to clarify their contributions in different tasks.

Methods

Ten human cadaveric hands were mounted on our custom frame with the FDS and FDP of the third finger looped through a mechanical pulley connected to a force transducer. Joint range of motion, tendon excursion and loading force were recorded during individual joint motion and free joint movement from rest to maximal flexion. Each flexor tendon’s moment arm was then calculated.

Results

In individual motions, we found that the FDP contributed more than the FDS in proximal interphalangeal (PIP) joint motion, with an overall slope of 1.34 and all FDP-to-FDS excursion (P/S) ratios greater than 1.0 with force increase. However, the FDP contributed less than the FDS in metacarpophalangeal (MCP) joint motion, with an overall slope of 0.95 and P/S ratios smaller than 1.0 throughout the whole motion except between 1.9% and 13.1% force. In free joint movement, the FDP played a greater role than the FDS, with an overall ratio of 1.37 and all P/S ratios greater than 1.0.

Conclusions

The new findings include differences in finger performance and excursion amounts between the FDS and FDP throughout flexion. Such findings may provide the basis for new hand models and treatments.

The Movement- and Load-Dependent Differences in the EMG Patterns of the Human Arm Muscles during Two-Joint Movements (A Preliminary Study)

Slow circular movements of the hand with a fixed wrist joint that were produced in a horizontal plane under visual guidance during conditions of action of the elastic load directed tangentially to the movement trajectory were studied. The positional dependencies of the averaged surface EMGs in the muscles of the elbow and shoulder joints were compared for four possible combinations in the directions of load and movements. The EMG intensities were largely correlated with the waves of the force moment computed for a corresponding joint in the framework of a simple geometrical model of the system: arm - experimental setup. At the same time, in some cases the averaged EMGs exit from the segments of the trajectory restricted by the force moment singular points (FMSPs), in which the moments exhibited altered signs. The EMG activities display clear differences for the eccentric and concentric zones of contraction that are separated by the joint angle singular points (JASPs), which present extreme at the joint angle traces. We assumed that the modeled patterns of FMSPs and JASPs may be applied for an analysis of the synergic interaction between the motor commands arriving at different muscles in arbitrary two-joint movements.

Spatiotemporal distribution of location and object effects in the electromyographic activity of upper extremity muscles during reach-to-grasp

In reaching to grasp an object, proximal muscles that act on the shoulder and elbow classically have been viewed as transporting the hand to the intended location, while distal muscles that act on the fingers simultaneously shape the hand to grasp the object. Prior studies of electromyographic (EMG) activity in upper extremity muscles therefore have focused, by and large, either on proximal muscle activity during reaching to different locations or on distal muscle activity as the subject grasps various objects. Here, we examined the EMG activity of muscles from the shoulder to the hand, as monkeys reached and grasped in a task that dissociated location and object. We quantified the extent to which variation in the EMG activity of each muscle depended on location, on object, and on their interaction-all as a function of time. Although EMG variation depended on both location and object beginning early in the movement, an early phase of substantial location effects in muscles from proximal to distal was followed by a later phase in which object effects predominated throughout the extremity. Interaction effects remained relatively small. Our findings indicate that neural control of reach-to-grasp may occur largely in two sequential phases: the first, serving to project the entire upper extremity toward the intended location, and the second, acting predominantly to shape the entire extremity for grasping the object.

Suboptimal Muscle Synergy Activation Patterns Generalize their Motor Function across Postures

We used a musculoskeletal model to investigate the possible biomechanical and neural bases of using consistent muscle synergy patterns to produce functional motor outputs across different biomechanical conditions, which we define as generalizability. Experimental studies in cats demonstrate that the same muscle synergies are used during reactive postural responses at widely varying configurations, producing similarly-oriented endpoint force vectors with respect to the limb axis. However, whether generalizability across postures arises due to similar biomechanical properties or to neural selection of a particular muscle activation pattern has not been explicitly tested. Here, we used a detailed cat hindlimb model to explore the set of feasible muscle activation patterns that produce experimental synergy force vectors at a target posture, and tested their generalizability by applying them to different test postures. We used three methods to select candidate muscle activation patterns: (1) randomly-selected feasible muscle activation patterns, (2) optimal muscle activation patterns minimizing muscle effort at a given posture, and (3) generalizable muscle activation patterns that explicitly minimized deviations from experimentally-identified synergy force vectors across all postures. Generalizability was measured by the deviation between the simulated force direction of the candidate muscle activation pattern and the experimental synergy force vectors at the test postures. Force angle deviations were the greatest for the randomly selected feasible muscle activation patterns (e.g., >100°), intermediate for effort-wise optimal muscle activation patterns (e.g., ~20°), and smallest for generalizable muscle activation patterns (e.g., <5°). Generalizable muscle activation patterns were suboptimal in terms of effort, often exceeding 50% of the maximum possible effort (cf. ~5% in minimum-effort muscle activation patterns). The feasible muscle activation ranges of individual muscles associated with producing a specific synergy force vector was reduced by ~45% when generalizability requirements were imposed. Muscles recruited in the generalizable muscle activation patterns had less sensitive torque-producing characteristics to changes in postures. We conclude that generalization of function across postures does not arise from limb biomechanics or a single optimality criterion. Muscle synergies may reflect acquired motor solutions globally tuned for generalizability across biomechanical contexts, facilitating rapid motor adaptation.

Proximal arm kinematics affect grip force-load force coordination

During object manipulation, grip force is coordinated with load force, which is primarily determined by object kinematics. Proximal arm kinematics may affect grip force control, as proximal segment motion could affect control of distal hand muscles via biomechanical and/or neural pathways. The aim of this study was to investigate the impact of proximal kinematics on grip force modulation during object manipulation. Fifteen subjects performed three vertical lifting tasks that involved distinct proximal kinematics (elbow/shoulder), but resulted in similar end-point (hand) trajectories. While temporal coordination of grip and load forces remained similar across the tasks, proximal kinematics significantly affected the grip force-to-load force ratio (P = 0.042), intrinsic finger muscle activation (P = 0.045), and flexor-extensor ratio (P < 0.001). Biomechanical coupling between extrinsic hand muscles and the elbow joint cannot fully explain the observed changes, as task-related changes in intrinsic hand muscle activation were greater than in extrinsic hand muscles. Rather, between-task variation in grip force (highest during task 3) appears to contrast to that in shoulder joint velocity/acceleration (lowest during task 3). These results suggest that complex neural coupling between the distal and proximal upper extremity musculature may affect grip force control during movements, also indicated by task-related changes in intermuscular coherence of muscle pairs, including intrinsic finger muscles. Furthermore, examination of the fingertip force showed that the human motor system may attempt to reduce variability in task-relevant motor output (grip force-to-load force ratio), while allowing larger fluctuations in output less relevant to task goal (shear force-to-grip force ratio).

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

The 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.

Altered phalanx force direction during power grip following stroke

Many stroke survivors with severe impairment can grasp only with a power grip. Yet, little knowledge is available on altered power grip after stroke, other than reduced power grip strength. This study characterized stroke survivors' static power grip during 100 and 50 % maximum grip. Each phalanx force angular deviation from the normal direction and its contribution to total normal force was compared for 11 stroke survivors and 11 age-matched controls. Muscle activities and skin coefficient of friction were additionally compared for another 20 stroke and 13 age-matched control subjects. The main finding was that stroke survivors gripped with a 34 % greater phalanx force angular deviation of 19° ± 2° compared to controls of 14° ± 1° (p < .05). Stroke survivors' phalanx force angular deviation was closer to the 23° threshold of slippage between the phalanx and grip surface, which may explain increased likelihood of object dropping in stroke survivors. In addition, this altered phalanx force direction decreases normal grip force by tilting the force vector, indicating a partial role of phalanx force angular deviation in reduced grip strength post-stroke. Greater phalanx force angular deviation may biomechanically result from more severe underactivation of stroke survivors' first dorsal interosseous and extensor digitorum communis muscles compared to their flexor digitorum superficialis or somatosensory deficit. While stroke survivors' maximum power grip strength was approximately half of the controls, the distribution of their remaining strength over the fingers and phalanges did not differ, indicating evenly distributed grip force reduction over the entire hand.

Evidence for altered upper extremity muscle synergies in chronic stroke survivors with mild and moderate impairment

Previous studies indicate that motor coordination may be achieved by assembling task-dependent combinations of a few muscle synergies, defined here as fixed patterns of activation across a set of muscles. Our recent study of severely impaired chronic stroke survivors showed that some muscle synergies underlying isometric force generation at the hand are altered in the affected arm. However, whether similar alterations are evident in stroke survivors with lesser impairment remains unclear. Accordingly, we examined muscle synergies underlying spatial patterns of elbow and shoulder muscle activation recorded during an isometric force target matching protocol performed by 16 chronic stroke survivors, evenly divided across mild and moderate impairment levels. We applied non-negative matrix factorization to identify the muscle synergies and compared their structure across groups, including previously collected data from six age-matched control subjects and eight severely impaired stroke survivors. For all groups, EMG spatial patterns were well explained by task-dependent combinations of only a few (typically 4) muscle synergies. Broadly speaking, elbow-related synergies were conserved across stroke survivors, regardless of impairment level. In contrast, the shoulder-related synergies of some stroke survivors with mild and moderate impairment differed from controls, in a manner similar to severely impaired subjects. Cluster analysis of pooled synergies for the 30 subjects identified seven distinct clusters (synergies). Subsequent analysis confirmed that the incidences of three elbow-related synergies were independent of impairment level, while the incidences of four shoulder-related synergies were systematically correlated with impairment level. Overall, our results suggest that alterations in the shoulder muscle synergies underlying isometric force generation appear prominently in mild and moderate stroke, as in most cases of severe stroke, in an impairment level-dependent manner.

Effects of contraction path and velocity on the coordination of hand muscles during a three-digit force production task

Though many studies indicated that the behavior of single muscle was different between contraction and relaxation, the effect of contraction history profile on multiple muscles has not been investigated. In this study, we analyzed the influence of contraction history on the coordination patterns of hand muscles during a three-digit force production task. The effects of the contraction and relaxation paths with two contraction velocities (5% and 10% maximum voluntary contraction per second) were investigated. The results showed that the force-independent characteristic of muscle coordination patterns still held regardless of the contraction history profiles. In addition, the effect of contraction path was more significant than that of velocity. The study provides a potential way to overcome the impact of contraction disturbance for improving the robustness of the human-machine interface (HMI) based on electromyographic (EMG) pattern recognition.

Are movement disorders and sensorimotor injuries pathologic synergies? When normal multi-joint movement synergies become pathologic

The intact nervous system has an exquisite ability to modulate the activity of multiple muscles acting at one or more joints to produce an enormous range of actions. Seemingly simple tasks, such as reaching for an object or walking, in fact rely on very complex spatial and temporal patterns of muscle activations. Neurological disorders such as stroke and focal dystonia affect the ability to coordinate multi-joint movements. This article reviews the state of the art of research of muscle synergies in the intact and damaged nervous system, their implications for recovery and rehabilitation, and proposes avenues for research aimed at restoring the nervous system’s ability to control movement.

Human-inspired feedback synergies for environmental interaction with a dexterous robotic hand

Effortless control of the human hand is mediated by the physical and neural couplings inherent in the structure of the hand. This concept was explored for environmental interaction tasks with the human hand, and a novel human-inspired feedback synergy (HFS) controller was developed for a robotic hand which synchronized position and force feedback signals to mimic observed human hand motions. This was achieved by first recording the finger joint motion profiles of human test subjects, where it was observed that the subjects would extend their fingers to maintain a natural hand posture when interacting with different surfaces. The resulting human joint angle data were used as inspiration to develop the HFS controller for the anthropomorphic robotic hand, which incorporated finger abduction and force feedback in the control laws for finger extension. Experimental results showed that by projecting a broader view of the tasks at hand to each specific joint, the HFS controller produced hand motion profiles that closely mimic the observed human responses and allowed the robotic manipulator to interact with the surfaces while maintaining a natural hand posture. Additionally, the HFS controller enabled the robotic hand to autonomously traverse vertical step discontinuities without prior knowledge of the environment, visual feedback, or traditional trajectory planning techniques.

Development of a biomimetic hand exotendon device (BiomHED) for restoration of functional hand movement post-stroke

Significant functional impairment of the hand is common among stroke survivors and restoration of hand function should be prioritized during post-stroke rehabilitation. The goal of this study was to develop a novel biomimetic device to assist patients in producing complex hand movements with a limited number of actuators. The Biomimetic Hand Exoskeleton Device (BiomHED) is actuated by exotendons that mimic the geometry of the major tendons of the hand. Ten unimpaired subjects and four chronic stroke survivors participated in experiments that tested the efficacy of the system. The exotendons reproduced distinct spatial joint coordination patterns similar to their target muscle-tendon units for both subject groups. In stroke survivors, the exotendon-produced joint angular displacements were smaller, but not significantly different, than those of unimpaired subjects [Formula: see text]. Even with limited use of the BiomHED, the kinematic workspace of the index finger increased by 63%-1014% in stroke survivors. The device improved the kinematics of the tip-pinch task in stroke survivors and resulted in a significant reduction in the fingertip-thumb tip distance ( 17.9 ±15.3 mm). This device is expected to enable effective "task-oriented" training of the hand post-stroke.

Involuntary contralateral upper extremity muscle activation pattern during unilateral pinch grip following stroke

STUDY DESIGN

Repeated measures design.

INTRODUCTION

Mirror activity refers to emergence of motion not only in the intended, but also in the contralateral limb.

PURPOSE

To characterize post-stroke mirror activities across multiple muscles during unilateral pinch.

METHODS

Chronic stroke survivors performed unilateral pinch grip using the paretic and nonparetic hand, while four muscles' EMGs were recorded for both hands.

RESULTS

During the paretic hand grip, the relaxed nonparetic hand showed mirror activity that was more pronounced for the intrinsic (FDI and thenar eminence) than extrinsic muscles (FDS and EDC). During the nonparetic hand grip, mirror activity in the paretic hand was suppressed for the intrinsic than extrinsic muscles.

CONCLUSION

Chronic stroke survivors' relaxed hand did not mirror the task hand's muscle activation pattern, but displayed altered muscle activation patterns depending on muscles and sides, possibly mediated by disturbed interhemispheric inhibition and relative reliance on corticospinal tracts among muscles.

LEVEL OF EVIDENCE

N/A.

Electromyogram synergy control of a dexterous artificial hand to unscrew and screw objects

BACKGROUND

Due to their limited dexterity, it is currently not possible to use a commercially available prosthetic hand to unscrew or screw objects without using elbow and shoulder movements. For these tasks, prosthetic hands function like a wrench, which is unnatural and limits their use in tight working environments. Results from timed rotational tasks with human subjects demonstrate the clinical need for increased dexterity of prosthetic hands, and a clinically viable solution to this problem is presented for an anthropomorphic artificial hand.

METHODS

Initially, a human hand motion analysis was performed during a rotational task. From these data, human hand synergies were derived and mapped to an anthropomorphic artificial hand. The synergy for the artificial hand is controlled using conventional dual site electromyogram (EMG) signals. These EMG signals were mapped to the developed synergy to control four joints of the dexterous artificial hand simultaneously.Five limb absent and ten able-bodied test subjects participated in a comparison study to complete a timed rotational task as quickly as possible with their natural hands (except for one subject with a bilateral hand absence), eight commercially available prosthetic hands, and the proposed synergy controller. Each test subject used two to four different artificial hands.

RESULTS

With the able-bodied subjects, the developed synergy controller reduced task completion time by 177% on average. The limb absent subjects completed the task faster on average than with their own prostheses by 46%. There was a statistically significant improvement in task completion time with the synergy controller for three of the four limb absent participants with integrated prostheses, and was not statistically different for the fourth.

CONCLUSIONS

The proposed synergy controller reduced average task completion time compared to commercially available prostheses. Additionally, the synergy controller is able to function in a small workspace and requires less physical effort since arm movements are not required. The synergy controller is driven by conventional dual site EMG signals that are commonly used for prosthetic hand control, offering a viable solution for people with an upper limb absence to use a more dexterous artificial hand to screw or unscrew objects.

The effect of arm weight support on upper limb muscle synergies during reaching movements

Background

Compensating for the effect of gravity by providing arm-weight support (WS) is a technique often utilized in the rehabilitation of patients with neurological conditions such as stroke to facilitate the performance of arm movements during therapy. Although it has been shown that, in healthy subjects as well as in stroke survivors, the use of arm WS during the performance of reaching movements leads to a general reduction, as expected, in the level of activation of upper limb muscles, the effects of different levels of WS on the characteristics of the kinematics of motion and of the activity of upper limb muscles have not been thoroughly investigated before.

Methods

In this study, we systematically assessed the characteristics of the kinematics of motion and of the activity of 14 upper limb muscles in a group of 9 healthy subjects who performed 3-D arm reaching movements while provided with different levels of arm WS. We studied the hand trajectory and the trunk, shoulder, and elbow joint angular displacement trajectories for different levels of arm WS. Besides, we analyzed the amplitude of the surface electromyographic (EMG) data collected from upper limb muscles and investigated patterns of coordination via the analysis of muscle synergies.

Results

The characteristics of the kinematics of motion varied across WS conditions but did not show distinct trends with the level of arm WS. The level of activation of upper limb muscles generally decreased, as expected, with the increase in arm WS. The same eight muscle synergies were identified in all WS conditions. Their level of activation depended on the provided level of arm WS.

Conclusions

The analysis of muscle synergies allowed us to identify a modular organization underlying the generation of arm reaching movements that appears to be invariant to the level of arm WS. The results of this study provide a normative dataset for the assessment of the effects of the level of arm WS on muscle synergies in stroke survivors and other patients who could benefit from upper limb rehabilitation with arm WS.

Directional coordination of thumb and finger forces during precision pinch

The human opposable thumb enables the hand to perform dexterous manipulation of objects, which requires well-coordinated digit force vectors. This study investigated the directional coordination of force vectors generated by the thumb and index finger during precision pinch. Fourteen right-handed, healthy subjects were instructed to exert pinch force on an externally stabilized apparatus with the pulps of the thumb and index finger. Subjects applied forces to follow a force-ramp profile that linearly increased from 0 to 12 N and then decreased to 0 N, at a rate of ±3 N/s. Directional relationships between the thumb and index finger force vectors were quantified using the coordination angle (CA) between the force vectors. Individual force vectors were further analyzed according to their projection angles (PAs) with respect to the pinch surface planes and the shear angles (SAs) within those planes. Results demonstrated that fingertip force directions were dependent on pinch force magnitude, especially at forces below 2 N. Hysteresis was observed in the force-CA relationship for increasing and decreasing forces and fitted with exponential models. The fitted asymptotic values were 156.0±6.6° and 150.8±9.3° for increasing and decreasing force ramps, respectively. The PA of the thumb force vector deviated further from the direction perpendicular to the pinching surface planes than that of the index finger. The SA showed that the index finger force vector deviated in the ulnar-proximal direction, whereas the thumb switched its force between the ulnar-proximal and radial-proximal directions. The findings shed light on the effects of anatomical composition, biomechanical function, and neuromuscular control in coordinating digit forces during precision pinch, and provided insight into the magnitude-dependent force directional control which potentially affects a range of dexterous manipulations.

Across-muscle coherence is modulated as a function of wrist posture during two-digit grasping

The purpose of this study was to investigate the extent to which correlated neural inputs, quantified as EMG-EMG coherence across intrinsic and extrinsic hand muscles, varied as a function of wrist angle during a constant force precision grip task. Eight adults (5 males; mean age 29 years) participated in the experiment. Subjects held an object using a two-digit precision grip at a constant force at a flexed, neutral, and extended wrist posture, while the EMG activity from intrinsic and extrinsic hand muscles was recorded through intramuscular fine-wire electrodes. The integral of z-transformed coherence computed across muscles pairs was greatest in the flexed wrist posture and significantly greater than EMG-EMG coherence measured in the neutral and extended wrist posture (P < 0.01 and 0.05, respectively). Furthermore, EMG-EMG coherence did not differ statistically between the extrinsic and intrinsic muscle pairs, even though it tended to be greater for the extrinsic muscle pair (P ≥ 0.063). These findings lend support to the notion of a functional role of correlated neural inputs to hand muscles for the task-dependent coordination of hand muscle activity that is likely mediated by somatosensory feedback.

Impairment in task-specific modulation of muscle coordination correlates with the severity of hand impairment following stroke

Significant functional impairment of the hand is commonly observed in stroke survivors. Our previous studies suggested that the inability to modulate muscle coordination patterns according to task requirements may be substantial after stroke, but these limitations have not been examined directly. In this study, we aimed to characterize post-stroke impairment in the ability to modulate muscle coordination patterns across tasks and its correlation with hand impairment. Fourteen stroke survivors, divided into a group with severe hand impairment (8 subjects) and a group with moderate hand impairment (6 subjects) according to their clinical functionality score, participated in the experiment. Another four neurologically intact subjects participated in the experiment to serve as a point of comparison. Activation patterns of nine hand and wrist muscles were recorded using surface electromyography while the subjects performed six isometric tasks. Patterns of covariation in muscle activations across tasks, i.e., muscle modules, were extracted from the muscle activation data. Our results showed that the degree of reduction in the inter-task separation of the multi-muscle activation patterns was indicative of the clinical functionality score of the subjects (mean value = 26.2 for severely impaired subjects, 38.1 for moderately impaired subjects). The values for moderately impaired subjects were much closer to those of the impaired subjects (mean value = 46.1). The number of muscle modules extracted from the muscle activation patterns of a subject across six tasks, which represents the degree of motor complexity, was found to be correlated with the clinical functionality score (R = 0.68). Greater impairment was also associated with a change in the muscle module patterns themselves, with greater muscle coactivation. A substantial reduction in the degrees-of-freedom of the multi-muscle coordination post-stroke was apparent, and the extent of the reduction, assessed by the stated metrics, was strongly associated with the level of clinical impairment.