Muscle redundancy does not imply robustness to muscle dysfunction

Evolution, biomechanics, and neurobiology converge to explain selective finger motor control

Humans use their fingers to perform a variety of tasks, from simple grasping to manipulating objects, to typing and playing musical instruments, a variety wider than any other species. The more sophisticated the task, the more it involves individuated finger movements, those in which one or more selected fingers perform an intended action while the motion of other digits is constrained. Here we review the neurobiology of such individuated finger movements. We consider their evolutionary origins, the extent to which finger movements are in fact individuated, and the evolved features of neuromuscular control that both enable and limit individuation. We go on to discuss other features of motor control that combine with individuation to create dexterity, the impairment of individuation by disease, and the broad extent of capabilities that individuation confers on humans. We comment on the challenges facing the development of a truly dexterous bionic hand. We conclude by identifying topics for future investigation that will advance our understanding of how neural networks interact across multiple regions of the central nervous system to create individuated movements for the skills humans use to express their cognitive activity.

Older age is associated with decreased overall shoulder strength but not direction-specific differences in the three-dimensional feasible torque space

Shoulder strength is reduced in older adults but has only been assessed in planar motions that do not reflect the diverse requirements of daily tasks. We quantified the impact of age on strength spanning the three degrees of freedom relevant to shoulder function, referred to as the feasible torque space. We hypothesized that the feasible torque space would differ with age and expected this age-effect to reflect direction-specific deficits. We measured strength in 32 directions to characterize the feasible torque space of the shoulder in participants without shoulder pain or tendinous pathology (n = 39, 19-86 years). We modeled the feasible torque space for each participant as an ellipsoid, computed the ellipsoid size and direction-specific metrics (ellipsoid position, orientation, and shape), and then tested the effect of age on each metric. Age was negatively associated with ellipsoid size (a measure of overall strength magnitude; -0.0033 ± 0.0007 (Nm/kg)/year, p < 0.0001). Contrary to our expectation, the effect of age on the direction-specific metrics did not reach statistical significance. The effect of age did not differ significantly between male and female participants. Three-dimensional strength measurements allowed us to constrain the direction of participants' maximum torque production and characterize the entire feasible torque space. Our findings support a generalized shoulder strengthening program to address age-related shoulder weakness in those without pain or pathology. Clinical exam findings of imbalanced weakness may suggest underlying pathology beyond an effect of age. Longitudinal studies are needed to determine the positive or negative impact of our results.

The role of the deep cervical extensor muscles in multi-directional isometric neck strength

Clinical management of whiplash-associated disorders is challenging and often unsuccessful, with over a third of whiplash injuries progressing to chronic neck pain. Previous imaging studies have identified muscle fat infiltration, indicative of muscle weakness, in the deep cervical extensor muscles (multifidus and semispinalis cervicis). Yet, kinematic and muscle redundancy prevent the direct assessment of individual neck muscle strength, making it difficult to determine the role of these muscles in motor dysfunction. The purpose of this study was to determine the effects of deep cervical extensor muscle weakness on multi-directional neck strength and muscle activation patterns. Maximum isometric forces and associated muscle activation patterns were computed in 25 test directions using a 3-joint, 24-muscle musculoskeletal model of the head and neck. The computational approach accounts for differential torques about the upper and lower cervical spine. To facilitate clinical translation, the test directions were selected based on locations where resistance could realistically be applied to the head during clinical strength assessments. Simulation results reveal that the deep cervical extensor muscles are active and contribute to neck strength in directions with an extension component. Weakness of this muscle group leads to complex compensatory muscle activation patterns characterized primarily by increased activation of the superficial extensors and deep upper cervical flexors, and decreased activation of the deep upper cervical extensors. These results provide a biomechanistic explanation for movement dysfunction that can be used to develop targeted diagnostics and treatments for chronic neck pain in whiplash-associated disorders.

Comparison of strength profile representations using musculoskeletal models and their applications in robotics

Musculoskeletal models provide an approach towards simulating the ability of the human body in a variety of human-robot applications. A promising use for musculoskeletal models is to model the physical capabilities of the human body, for example, estimating the strength at the hand. Several methods of modelling and representing human strength with musculoskeletal models have been used in ergonomic analysis, human-robot interaction and robotic assistance. However, it is currently unclear which methods best suit modelling and representing limb strength. This paper compares existing methods for calculating and representing the strength of the upper limb using musculoskeletal models. It then details the differences and relative advantages of the existing methods, enabling the discussion on the appropriateness of each method for particular applications.

Behavioral Motor Performance

The human sensorimotor control system has exceptional abilities to perform skillful actions. We easily switch between strenuous tasks that involve brute force, such as lifting a heavy sewing machine, and delicate movements such as threading a needle in the same machine. Using a structure with different control architectures, the motor system is capable of updating its ability to perform through our daily interaction with the fluctuating environment. However, there are issues that make this a difficult computational problem for the brain to solve. The brain needs to control a nonlinear, nonstationary neuromuscular system, with redundant and occasionally undesired degrees of freedom, in an uncertain environment using a body in which information transmission is subject to delays and noise. To gain insight into the mechanisms of motor control, here we survey movement laws and invariances that shape our everyday motion. We then examine the major solutions to each of these problems in the three parts of the sensorimotor control system, sensing, planning, and acting. We focus on how the sensory system, the control architectures, and the structure and operation of the muscles serve as complementary mechanisms to overcome deviations and disturbances to motor behavior and give rise to skillful motor performance. We conclude with possible future research directions based on suggested links between the operation of the sensorimotor system across the movement stages. © 2024 American Physiological Society. Compr Physiol 14:5179-5224, 2024.

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.

Variation of muscle recruitment during exercises performed below horizontal arm elevation that target the lower trapezius: A repeated measures cross-sectional study on asymptomatic individuals

The gold standard exercise for recruitment of the lower trapezius is the Y prone exercise which is performed above 90° of shoulder elevation. However, clinicians often prescribe exercises that avoid high elevation postures during early stages of rehabilitation. Comparatively little data exists on relative muscle recruitment during lower arm elevation exercises. This study examined the EMG activity of four shoulder girdle muscles during four exercises accomplished below 90° of shoulder elevation and compared them to the Y prone while considering sex effects. Variance across exercises of the ratio between upper trapezius and lower trapezius was also explored. 32 healthy participants completed standardized muscle-specific MVCs and two repetitions of each exercise. The side lying external rotation and the wall slide exercises produced the highest peak EMG for the lower trapezius, both 33 and 29% lower than the Y Prone. For the upper trapezius to lower trapezius ratio, the side lying external rotation elicited the lowest value, followed by the Y prone and wall slide (53 and 59% respectively higher). Sex influenced some EMG values, typically interacting with exercise type. Thus, side lying external rotation and the wall slide are recommended for targeting the lower trapezius muscle during early rehabilitation.

Alterations in motor modules and their contribution to limitations in force control in the upper extremity after stroke

The generation of isometric force at the hand can be mediated by activating a few motor modules. Stroke induces alterations in motor modules underlying steady-state isometric force generation in the human upper extremity (UE). However, how the altered motor modules impact task performance (force production) remains unclear as stroke survivors develop and converge to the three-dimensional (3D) target force. Thus, we tested whether stroke-specific motor modules would be activated from the onset of force generation and also examined how alterations in motor modules would induce changes in force representation. During 3D isometric force development, electromyographic (EMG) signals were recorded from eight major elbow and shoulder muscles in the paretic arm of 10 chronic hemispheric stroke survivors and both arms of six age-matched control participants. A non-negative matrix factorization algorithm identified motor modules in four different time windows: three “exploratory” force ramping phases (Ramps 1–3; 0–33%, 33–67%, and 67–100% of target force magnitude, respectively) and the stable force match phase (Hold). Motor module similarity and between-force coupling were examined by calculating the scalar product and Pearson correlation across the phases. To investigate the association between the end-point force representation and the activation of the motor modules, principal component analysis (PCA) and multivariate multiple linear regression analyses were applied. In addition, the force components regressed on the activation profiles of motor modules were utilized to model the feasible force direction. Both stroke and control groups developed exploratory isometric forces with a non-linear relationship between EMG and force. During the force matching, only the stroke group showed abnormal between-force coupling in medial-lateral and backward-forward and medial-lateral and downward-upward directions. In each group, the same motor modules, including the abnormal deltoid module in stroke survivors, were expressed from the beginning of force development instead of emerging during the force exploration. The PCA and the multivariate multiple linear regression analyses showed that alterations in motor modules were associated with abnormal between-force coupling and limited feasible force direction after stroke. Overall, these results suggest that alterations in intermuscular coordination contribute to the abnormal end-point force control under isometric conditions in the UE after stroke.

Estimation of Hand Grip Strength Using Foot motion Measured by In-shoe Motion Sensor

There is a strong need to assess frailty in daily living. Hand grip strength (HGS) has been proven to be a very important factor for identifying frailty, however it is always assessed under the guidance of facility clinicians. Our purpose is to demonstrate the possibility of providing HGS estimation by using foot-motion signals measured by an in-shoe motion sensor (IMS) embedded in an insole to achieve high precision HGS assessment in daily living. The foot-motion signals were collected from 62 elder participants (27 men and 35 women). Their HGSs were assessed by a hand dynamometer. Gait parameters, individual properties, and predictors derived from foot-motion signal features in one gait cycle were selected as candidates. Statistical parametric mapping analyses were used to generate predictors from the foot-motion signals. Prior to estimation construction, least absolute shrinkage and selection operator was applied to reduce redundant predictors from candidates. Linear regression models for HGS estimation of men and women were constructed. As the results, we discovered new effective predictors for HGS estimation from foot motions and successfully constructed HGS estimation models that achieved "excellent" agreement with the reference according to intra-class coefficients, and mean absolute errors of 2.96 and 2.57 kg for men and women in leave-one-subject-out cross-validation, respectively. These results suggest that HGS can be estimated with high precision by IMS-measured foot motion and more effective frailty identification in daily living is possible through wearing an IMS.

Design and Evaluation of a Knee Flexion Assistance Exoskeleton for People with Transtibial Amputation

People with below-knee amputation walk with asymmetric gaits that over time can lead to further musculoskeletal disorders and decreased quality of life. While prosthesis technology is improving, prosthetic ankles may be fundamentally limited in their ability to restore healthy walking patterns because they do not assist the residual knee joint. The knee on the residual limb has muscular deficits due to the loss of the gastrocnemius, a biarticular muscle that crosses both the ankle and knee. Here we present the design, development, and preliminary evaluation of a robotic knee exoskeleton for people with transtibial amputation. The device is intended to restore gastrocnemius-like flexion moments to the knee on the residual limb. The exoskeleton uses a custom offboard actuation and control system to allow for a simple and lightweight design with high torque capabilities. A preliminary walking experiment with one person with transtibial amputation was conducted. The exoskeleton provided a range of knee flexion torque profiles and had an RMS tracking error of 1.9 Nm across four assistance conditions. This device will be used in future studies to explore the effects of providing knee flexion assistance to people with transtibial amputation during walking. Long term, findings from studies with this exoskeleton could motivate future assistive device designs that improve walking mechanics and quality of life for people with limb loss.

Determination of muscle strength and function in plesiosaur limbs: finite element structural analyses of Cryptoclidus eurymerus humerus and femur

Background

The Plesiosauria (Sauropterygia) are secondary marine diapsids. They are the only tetrapods to have evolved hydrofoil fore- and hindflippers. Once this specialization of locomotion had evolved, it remained essentially unchanged for 135 Ma. It is still controversial whether plesiosaurs flew underwater, rowed, or used a mixture of the two modes of locomotion. The long bones of Tetrapoda are functionally loaded by torsion, bending, compression, and tension during locomotion. Superposition of load cases shows that the bones are loaded mainly by compressive stresses. Therefore, it is possible to use finite element structure analysis (FESA) as a test environment for loading hypotheses. These include muscle reconstructions and muscle lines of action (LOA) when the goal is to obtain a homogeneous compressive stress distribution and to minimize bending in the model. Myological reconstruction revealed a muscle-powered flipper twisting mechanism. The flippers of plesiosaurs were twisted along the flipper length axis by extensors and flexors that originated from the humerus and femur as well as further distal locations.

Methods

To investigate locomotion in plesiosaurs, the humerus and femur of a mounted skeleton of Cryptoclidus eurymerus (Middle Jurassic Oxford Clay Formation from Britain) were analyzed using FE methods based on the concept of optimization of loading by compression. After limb muscle reconstructions including the flipper twisting muscles, LOA were derived for all humerus and femur muscles of Cryptoclidus by stretching cords along casts of the fore- and hindflippers of the mounted skeleton. LOA and muscle attachments were added to meshed volumetric models of the humerus and femur derived from micro-CT scans. Muscle forces were approximated by stochastic iteration and the compressive stress distribution for the two load cases, "downstroke" and "upstroke", for each bone were calculated by aiming at a homogeneous compressive stress distribution.

Results

Humeral and femoral depressors and retractors, which drive underwater flight rather than rowing, were found to exert higher muscle forces than the elevators and protractors. Furthermore, extensors and flexors exert high muscle forces compared to Cheloniidae. This confirms a convergently evolved myological mechanism of flipper twisting in plesiosaurs and complements hydrodynamic studies that showed flipper twisting is critical for efficient plesiosaur underwater flight.

Comparison of Optimization Strategies for Musculoskeletal Modeling of the Wrist for Therapy Planning in Case of Total Wrist Arthroplasty

The human wrist joint is an elegant mechanism. The wrist allows the positioning and orienting of the hand to the forearm. The computational modeling of the human hand, especially of the wrist joint, can reveal important information about biomechanical mechanisms and provide the basis for its dysfunction and pathologies. For instance, this could be used for therapy planning in total wrist arthroplasty (TWA). In this study, different optimization methods and sensitivity analyses of anatomical parameters for musculoskeletal modeling were presented. Optimization includes finding the best available value of an objective function, including a variety of different types of objective functions. In the simplest case, optimization consists of maximizing or minimizing a function by systematically choosing input values from within an allowed set and computing the value of the function. Optimization techniques are used in many facets, such as the model building of joints or joint systems such as the wrist. The purpose of this study is to show the variability and influence of the included information for modeling, investigating the biomechanical function and load situation of the joint in representative scenarios. These possibilities to take them into account by an optimization and seem essential for the application of computational modeling to joint pathologies.

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

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

Number of synergies impacts sensitivity of gait to weakness and contracture

Muscle activity during gait can be described by a small set of synergies, weighted groups of muscles, that are theorized to reflect underlying neural control. For people with neurologic injuries, like cerebral palsy or stroke, even fewer synergies are required to explain muscle activity during gait. This reduction in synergies is thought to reflect altered control and is associated with impairment severity and treatment outcomes. Individuals with neurologic injuries also develop secondary musculoskeletal impairments, like weakness or contracture, that can impact gait. Yet, the combined impacts of altered control and musculoskeletal impairments on gait remains unclear. In this study, we use a two-dimensional musculoskeletal model constrained to synergy control to simulate unimpaired gait. We vary the number of synergies, while simulating muscle weakness and contracture to examine how altered control impacts sensitivity to musculoskeletal impairment while tracking unimpaired gait. Results demonstrate that reducing the number of synergies increases sensitivity to weakness and contracture for specific muscle groups. For example, simulations using five-synergy control tolerated 40% and 51% more knee extensor weakness than those using four- or three-synergy control, respectively. Furthermore, when constrained to four- or three-synergy control, the model was increasingly sensitive to contracture and weakness of proximal muscles, such as the hamstring and hip flexors. Contrastingly, neither the amount of generalized nor plantarflexor weakness tolerated was affected by the number of synergies. These findings highlight the interactions between altered control and musculoskeletal impairments, emphasizing the importance of measuring and incorporating both in future simulation and experimental studies.

Experimentally quantifying the feasible torque space of the human shoulder

Daily tasks rely on our ability to generate multi-dimensional shoulder torques. When function is limited, strength assessments are used to identify impairments and guide treatment. However, these assessments are often one-dimensional and limited in their sensitivity to diagnose shoulder pathology. To address these limitations, we have proposed novel metrics to quantify shoulder torque capacity in all directions. To quantify the feasible torque space of the shoulder, we measured maximal volitional shoulder torques in 32 unique directions and fit an ellipsoid model to these data. This ellipsoid model was used to quantify overall strength magnitude, strength balance, and the directions in which participants were strongest and weakest. We used these metrics to characterize three-dimensional shoulder strength in healthy adults and demonstrated their repeatability across days. Finally, using musculoskeletal simulations, we showed that our proposed metrics can distinguish between changes in muscle strength associated with aging or rotator cuff tears and quantified the influence of altered experimental conditions on this diagnostic capacity. Our results demonstrate that the proposed metrics can robustly quantify the feasible torque space of the shoulder and may provide a clinically useful description of the functional capacity of the shoulder in health and disease.

Simulation-based biomechanical assessment of unpowered exoskeletons for running

Due to the complexity and high degrees of freedom, the detailed assessment of human biomechanics is necessary for the design and optimization of an effective exoskeleton. In this paper, we present full kinematics, dynamics, and biomechanics assessment of unpowered exoskeleton augmentation for human running gait. To do so, the considered case study is the assistive torque profile of I-RUN. Our approach is using some extensive data-driven OpenSim simulation results employing a generic lower limb model with 92-muscles and 29-DOF. In the simulation, it is observed that exoskeleton augmentation leads to \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$4.62\%$$\end{document}4.62% metabolic rate reduction for the stiffness coefficient of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\alpha ^*=0.6$$\end{document}α∗=0.6. Moreover, this optimum stiffness coefficient minimizes the biological hip moment by \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$26\%$$\end{document}26%. The optimum stiffness coefficient (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\alpha ^*=0.6$$\end{document}α∗=0.6) also reduces the average force of four major hip muscles, i.e., Psoas, Gluteus Maximus, Rectus Femoris, and Semimembranosus. The effect of assistive torque profile on the muscles’ fatigue is also studied. Interestingly, it is observed that at \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\alpha ^{\#}=0.8$$\end{document}α#=0.8, both all 92 lower limb muscles’ fatigue and two hip major mono-articular muscles’ fatigue have the maximum reduction. This result re-confirm our hypothesis that ”reducing the forces of two antagonistic mono-articular muscles is sufficient for involved muscles’ total fatigue reduction.” Finally, the relation between the amount of metabolic rate reduction and kinematics of hip joint is examined carefully where for the first time, we present a reliable kinematic index for prediction of the metabolic rate reduction by I-RUN augmentation. This index not only explains individual differences in metabolic rate reduction but also provides a quantitative measure for training the subjects to maximize their benefits from I-RUN.

Cycling Biomechanics and Its Relationship to Performance

State-of-the-art biomechanical laboratories provide a range of tools that allow precise measurements of kinematic, kinetic, motor and physiologic characteristics. Force sensors, motion capture devices and electromyographic recording measure the forces exerted at the pedal, saddle, and handlebar and the joint torques created by muscle activity. These techniques make it possible to obtain a detailed biomechanical analysis of cycling movements. However, despite the reasonable accuracy of such measures, cycling performance remains difficult to fully explain. There is an increasing demand by professionals and amateurs for various biomechanical assessment services. Most of the difficulties in understanding the link between biomechanics and performance arise because of the constraints imposed by the bicycle, human physiology and musculo-skeletal system. Recent studies have also pointed out the importance of evaluating not only output parameters, such as power output, but also intrinsic factors, such as the cyclist coordination. In this narrative review, we present various techniques allowing the assessment of a cyclist at a biomechanical level, together with elements of interpretation, and we show that it is not easy to determine whether a certain technique is optimal or not.

Muscle synergy for upper limb damping behavior during object transport while walking in healthy young individuals

Transporting an object during locomotion is one of the most common activities humans perform. Previous studies have shown that continuous and predictive control of grip force, along with the inertial load force of the object, is required to complete this task successfully. Another possible CNS strategy to ensure the dynamic stability of the upper limb is to modify the apparent stiffness and damping via altered muscle activation patterns. In this study, the term damping was used to describe a reduction in upper limb vertical oscillation amplitude to maintain the orientation of the hand-held object. The goal of this study was to identify the neuromuscular strategy for controlling the upper limb during object transport while walking. Three-dimensional kinematic and surface electromyography (EMG) data were recorded from eight, right-handed, healthy young adults who were instructed to walk on a treadmill while carrying an object in their dominant/non-dominant hand, with dominant/non-dominant arm positioning but without an object, and without any object or instructed arm-positioning. EMG recordings from the dominant and non-dominant arms were decomposed separately into underlying muscle synergies using non-negative matrix factorization (NNMF). Results revealed that the dominant arm showed higher damping compared to the non-dominant arm. All muscles showed higher mean levels of activation during object transport except for posterior deltoid (PD), with activation peaks occurring around or slightly before heel contact. The muscle synergy analysis revealed an anticipatory stabilization of the shoulder and elbow joints through a proximal-to-distal muscle activation pattern. These activations appear to play an essential role in maintaining the stability of the carried object in addition to the adjustment of grip force against the perturbations caused by heel contact during walking.

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.

A parametric study of effect of experimental tibialis posterior muscle pain on joint loading and muscle forces-Implications for patients with rheumatoid arthritis?

BACKGROUND

Foot pain and deformities are commonly encountered in patients with rheumatoid arthritis (RA). Likewise, Posterior tibial tendon dysfunction (PTTD) is commonly involved in development of foot and ankle abnormalities and has been reported with a prevalence in two-thirds of the RA patients.

RESEARCH QUESTION

Redundancy in the physiological function between different muscles provides the central nervous system multiple options to perform the same movement but which muscles compensate for the impairment of the tibialis posterior (TP) muscle? And how does these changes affect ankle joint loading?

METHODS

Experimental and computational disciplines were applied to investigate changes in muscle forces as result of induced pain in the right TP muscle. Twelve healthy subjects were enrolled in the study. Experimental pain was induced in the TP by a single ultrasound graphically guided injection of 1 mL hypertonic saline (5.0% Sodium Chloride). The participants' gait was assessed by skin marker-based motion capture and force plates. Musculoskeletal models were used to investigate compensation mechanisms systematically in the lower under extremity when TP muscle was recruited less as a consequence of the induced pain.

RESULTS

Experimental TP muscle pain and simulated reduced strength caused altered muscle recruitment and made the flexor digitorum longus and flexor hallucis longus muscles compensated for the impairment of the TP muscle. Further, the resultant ankle joint force was increased as the strength of the TP muscle was reduced.

SIGNIFICANCE

The compensation mechanism observed in the present study indicate that alterations in muscle recruitment and muscle force distribution as a result of the underlying disease inflammation itself may contribute to development of chronic foot pain and deformities in patients with RA. Further studies are required to understand the role of PTTD in occurrence of those late adverse musculoskeletal manifestations aiming at search for early preventive strategies.

Analyzing Moment Arm Profiles in a Full-Muscle Rat Hindlimb Model

Understanding the kinematics of a hindlimb model is a fundamental aspect of modeling coordinated locomotion. This work describes the development process of a rat hindlimb model that contains a complete muscular system and incorporates physiological walking data to examine realistic muscle movements during a step cycle. Moment arm profiles for selected muscles are analyzed and presented as the first steps to calculating torque generation at hindlimb joints. A technique for calculating muscle moment arms from muscle attachment points in a three-dimensional (3D) space has been established. This model accounts for the configuration of adjacent joints, a critical aspect of biarticular moment arm analysis that must be considered when calculating joint torque. Moment arm profiles from isolated muscle motions are compared to two existing models. The dependence of biarticular muscle's moment arms on the configuration of the adjacent joint is a critical aspect of moment arm analysis that must be considered when calculating joint torque. The variability in moment arm profiles suggests changes in muscle function during a step.

Advancing System Performance with Redundancy: From Biological to Artificial Designs

Redundancy is a fundamental characteristic of many biological processes such as those in the genetic, visual, muscular, and nervous systems, yet its driven mechanism has not been fully comprehended. Until recently, the only understanding of redundancy is as a mean to attain fault tolerance, which is reflected in the design of many man-made systems. On the contrary, our previous work on redundant sensing (RS) has demonstrated an example where redundancy can be engineered solely for enhancing accuracy and precision. The design was inspired by the binocular structure of human vision, which we believe may share a similar operation. In this letter, we present a unified theory describing how such utilization of redundancy is feasible through two complementary mechanisms: representational redundancy (RPR) and entangled redundancy (ETR). We also point out two additional examples where our new understanding of redundancy can be applied to justify a system's superior performance. One is the human musculoskeletal system (HMS), a biological instance, and the other is the deep residual neural network (ResNet), an artificial counterpart. We envision that our theory would provide a framework for the future development of bio-inspired redundant artificial systems, as well as assist studies of the fundamental mechanisms governing various biological processes.

Modeling musculoskeletal kinematic and dynamic redundancy using null space projection

The coordination of the human musculoskeletal system is deeply influenced by its redundant structure, in both kinematic and dynamic terms. Noticing a lack of a relevant, thorough treatment in the literature, we formally address the issue in order to understand and quantify factors affecting the motor coordination. We employed well-established techniques from linear algebra and projection operators to extend the underlying kinematic and dynamic relations by modeling the redundancy effects in null space. We distinguish three types of operational spaces, namely task, joint and muscle space, which are directly associated with the physiological factors of the system. A method for consistently quantifying the redundancy on multiple levels in the entire space of feasible solutions is also presented. We evaluate the proposed muscle space projection on segmental level reflexes and the computation of the feasible muscle forces for arbitrary movements. The former proves to be a convenient representation for interfacing with segmental level models or implementing controllers for tendon driven robots, while the latter enables the identification of force variability and correlations between muscle groups, attributed to the system’s redundancy. Furthermore, the usefulness of the proposed framework is demonstrated in the context of estimating the bounds of the joint reaction loads, where we show that misinterpretation of the results is possible if the null space forces are ignored. This work presents a theoretical analysis of the redundancy problem, facilitating application in a broad range of fields related to motor coordination, as it provides the groundwork for null space characterization. The proposed framework rigorously accounts for the effects of kinematic and dynamic redundancy, incorporating it directly into the underlying equations using the notion of null space projection, leading to a complete description of the system.

Force feasible set prediction with artificial neural network and musculoskeletal model

Developing tools to predict the force capabilities of the human limbs through the Force Feasible Set (FFS) may be of great interest for robotic assisted rehabilitation and digital human modelling for ergonomics. Indeed, it could help to refine rehabilitation programs for active participation during exercise therapy and to prevent musculoskeletal disorders. In this framework, the purpose of this study is to use artificial neural networks (ANN) to predict the FFS of the upper-limb based on joint centre Cartesian positions and anthropometric data. Seventeen right upper-limb musculoskeletal models based on individual anthropometric data are created. For each musculoskeletal model, the FFS is computed for 8428 different postures. For any combination of force direction and joint positions, ANNs can predict the FFS with high values of coefficient of determination (R² > 0.89) between the true and predicted data.

The Effects of Selective Muscle Weakness on Muscle Coordination in the Human Arm

Despite the fundamental importance of muscle coordination in daily life, it is currently unclear how muscle coordination adapts when the musculoskeletal system is perturbed. In this study, we quantified the impact of selective muscle weakness on several metrics of muscle coordination. Seven healthy subjects performed 2D and 3D isometric force target matches, while electromyographic (EMG) signals were recorded from 13 elbow and shoulder muscles. Subsequently, muscle weakness was induced by a motor point block of brachialis muscle. Postblock subjects repeated the force generation tasks. We quantified muscle coordination pre- and postblock using three metrics: tuning curve preferred direction, tuning curve area, and motor modules analysis via nonnegative matrix factorization. For most muscles, the tuning direction for the 2D protocol was not substantially altered postblock, while tuning areas changed more drastically. Typically, five motor modules were identified from the 3D task, and four motor modules were identified in the 2D task; this result held across both pre- and postblock conditions. The composition of one or two motor modules, ones that involved mainly the activation of shoulder muscles, was altered postblock. Our results demonstrate that selective muscle weakness can induce nonintuitive alternations in muscle coordination in the mechanically redundant human arm.

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).

Wheelchair propulsion: Force orientation and amplitude prediction with Recurrent Neural Network

The aim of this study was to use Recurrent Neural Network (RNN) to predict the orientation and amplitude of the applied force during the push phase of manual wheelchair propulsion. Trunk and the right-upper limb kinematics data were assessed with an optoeletronic device (Qualisys) and the force applied on the handrim was recorded with an instrumented wheel (SMARTWheel®). Data acquisitions were performed at 60/80/10/120/140% of the freely chosen frequency at submaximal and maximal conditions. The final database consisted of d = 5708 push phases. The input data were the trunk and right upper-limb kinematics (joint angle, angular velocity and acceleration) and anthropometric data (height, weight, segment length) and the output data were the applied forces orientation and amplitude. A ratio of 70/15/15 was used to train, validate and test the RNN (d_train = 3996, d_validation = 856 and d_test = 856). The angle and amplitude errors between the measured and predicted force was assessed from d_test. Results showed that for most of the push phase (∼70%), the force direction prediction errors were less than 12°. The mean absolute amplitude errors were less than 8 N and the mean absolute amplitude percentage errors were less than 20% for most of the push phase (∼80%).

Multi-finger synergies and the muscular apparatus of the hand

We explored whether the synergic control of the hand during multi-finger force production tasks depends on the hand muscles involved. Healthy subjects performed accurate force production tasks and targeted force pulses while pressing against loops positioned at the level of fingertips, middle phalanges, and proximal phalanges. This varied the involvement of the extrinsic and intrinsic finger flexors. The framework of the uncontrolled manifold (UCM) hypothesis was used to analyze the structure of inter-trial variance, motor equivalence, and anticipatory synergy adjustments prior to the force pulse in the spaces of finger forces and finger modes (hypothetical finger-specific control signals). Subjects showed larger maximal force magnitudes at the proximal site of force production. There were synergies stabilizing total force during steady-state phases across all three sites of force production; no differences were seen across the sites in indices of structure of variance, motor equivalence, or anticipatory synergy adjustments. Indices of variance, which did not affect the task (within the UCM), correlated with motor equivalent motion between the steady states prior to and after the force pulse; in contrast, variance affecting task performance did not correlate with non-motor equivalent motion. The observations are discussed within the framework of hierarchical control with referent coordinates for salient effectors at each level. The findings suggest that multi-finger synergies are defined at the level of abundant transformation between the low-dimensional hand level and higher dimensional finger level while being relatively immune to transformations between the finger level and muscle level. The results also support the scheme of control with two classes of neural variables that define referent coordinates and gains in back-coupling loops between hierarchical control levels.

Neuromechanical coupling within the human triceps surae and its consequence on individual force sharing strategies

Little is known about the factors that influence the coordination of synergist muscles that act across the same joint, even during single-joint isometric tasks. The overall aim of this study was to determine the nature of the relationship between the distribution of activation and the distribution of force-generating capacity among the three heads of the triceps surae (soleus [SOL], gastrocnemius medialis [GM] and lateralis [GL]). Twenty volunteers performed isometric plantarflexions during which the activation of GM, GL and SOL was estimated using electromyography (EMG). Functional muscle physiological cross-sectional area (PCSA) was estimated using imaging techniques and was considered as an index of muscle-force generating capacity. The distribution of activation and PCSA among the three muscles varied greatly between participants. A significant positive correlation between the distribution of activation and the distribution of PCSA was observed when considering the two bi-articular muscles at intensities ≤50% of the maximal contraction (0.51&lt;r&lt;0.62). Specifically, the greater the PCSA of GM compared with GL, the stronger bias of activation to the GM. There was no significant correlation between monoarticular and biarticular muscles. A higher contribution of GM activation compared with GL activation was associated with lower triceps surae activation (−0.66 &lt;r&lt;−0.42) and metabolic cost (−0.74&lt;r&lt;−0.52) for intensities ≥30% of the maximal contraction. Considered together, an imbalance of force between the three heads was observed, the magnitude of which varied greatly between participants. The origin and consequences of these individual force-sharing strategies remain to be determined.

On neuromechanical approaches for the study of biological and robotic grasp and manipulation

Biological and robotic grasp and manipulation are undeniably similar at the level of mechanical task performance. However, their underlying fundamental biological vs. engineering mechanisms are, by definition, dramatically different and can even be antithetical. Even our approach to each is diametrically opposite: inductive science for the study of biological systems vs. engineering synthesis for the design and construction of robotic systems. The past 20 years have seen several conceptual advances in both fields and the quest to unify them. Chief among them is the reluctant recognition that their underlying fundamental mechanisms may actually share limited common ground, while exhibiting many fundamental differences. This recognition is particularly liberating because it allows us to resolve and move beyond multiple paradoxes and contradictions that arose from the initial reasonable assumption of a large common ground. Here, we begin by introducing the perspective of neuromechanics, which emphasizes that real-world behavior emerges from the intimate interactions among the physical structure of the system, the mechanical requirements of a task, the feasible neural control actions to produce it, and the ability of the neuromuscular system to adapt through interactions with the environment. This allows us to articulate a succinct overview of a few salient conceptual paradoxes and contradictions regarding under-determined vs. over-determined mechanics, under- vs. over-actuated control, prescribed vs. emergent function, learning vs. implementation vs. adaptation, prescriptive vs. descriptive synergies, and optimal vs. habitual performance. We conclude by presenting open questions and suggesting directions for future research. We hope this frank and open-minded assessment of the state-of-the-art will encourage and guide these communities to continue to interact and make progress in these important areas at the interface of neuromechanics, neuroscience, rehabilitation and robotics.

Hammering Does Not Fit Fitts' Law

While movement is essential to human wellbeing, we are still unable to reproduce the deftness and robustness of human movement in automatons or completely restore function to individuals with many types of motor impairment. To better understand how the human nervous system plans and controls movements, neuromechanists employ simple tasks such as upper extremity reaches and isometric force tasks. However, these simple tasks rarely consider impacts and may not capture aspects of motor control that arise from real-world complexity. Here we compared existing models of motor control with the results of a periodic targeted impact task extended from Bernstein's seminal work: hammering a nail into wood. We recorded impact forces and kinematics from 10 subjects hammering at different frequencies and with hammers with different physical properties (mass and face area). We found few statistical differences in most measures between different types of hammer, demonstrating human robustness to minor changes in dynamics. Because human motor control is thought to obey optimality principles, we also developed a feedforward optimal simulation with a neuromechanically inspired cost function that reproduces the experimental data. However, Fitts' Law, which relates movement time to distance traveled and target size, did not match our experimental data. We therefore propose a new model in which the distance moved is a logarithmic function of the time to move that yields better results (R2 ≥ 0.99 compared to R2 ≥ 0.88). These results support the argument that humans control movement in an optimal way, but suggest that Fitts' Law may not generalize to periodic impact tasks.

Improving the upper-limb force feasible set evaluation by muscles maximal isometric force identification and cocontraction factors

In order to improve the evaluation of the force feasible set (FFS) of the upper-limb which is of great interest in the biomechanics field, this study proposes two additional techniques. The first one is based on the identification of the maximal isometric force (MIF) of Hill-based muscles models from sEMG and isometric force measurements at the hand. The second one considers muscles cocontraction. The FFS was computed with an upper-limb musculoskeletal model in three different cases. The first one (M1) considered binary muscular activation and a simple MIF scaling method based on the weight and muscle length of the subject. The second one (M2) introduces cocontraction factors determined from sEMG. The third one (M3) considers the cocontraction factors and the MIF identification. Finally, M1, M2 and M3 are compared with end-effector force measurement. M3 outperforms the two other methods on FFS prediction demonstrating the validity and the usefulness of MIF identification and the consideration of the cocontraction factors.

Forearm Flexor Muscles in Children with Cerebral Palsy Are Weak, Thin and Stiff

Children with cerebral palsy (CP) often develop reduced passive range of motion with age. The determining factor underlying this process is believed to be progressive development of contracture in skeletal muscle that likely changes the biomechanics of the joints. Consequently, to identify the underlying mechanisms, we modeled the mechanical characteristics of the forearm flexors acting across the wrist joint. We investigated skeletal muscle strength (Grippit®) and passive stiffness and viscosity of the forearm flexors in 15 typically developing (TD) children (10 boys/5 girls, mean age 12 years, range 8–18 yrs) and nine children with CP Nine children (6 boys/3 girls, mean age 11 ± 3 years (yrs), range 7–15 yrs) using the NeuroFlexor® apparatus. The muscle stiffness we estimate and report is the instantaneous mechanical response of the tissue that is independent of reflex activity. Furthermore, we assessed cross-sectional area of the flexor carpi radialis (FCR) muscle using ultrasound. Age and body weight did not differ significantly between the two groups. Children with CP had a significantly weaker (−65%, p < 0.01) grip and had smaller cross-sectional area (−43%, p < 0.01) of the FCR muscle. Passive stiffness of the forearm muscles in children with CP was increased 2-fold (p < 0.05) whereas viscosity did not differ significantly between CP and TD children. FCR cross-sectional area correlated to age (R² = 0.58, p < 0.01), body weight (R² = 0.92, p < 0.0001) and grip strength (R² = 0.82, p < 0.0001) in TD children but only to grip strength (R² = 0.60, p < 0.05) in children with CP. We conclude that children with CP have weaker, thinner, and stiffer forearm flexors as compared to typically developing children.

Effects of Sensory Deficit on Phalanx Force Deviation During Power Grip Post Stroke

The effect of sensory deficits on power grip force from individual phalanges was examined. The authors found that stroke survivors with sensory deficits (determined by the Semmes-Weinstein monofilament test) gripped with phalanx force directed more tangential to the object surface, than those without, although both groups had similar motor deficits (Chedoke-McMaster and Fugl-Meyer), grip strength, and skin friction. Altered grip force direction elevates risk of finger slippage against the object thus grip loss/object dropping, hindering activities of daily living. Altered grip force direction was associated with altered muscle activation patterns. In summary, the motor impairment level alone may not describe hand motor control in detail. Information about sensory deficits helps elucidate patients' hand motor control with functional relevance.

Proposition of a Classification of Adult Patients with Hemiparesis in Chronic Phase

Background

Patients who have developed hemiparesis as a result of a central nervous system lesion, often experience reduced walking capacity and worse gait quality. Although clinically, similar gait patterns have been observed, presently, no clinically driven classification has been validated to group these patients’ gait abnormalities at the level of the hip, knee and ankle joints. This study has thus intended to put forward a new gait classification for adult patients with hemiparesis in chronic phase, and to validate its discriminatory capacity.

Methods and Findings

Twenty-six patients with hemiparesis were included in this observational study. Following a clinical examination, a clinical gait analysis, complemented by a video analysis, was performed whereby participants were requested to walk spontaneously on a 10m walkway. A patient’s classification was established from clinical examination data and video analysis. This classification was made up of three groups, including two sub-groups, defined with key abnormalities observed whilst walking. Statistical analysis was achieved on the basis of 25 parameters resulting from the clinical gait analysis in order to assess the discriminatory characteristic of the classification as displayed by the walking speed and kinematic parameters. Results revealed that the parameters related to the discriminant criteria of the proposed classification were all significantly different between groups and subgroups. More generally, nearly two thirds of the 25 parameters showed significant differences (p<0.05) between the groups and sub-groups. However, prior to being fully validated, this classification must still be tested on a larger number of patients, and the repeatability of inter-operator measures must be assessed.

Conclusions

This classification enables patients to be grouped on the basis of key abnormalities observed whilst walking and has the advantage of being able to be used in clinical routines without necessitating complex apparatus. In the midterm, this classification may allow a decision-tree of therapies to be developed on the basis of the group in which the patient has been categorised.

A Probabilistic Analysis of Muscle Force Uncertainty for Control

BACKGROUND

We control the movements of our body and limbs through our muscles. However, the forces produced by our muscles depend unpredictably on the commands sent to them. This uncertainty has two sources: irreducible noise in the motor system's processes (i.e., motor noise) and variability in the relationship between muscle commands and muscle outputs (i.e., model uncertainty). Any controller, neural or artificial, benefits from estimating these uncertainties when choosing commands.

METHODS

To examine these benefits, we used an experimental preparation of the rat hindlimb to electrically stimulate muscles and measure the resulting isometric forces. We compare a functional electric stimulation (FES) controller that represents and compensates for uncertainty in muscle forces with a standard FES controller that neglects uncertainty.

RESULTS

Accounting for uncertainty substantially increased the precision of force control.

CONCLUSION

Our study demonstrates the theoretical and practical benefits of representing muscle uncertainty when computing muscle commands.

SIGNIFICANCE

The findings are relevant beyond FES as they highlight the benefits of estimating statistical properties of muscles for both artificial controllers and the nervous system.

Muscle Synergies Heavily Influence the Neural Control of Arm Endpoint Stiffness and Energy Consumption

Much debate has arisen from research on muscle synergies with respect to both limb impedance control and energy consumption. Studies of limb impedance control in the context of reaching movements and postural tasks have produced divergent findings, and this study explores whether the use of synergies by the central nervous system (CNS) can resolve these findings and also provide insights on mechanisms of energy consumption. In this study, we phrase these debates at the conceptual level of interactions between neural degrees of freedom and tasks constraints. This allows us to examine the ability of experimentally-observed synergies—correlated muscle activations—to control both energy consumption and the stiffness component of limb endpoint impedance. In our nominal 6-muscle planar arm model, muscle synergies and the desired size, shape, and orientation of endpoint stiffness ellipses, are expressed as linear constraints that define the set of feasible muscle activation patterns. Quadratic programming allows us to predict whether and how energy consumption can be minimized throughout the workspace of the limb given those linear constraints. We show that the presence of synergies drastically decreases the ability of the CNS to vary the properties of the endpoint stiffness and can even preclude the ability to minimize energy. Furthermore, the capacity to minimize energy consumption—when available—can be greatly affected by arm posture. Our computational approach helps reconcile divergent findings and conclusions about task-specific regulation of endpoint stiffness and energy consumption in the context of synergies. But more generally, these results provide further evidence that the benefits and disadvantages of muscle synergies go hand-in-hand with the structure of feasible muscle activation patterns afforded by the mechanics of the limb and task constraints. These insights will help design experiments to elucidate the interplay between synergies and the mechanisms of learning, plasticity, versatility and pathology in neuromuscular systems.

The manner in which the nervous system coordinates the multiple muscles in the body is complex. It has been studied for decades, but a more full understanding is needed to enable the development of effective evaluation and treatment methods in disorders that cause neuromuscular disability such as cerebral palsy and stroke. In addition, the computational control of robots has and will continue to improve as the brain’s methods of muscular control are progressively reverse-engineered. Here, we study the capacity of arm muscles to regulate the stiffness of the hand for tasks such as using tools, stabilizing hand-held objects, and using doors. Using a simplified but generalizable model, we show that there will be necessary trade-offs in the functional capabilities of the limb if the nervous system chooses to control muscles in functional groups. This adds to our understanding of the consequences of different strategies to control muscles for real-world tasks with multiple and often competing demands. It enables future research and clinical experiments on the learning and execution of the multiple tasks of varying difficulty encountered in real life. It also sheds light on the design of control strategies for robots to operate in human and unstructured environments.

Learning new gait patterns: Exploratory muscle activity during motor learning is not predicted by motor modules

The motor module hypothesis in motor control proposes that the nervous system can simplify the problem of controlling a large number of muscles in human movement by grouping muscles into a smaller number of modules. Here, we tested one prediction of the modular organization hypothesis by examining whether there is preferential exploration along these motor modules during the learning of a new gait pattern. Healthy college-aged participants learned a new gait pattern which required increased hip and knee flexion during the swing phase while walking in a lower-extremity robot (Lokomat). The new gait pattern was displayed as a foot trajectory in the sagittal plane and participants attempted to match their foot trajectory to this template. We recorded EMG from 8 lower-extremity muscles and we extracted motor modules during both baseline walking and target-tracking using non-negative matrix factorization (NMF). Results showed increased trajectory variability in the first block of learning, indicating that participants were engaged in exploratory behavior. Critically, when we examined the muscle activity during this exploratory phase, we found that the composition of motor modules changed significantly within the first few strides of attempting the new gait pattern. The lack of persistence of the motor modules under even short time scales suggests that motor modules extracted during locomotion may be more indicative of correlated muscle activity induced by the task constraints of walking, rather than reflecting a modular control strategy.

Structure of the set of feasible neural commands for complex motor tasks

The brain must select its control strategies among an infinite set of possibilities; researchers believe that it must be solving an optimization problem. While this set of feasible solutions is infinite and lies in high dimensions, it is bounded by kinematic, neuromuscular, and anatomical constraints, within which the brain must select optimal solutions. That is, the set of feasible activations is well structured. However, to date there is no method to describe and quantify the structure of these high-dimensional solution spaces. Bounding boxes or dimensionality reduction algorithms do not capture their detailed structure. We present a novel approach based on the well-known Hit-and-Run algorithm in computational geometry to extract the structure of the feasible activations capable of producing 50% of maximal fingertip force in a specific direction. We use a realistic model of a human index finger with 7 muscles, and 4 DOFs. For a given static force vector at the endpoint, the feasible activation space is a 3D convex polytope, embedded in the 7D unit cube. It is known that explicitly computing the volume of this polytope can become too computationally complex in many instances. However, our algorithm was able to sample 1,000,000 uniform at random points from the feasible activation space. The computed distribution of activation across muscles sheds light onto the structure of these solution spaces-rather than simply exploring their maximal and minimal values. Although this paper presents a 7 dimensional case of the index finger, our methods extend to systems with at least 40 muscles. This will allow our motor control community to understand the distributions of feasible muscle activations, providing important contextual information into learning, optimization and adaptation of motor patterns in future research.

Capacity of small groups of muscles to accomplish precision grasping tasks

An understanding of the capacity or ability of various muscle groups to generate endpoint forces that enable grasping tasks could provide a stronger biomechanical basis for the design of reconstructive surgery or rehabilitation for the treatment of the paralyzed or paretic hand. We quantified two-dimensional endpoint force distributions for every combination of the muscles of the index finger, in cadaveric specimens, to understand the capability of muscle groups to produce endpoint forces that accomplish three common types of grasps-tripod, tip and lateral pinch-characterized by a representative level of Coulomb friction. We found that muscle groups of 4 or fewer muscles were capable of generating endpoint forces that enabled performance of each of the grasping tasks examined. We also found that flexor muscles were crucial to accomplish tripod pinch; intrinsic muscles, tip pinch; and the dorsal interosseus muscle, lateral pinch. The results of this study provide a basis for decision making in the design of reconstructive surgeries and rehabilitation approaches that attempt to restore the ability to perform grasping tasks with small groups of muscles.

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).

Exploring the high-dimensional structure of muscle redundancy via subject-specific and generic musculoskeletal models

Subject-specific and generic musculoskeletal models are the computational instantiation of hypotheses, and stochastic techniques help explore their validity. We present two such examples to explore the hypothesis of muscle redundancy. The first addresses the effect of anatomical variability on static force capabilities for three individual cat hindlimbs, each with seven kinematic degrees of freedom (DoFs) and 31 muscles. We present novel methods to characterize the structure of the 31-dimensional set of feasible muscle activations for static force production in every 3-D direction. We find that task requirements strongly define the set of feasible muscle activations and limb forces, with few differences comparing individual vs. species-average results. Moreover, muscle activity is not smoothly distributed across 3-D directions. The second example explores parameter uncertainty during a flying disc throwing motion by using a generic human arm with five DoFs and 17 muscles to predict muscle fiber velocities. We show that the measured joint kinematics fully constrain the eccentric and concentric fiber velocities of all muscles via their moment arms. Thus muscle activation for limb movements is likely not redundant: there is little, if any, latitude in synchronizing alpha-gamma motoneuron excitation-inhibition for muscles to adhere to the time-critical fiber velocities dictated by joint kinematics. Importantly, several muscles inevitably exhibit fiber velocities higher than thought tenable, even for conservative throwing speeds. These techniques and results, respectively, enable and compel us to continue to revise the classical notion of muscle redundancy for increasingly more realistic models and tasks.

Feasible muscle activation ranges based on inverse dynamics analyses of human walking

Although it is possible to produce the same movement using an infinite number of different muscle activation patterns owing to musculoskeletal redundancy, the degree to which observed variations in muscle activity can deviate from optimal solutions computed from biomechanical models is not known. Here, we examined the range of biomechanically permitted activation levels in individual muscles during human walking using a detailed musculoskeletal model and experimentally-measured kinetics and kinematics. Feasible muscle activation ranges define the minimum and maximum possible level of each muscle's activation that satisfy inverse dynamics joint torques assuming that all other muscles can vary their activation as needed. During walking, 73% of the muscles had feasible muscle activation ranges that were greater than 95% of the total muscle activation range over more than 95% of the gait cycle, indicating that, individually, most muscles could be fully active or fully inactive while still satisfying inverse dynamics joint torques. Moreover, the shapes of the feasible muscle activation ranges did not resemble previously-reported muscle activation patterns nor optimal solutions, i.e. static optimization and computed muscle control, that are based on the same biomechanical constraints. Our results demonstrate that joint torque requirements from standard inverse dynamics calculations are insufficient to define the activation of individual muscles during walking in healthy individuals. Identifying feasible muscle activation ranges may be an effective way to evaluate the impact of additional biomechanical and/or neural constraints on possible versus actual muscle activity in both normal and impaired movements.