Gravitational and Dynamic Components of Muscle Torque Underlie Tonic and Phasic Muscle Activity during Goal-Directed Reaching

Hypergravity is more challenging than microgravity for the human sensorimotor system

The importance of gravity for human motor control is well established, but it remains unclear how the central nervous system accounts for gravitational changes to perform complex motor skills. We tested the hypothesis that microgravity and hypergravity have distinct effects on the neuromuscular control of reaching movements compared to normogravity. To test the influence of gravity levels on sensorimotor planning and control, participants (n = 9) had to reach toward visual targets during parabolic flights. Whole-body kinematics and muscular activity were adjusted in microgravity, allowing arm reaching to be as accurate as in normogravity. However, we observed in hypergravity a systematic undershooting, which likely resulted from a lack of reorganization of muscle activations. While new studies are necessary to clarify whether hypergravity impairs the internal model of limb dynamics, our findings provide new evidence that hypergravity creates a challenge that the human sensorimotor system is unable to solve in the short term.

Spinal maps in phasic and tonic EMG: Investigating intra-subject and inter-subject variability

Reaching movements are essential for daily tasks and they have been widely investigated through kinematic, kinetic, and electromyographic (EMG) analyses. Recent studies have suggested that the central nervous system simplifies control of reaching movements by using muscle synergies. An alternative approach is to investigate how EMG activity reflects at theneural level with the representation of spinal maps that visualize the spatiotemporal activity of motoneuronal pools. Spinal maps have been rarely used and their investigation could be made by exploiting recent findings in EMG processing such as the separation of phasic (motion-related) and tonic components (anti-gravity). In this study, we aimed at characterizing spinal maps in the upper limb workspace. EMG data from 15 participants were recorded during repeated point-to-point movements toward target boards placed in five orientations. EMG waveforms were divided into total EMG envelope, tonic EMG, and phasic EMG. The multidimensional Pearson's correlation coefficient was used to assess thesimilarity of spinal maps among repetitions of movements within subjects (intra-subject variability) and among participants (inter-subject variability). Spinal maps of tonic and total EMG showed high intra- and inter-subject similarity in all planes, while phasic spinal maps were less repeatable and more subject-specific. These results may be useful as areference for rehabilitation, clinical, and neurological evaluations, especially for longitudinal assessments.

Evaluating Joint Angle Data for Clinical Assessment Using Multidimensional Inverse Kinematics with Average Segment Morphometry

Movement analysis is a critical tool in understanding and addressing various disabilities associated with movement deficits. By analyzing movement patterns, healthcare professionals can identify the root causes of these alterations, which is essential for preventing, diagnosing, and rehabilitating a broad spectrum of medical conditions, disabilities, and injuries. With the advent of affordable motion capture technologies, quantitative data on patient movement is more accessible to clinicians, enhancing the quality of care. Nonetheless, it is crucial that these technologies undergo rigorous validation to ensure their accuracy in collecting and monitoring patient movements, particularly for remote healthcare services where direct patient observation is not possible. In this study, motion capture technology was used to track upper extremity movements during a reaching task presented in virtual reality. Kinematic data was then calculated for each participant using a scaled dynamic inertial model. The goal was to evaluate the accuracy of joint angle calculations using inverse kinematics from motion capture relative to the typical movement redundancy. Shoulder, elbow, radioulnar, and wrist joint angles were calculated with models scaled using either direct measurements of each individual's arm segment lengths or those lengths were calculated from individual height using published average proportions. The errors in joint angle trajectories calculated using the two methods of model scaling were compared to the inter-trial variability of those trajectories. The variance of this error was primarily within the normal range of variability between repetitions of the same movements. This suggests that arm joint angles can be inferred with good enough accuracy from motion capture data and individual height to be useful for the clinical assessment of motor deficits.

Differential Impact of Biomechanical Constraints on Control Signal Dimensionality for Gravity Support Versus Propulsion

Neural control of movement has to overcome the problem of redundancy in the multidimensional musculoskeletal system. The problem can be solved by reducing the dimensionality of the control space of motor commands, i.e., through muscle synergies or motor primitives. Evidence for this solution exists, multiple studies have obtained muscle synergies using decomposition methods. These synergies vary across different workspaces and are present in both dominant and non-dominant limbs. Here we explore the dimensionality of control space by examining muscle activity patterns across reaching movements in different directions starting from different postures performed bilaterally by healthy individuals. We further explore the effect of biomechanical constraints on the dimensionality of control space. We are building on top of prior work showing that muscle activity profiles can be explained by applied moments about the limb joints that reflect the biomechanical constraints. These muscle torques derived from motion capture represent the combined actions of muscle contractions that are under the control of the nervous system. Here we test the generalizability of the relationship between muscle torques and muscle activity profiles across different starting positions and between limbs. We also test a hypothesis that the dimensionality of control space is shaped by biomechanical constraints. We used principal component analysis to evaluate the contribution of individual muscles to producing muscle torques across different workspaces and in both dominant and non-dominant limbs. Results generalize and support the hypothesis. We show that the muscle torques that support the limb against gravity are produced by more consistent combinations of muscle co-contraction than those that produce propulsion. This effect was the strongest in the non-dominant arm moving in the lateral workspace on one side of the body.

Impedance-based biomechanical method for robust inverse kinematics from noisy data

This paper presents a novel method for solving the inverse kinematic problem of capturing human reaching movements using a dynamic biomechanical model. The model consists of rigid segments connected by joints and actuated by markers. The method was validated against a rotation matrix-based method using motion capture data recorded during reaching movements performed by healthy human volunteers. The results showed that the proposed method achieved low errors in joint angles and compensated for noise in motion capture data. The angles were comparable to those calculated using the standard marker-based method. The proposed bioinspired method can be used in real-time medical applications for processing noisy marker data with occlusions.

Phasic and tonic muscle synergies are different in number, structure and sparseness

In the last two decades, muscle synergies analysis has been commonly used to assess the neurophysiological mechanisms underlying human motor control. Several synergy models and algorithms have been employed for processing the electromyographic (EMG) signal, and it has been shown that the coordination of motor control is characterized by the presence of phasic (movement-related) and tonic (anti-gravity and related to co-contraction) EMG components. Neural substrates indicate that phasic and tonic components have non-homogeneous origin; however, it is still unclear if these components are generated by the same set of synergies or by distinct synergies. This study aims at testing whether phasic and tonic components are generated by distinct phasic and tonic synergies or by the same set of synergies with phasic and tonic activation coefficients. The study also aims at characterizing the differences between the phasic and the tonic synergies. Using a comprehensive mapping of upper-limb point-to-point movements, synergies were extracted from phasic and tonic EMG signal separately, estimating the tonic components with a linear ramp model. The goodness of reconstruction (R2) as a function of the number of synergies was compared, and sets of synergies extracted from each dataset at three R2 threshold levels (0.80, 0.85, 0.90) were retained for further analysis. Then, shared, phasic-specific, and tonic-specific synergies were extracted from the two datasets concatenated. The dimensionality of the synergies shared between the phasic and the tonic datasets was estimated with a bootstrap procedure based on the evaluation of the distribution of principal angles between the subspaces spanned by phasic and tonic synergies due to noise. We found only few shared synergies, indicating that phasic and tonic synergies have in general different structures. To compare consistent differences in synergy composition, shared, phasic-specific, and tonic-specific synergies were clustered separately. Phasic-specific clusters were more numerous than tonic-specific ones, suggesting that they were more differentiated among subjects. The structure of phasic clusters and the higher sparseness indicated that phasic synergies capture specific muscle activation patterns related to the movement while tonic synergies show co-contraction of multiple muscles for joint stabilization and holding postures. These results suggest that in many scenarios phasic and tonic synergies should be extracted separately, especially when performing muscle synergy analysis in patients with abnormal tonic activity and for tuning devices with gravity support.

Reoptimization of single-joint motor patterns to non-Earth gravity torques induced by a robotic exoskeleton

Gravity is a ubiquitous component of our environment that we have learned to optimally integrate in movement control. Yet, altered gravity conditions arise in numerous applications from space exploration to rehabilitation, thereby pressing the sensorimotor system to adapt. Here, we used a robotic exoskeleton to reproduce the elbow joint-level effects of arbitrary gravity fields ranging from 1g to -1g, passing through Mars- and Moon-like gravities, and tested whether humans can reoptimize their motor patterns accordingly. By comparing the motor patterns of actual arm movements with those predicted by an optimal control model, we show that our participants (N = 61 ) adapted optimally to each gravity-like torque. These findings suggest that the joint-level effects of a large range of gravities can be efficiently apprehended by humans, thus opening new perspectives in arm weight support training in manipulation tasks, whether it be for patients or astronauts.

The human motor cortex contributes to gravity compensation to maintain posture and during reaching

The neural control of posture and movement is interdependent. During voluntary movement, the neural motor command is executed by the motor cortex through the corticospinal tract and its collaterals and subcortical targets. Here we address the question of whether the control mechanism for the postural adjustments at nonmoving joints is also involved in overcoming gravity at the moving joints. We used single-pulse transcranial magnetic stimulation to measure the corticospinal excitability in humans during postural and reaching tasks. We hypothesized that the corticospinal excitability is proportional to background muscle activity and the gravity-related joint moments during both static postures and reaching movements. To test this hypothesis, we used visual targets in virtual reality to instruct five postures and three movements with or against gravity. We then measured the amplitude and gain of motor evoked potentials in multiple arm and hand muscles at several phases of the reaching motion and during static postures. The stimulation caused motor evoked potentials in all muscles that were proportional to the muscle activity. During both static postures and reaching movements, the muscle activity and the corticospinal contribution to these muscles changed in proportion with the postural moments needed to support the arm against gravity, supporting the hypothesis. Notably, these changes happened not only in antigravity muscles. Altogether, these results provide evidence that the changes in corticospinal excitability cause muscle cocontraction that modulates limb stiffness. This suggests that the motor cortex is involved in producing postural adjustments that support the arm against gravity during posture maintenance and reaching.NEW & NOTEWORTHY Animal studies suggest that the corticospinal tract and its collaterals are crucial for producing postural adjustments that accompany movement in limbs other than the moving limb. Here we provide evidence for a similar control schema for both arm posture maintenance and gravity compensation during movement of the same limb. The observed interplay between the postural and movement control signals within the corticospinal tract may help explain the underlying neural motor deficits after stroke.

The reserve of joint torque determines movement coordination

Humans coordinate biomechanical degrees of freedom to perform tasks at minimum cost. When reaching a target from a seated position, the trunk-arm-forearm coordination moves the hand to the well-defined spatial goal, while typically minimising hand jerk and trunk motion. However, due to fatigue or stroke, people visibly move the trunk more, and it is unclear what cost can account for this. Here we show that people recruit their trunk when the torque at the shoulder is too close to the maximum. We asked 26 healthy participants to reach a target while seated and we found that the trunk contribution to hand displacement increases from 11 to 27% when an additional load is handled. By flexing and rotating the trunk, participants spontaneously increase the reserve of anti-gravitational torque at the shoulder from 25 to 40% of maximal voluntary torque. Our findings provide hints on how to include the reserve of torque in the cost function of optimal control models of human coordination in healthy fatigued persons or in stroke victims.

Detailed characterization of physiological EMG activations and directional tuning of upper-limb and trunk muscles in point-to-point reaching movements

In recent years, several studies have investigated upper-limb motion in a variety of scenarios including motor control, physiology, rehabilitation and industry. Such applications assess people’s kinematics and muscular performances, focusing on typical movements that simulate daily-life tasks. However, often only a limited interpretation of the EMG patterns is provided. In fact, rarely the assessments separate phasic (movement-related) and tonic (postural) EMG components, as well as the EMG in the acceleration and deceleration phases. With this paper, we provide a comprehensive and detailed characterization of the activity of upper-limb and trunk muscles in healthy people point-to-point upper limb movements. Our analysis includes in-depth muscle activation magnitude assessment, separation of phasic (movement-related) and tonic (postural) EMG activations, directional tuning, distinction between activations in the acceleration and deceleration phases. Results from our study highlight a predominant postural activity with respect to movement related muscular activity. The analysis based on the acceleration phase sheds light on finer motor control strategies, highlighting the role of each muscle in the acceleration and deceleration phase. The results of this study are applicable to several research fields, including physiology, rehabilitation, design of robots and assistive solutions, exoskeletons.

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Upper-limb motion is assessed with kinematics and EMG in many scenarios: motor control, physiology, rehabilitation, industry

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Separation of phasic (movement-related) and tonic (postural) EMG, and of acceleration and deceleration phases

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Comprehensive and detailed characterization of the EMG of upper-limb and trunk muscles in point-to-point upper limb movements

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EMG magnitude assessment, phasic and tonic EMG activations, directional tuning, acceleration and deceleration phases

Stroke impairs the control of isometric forces and muscle activations in the ipsilesional arm

Stroke often impairs the control of the contralesional arm, thus most survivors rely on the ipsilesional arm to perform daily living activities that require an efficient control of movements and forces. Whereas the ipsilesional arm is often called 'unaffected' or 'unimpaired', several studies suggested that during dynamic tasks its kinematics and joint torques are altered. Is stroke also affecting the ability of the ipsilesional arm to produce isometric force, as when pushing or pulling a handle? Here, we address this question by analyzing behavioral performance and muscles' activity when subjects applied an isometric force of 10 N in eight coplanar directions. We found that stroke affected the ability to apply well-controlled isometric forces with the ipsilesional arm, although to a minor extent compared to the contralesional arm. The spinal maps, the analysis of single muscle activities and the organization of muscle synergies highlighted that this effect was mainly associated with abnormal activity of proximal muscles with respect to matched controls, especially when pushing or pulling in lateral directions.

Muscle torques and joint accelerations provide more sensitive measures of poststroke movement deficits than joint angles

The whole repertoire of complex human motion is enabled by forces applied by our muscles and controlled by the nervous system. The impact of stroke on the complex multijoint motor control is difficult to quantify in a meaningful way that informs about the underlying deficit in the active motor control and intersegmental coordination. We tested whether poststroke deficit can be quantified with high sensitivity using motion capture and inverse modeling of a broad range of reaching movements. Our hypothesis is that muscle moments estimated based on active joint torques provide a more sensitive measure of poststroke motor deficits than joint angles. The motion of 22 participants was captured while performing reaching movements in a center-out task, presented in virtual reality. We used inverse dynamic analysis to derive active joint torques that were the result of muscle contractions, termed muscle torques, that caused the recorded multijoint motion. We then applied a novel analysis to separate the component of muscle torque related to gravity compensation from that related to intersegmental dynamics. Our results show that muscle torques characterize individual reaching movements with higher information content than joint angles do. Moreover, muscle torques enable distinguishing the individual motor deficits caused by aging or stroke from the typical differences in reaching between healthy individuals. Similar results were obtained using metrics derived from joint accelerations. This novel quantitative assessment method may be used in conjunction with home-based gaming motion capture technology for remote monitoring of motor deficits and inform the development of evidence-based robotic therapy interventions.NEW & NOTEWORTHY Functional deficits seen in task performance have biomechanical underpinnings, seen only through the analysis of forces. Our study has shown that estimating muscle moments can quantify with high-sensitivity poststroke deficits in intersegmental coordination. An assessment developed based on this method could help quantify less observable deficits in mildly affected stroke patients. It may also bridge the gap between evidence from studies of constrained or robotically manipulated movements and research with functional and unconstrained movements.

A segmented forearm model of hand pronation-supination approximates joint moments for real time applications

Musculoskeletal modeling is a new computational tool to reverse engineer human control systems, which require efficient algorithms running in real-time. Human hand pronation-supination movement is accomplished by movement of the radius and ulna bones relative to each other via the complex proximal and distal radioulnar joints, each with multiple degrees of freedom (DOFs). Here, we report two simplified models of this complex kinematic transformation implemented as a part of a 20 DOF model of the hand and forearm. The pronation/supination DOF was implemented as a single rotation joint either within the forearm segment or separating proximal and distal parts of the forearm segment. Torques produced by the inverse dynamic simulations with anatomical architecture of the forearm (OpenSim model) were used as the "gold standard" in the comparison of two simple models. Joint placement was iteratively optimized to achieve the closest representation of torques during realistic hand movements. The model with a split forearm segment performed better than the model with a solid forearm segment in simulating pronation/supination torques. We conclude that simplifying pronation/supination DOF as a single-axis rotation between arm segments is a viable strategy to reduce the complexity of multi-DOF dynamic simulations.

A cross-species neural integration of gravity for motor optimization

Recent kinematic results, combined with model simulations, have provided support for the hypothesis that the human brain shapes motor patterns that use gravity effects to minimize muscle effort. Because many different muscular activation patterns can give rise to the same trajectory, here, we specifically investigate gravity-related movement properties by analyzing muscular activation patterns during single-degree-of-freedom arm movements in various directions. Using a well-known decomposition method of tonic and phasic electromyographic activities, we demonstrate that phasic electromyograms (EMGs) present systematic negative phases. This negativity reveals the optimal motor plan's neural signature, where the motor system harvests the mechanical effects of gravity to accelerate downward and decelerate upward movements, thereby saving muscle effort. We compare experimental findings in humans to monkeys, generalizing the Effort-optimization strategy across species.

Computational evidence for nonlinear feedforward modulation of fusimotor drive to antagonistic co-contracting muscles

The sensorimotor integration during unconstrained reaching movements in the presence of variable environmental forces remains poorly understood. The objective of this study was to quantify how much the primary afferent activity of muscle spindles can contribute to shaping muscle coactivation patterns during reaching movements with complex dynamics. To achieve this objective, we designed a virtual reality task that guided healthy human participants through a set of planar reaching movements with controlled kinematic and dynamic conditions that were accompanied by variable muscle co-contraction. Next, we approximated the Ia afferent activity using a phenomenological model of the muscle spindle and muscle lengths derived from a musculoskeletal model. The parameters of the spindle model were altered systematically to evaluate the effect of fusimotor drive on the shape of the temporal profile of afferent activity during movement. The experimental and simulated data were analyzed with hierarchical clustering. We found that the pattern of co-activation of agonistic and antagonistic muscles changed based on whether passive forces in each movement played assistive or resistive roles in limb dynamics. The reaching task with assistive limb dynamics was associated with the most muscle co-contraction. In contrast, the simulated Ia afferent profiles were not changing between tasks and they were largely reciprocal with homonymous muscle activity. Simulated physiological changes to the fusimotor drive were not sufficient to reproduce muscle co-contraction. These results largely rule out the static set and α-γ coactivation as the main types of fusimotor drive that transform the monosynaptic Ia afferent feedback into task-dependent co-contraction of antagonistic muscles. We speculate that another type of nonlinear transformation of Ia afferent signals that is independent of signals modulating the activity of α motoneurons is required for Ia afferent-based co-contraction. This transformation could either be applied through a complex nonlinear profile of fusimotor drive that is not yet experimentally observed or through presynaptic inhibition.

Motor Planning of Vertical Arm Movements in Healthy Older Adults: Does Effort Minimization Persist With Aging?

Several sensorimotor modifications are known to occur with aging, possibly leading to adverse outcomes such as falls. Recently, some of those modifications have been proposed to emerge from motor planning deteriorations. Motor planning of vertical movements is thought to engage an internal model of gravity to anticipate its mechanical effects on the body-limbs and thus to genuinely produce movements that minimize muscle effort. This is supported, amongst other results, by direction-dependent kinematics where relative durations to peak accelerations and peak velocity are shorter for upward than for downward movements. The present study compares the motor planning of fast and slow vertical arm reaching movements between 18 young (24 ± 3 years old) and 17 older adults (70 ± 5 years old). We found that older participants still exhibit strong directional asymmetries (i.e., differences between upward and downward movements), indicating that optimization processes during motor planning persist with healthy aging. However, the size of these differences was increased in older participants, indicating that gravity-related motor planning changes with age. We discuss this increase as the possible result of an overestimation of gravity torque or increased weight of the effort cost in the optimization process. Overall, these results support the hypothesis that feedforward processes and, more precisely, optimal motor planning, remain active with healthy aging.

A novel method of identifying motor primitives using wavelet decomposition

This study reports a new technique for extracting muscle synergies using continuous wavelet transform. The method allows to quantify coincident activation of muscle groups caused by the physiological processes of fixed duration, thus enabling the extraction of wavelet modules of arbitrary groups of muscles. Hierarchical clustering and identification of the repeating wavelet modules across subjects and across movements, was used to identify consistent muscle synergies. Results indicate that the most frequently repeated wavelet modules comprised combinations of two muscles that are not traditional agonists and span different joints. We have also found that these wavelet modules were flexibly combined across different movement directions in a pattern resembling directional tuning. This method is extendable to multiple frequency domains and signal modalities.