Effector dynamics of rhythmic wrist activity and its implications for (modeling) bimanual coordination

Proximal-distal differences in movement smoothness reflect differences in biomechanics

Smoothness is a hallmark of healthy movement. Past research indicates that smoothness may be a side product of a control strategy that minimizes error. However, this is not the only reason for smooth movements. Our musculoskeletal system itself contributes to movement smoothness: the mechanical impedance (inertia, damping, and stiffness) of our limbs and joints resists sudden change, resulting in a natural smoothing effect. How the biomechanics and neural control interact to result in an observed level of smoothness is not clear. The purpose of this study is to 1) characterize the smoothness of wrist rotations, 2) compare it with the smoothness of planar shoulder-elbow (reaching) movements, and 3) determine the cause of observed differences in smoothness. Ten healthy subjects performed wrist and reaching movements involving different targets, directions, and speeds. We found wrist movements to be significantly less smooth than reaching movements and to vary in smoothness with movement direction. To identify the causes underlying these observations, we tested a number of hypotheses involving differences in bandwidth, signal-dependent noise, speed, impedance anisotropy, and movement duration. Our simulations revealed that proximal-distal differences in smoothness reflect proximal-distal differences in biomechanics: the greater impedance of the shoulder-elbow filters neural noise more than the wrist. In contrast, differences in signal-dependent noise and speed were not sufficiently large to recreate the observed differences in smoothness. We also found that the variation in wrist movement smoothness with direction appear to be caused by, or at least correlated with, differences in movement duration, not impedance anisotropy.NEW & NOTEWORTHY This article presents the first thorough characterization of the smoothness of wrist rotations (flexion-extension and radial-ulnar deviation) and comparison with the smoothness of reaching (shoulder-elbow) movements. We found wrist rotations to be significantly less smooth than reaching movements and determined that this difference reflects proximal-distal differences in biomechanics: the greater impedance (inertia, damping, stiffness) of the shoulder-elbow filters noise in the command signal more than the impedance of the wrist.

A neuromuscular elbow model for analysis of force and movement variability in slow movements

In this paper, we present a neuromuscular elbow model with both motor unit pool recruitment and Hill-based contraction dynamics. The model builds upon various models reported in the literature and provides a way to quantify force and movement variability in both isometric and non-isometric contractions. The model's accuracy in estimating muscle force variability at low force levels (at less than 20% maximum voluntary contraction) is evaluated in isometric contraction case and compared with experimental results from the literature. This comparison suggests that the model is accurate in estimating force variability within the low force range and can be used to explore effects of muscle force variability in increased kinematic variability during slow movements.

Enhanced multi-site EMG-force estimation using contact pressure

A modification method based on integrated contact pressure and surface electromyogram (SEMG) recordings over the biceps brachii muscle is presented. Multi-site sEMGs are modified by pressure signals recorded at the same locations for isometric contractions. The resulting pressure times SEMG signals are significantly more correlated to the force induced at the wrist (FW), yielding SEMG-force models with superior performance in force estimation. A sensor patch, combining six SEMG and six contact pressure sensors was designed and built. SEMG, and contact pressure data over the biceps brachii and induced wrist force data were collected from 5 subjects. Polynomial fitting was used to find a mapping between biceps SEMG and wrist force. Comparison between evaluation values from models trained with modified and non-modified SEMG signals revealed a statistically significant superiority of models trained with the modified SEMG.

Methodological aspects of SEMG recordings for force estimation--a tutorial and review

Insight into the magnitude of muscle forces is important in biomechanics research, for example because muscle forces are the main determinants of joint loading. Unfortunately muscle forces cannot be calculated directly and can only be measured using invasive procedures. Therefore, estimates of muscle force based on surface EMG measurements are frequently used. This review discusses the problems associated with surface EMG in muscle force estimation and the solutions that novel methodological developments provide to this problem. First, some basic aspects of muscle activity and EMG are reviewed and related to EMG amplitude estimation. The main methodological issues in EMG amplitude estimation are precision and representativeness. Lack of precision arises directly from the stochastic nature of the EMG signal as the summation of a series of randomly occurring polyphasic motor unit potentials and the resulting random constructive and destructive (phase cancellation) superimpositions. Representativeness is an issue due the structural and functional heterogeneity of muscles. Novel methods, i.e. multi-channel monopolar EMG and high-pass filtering or whitening of conventional bipolar EMG allow substantially less variable estimates of the EMG amplitude and yield better estimates of muscle force by (1) reducing effects of phase cancellation, and (2) adequate representation of the heterogeneous activity of motor units within a muscle. With such methods, highly accurate predictions of force, even of the minute force fluctuations that occur during an isometric and isotonic contraction have been achieved. For dynamic contractions, EMG-based force estimates are confounded by the effects of muscle length and contraction velocity on force producing capacity. These contractions require EMG amplitude estimates to be combined with modeling of muscle contraction dynamics to achieve valid force predictions.

Coordination of complex bimanual multijoint movements under increasing cycling frequencies: the prevalence of mirror-image and translational symmetry

The present study examined the principles underlying inter and intralimb coordination constraints during performance of bimanual elbow-wrist movements at different cycling frequencies (from 0.75 Hz to 2.50 Hz). Participants performed eight coordination tasks that consisted of a combination of in-phase (IN) and/or anti-phase (AN) coordination modes between both elbows and wrists (interlimb), with isodirectional (Iso) or non-isodirectional (NonI) coordination modes within each limb (intralimb). As expected, the principle of muscle homology (in-phase coordination), giving rise to mirror symmetrical movements with respect to the mid-sagittal plane, had a powerful influence on the quality of global coordinative behavior both between and within limbs. When this principle was violated (i.e., when the anti-phase mode was introduced in one or both joint pairs), the non-isodirectional intralimb mode exhibited a (de)stabilizing role in coordination, which became more pronounced at higher cycling frequencies. However, pattern loss with increasing cycling frequency resulted not only in convergence toward the more stable in-phase patterns with the elbows and wrists but also to the anti-phase patterns (which were associated with directional compatibility of within-limb motions). Moreover, participants generally preserved their initial mode of coordination (either in-phase or anti-phase) in the proximal joints (i.e., elbows) while shifting from anti-phase to in-phase (or vice versa) with their distal joint pair (i.e., wrists). Taken together, these findings reflect the impact of two immanent types of symmetry in bimanual coordination: mirror-image and translational symmetry.

Error correction in bimanual coordination benefits from bilateral muscle activity: evidence from kinesthetic tracking

Although previous studies indicated that the stability properties of interlimb coordination largely result from the integrated timing of efferent signals to both limbs, they also depend on afference-based interactions. In the present study, we examined contributions of afference-based error corrections to rhythmic bimanual coordination using a kinesthetic tracking task. Furthermore, since we found in previous research that subjects activated their muscles in the tracked (motor-driven) arm, we examined the functional significance of this activation to gain more insight into the processes underlying this phenomenon. To these aims, twelve subjects coordinated active movements of the right hand with motor-driven oscillatory movements of the left hand in two coordinative patterns: in-phase (relative phase 0 degrees) and antiphase (relative phase 180 degrees). They were either instructed to activate the muscles in the motor-driven arm as if moving along with the motor (active condition), or to keep these muscles as relaxed as possible (relaxed condition). We found that error corrections were more effective in in-phase than in antiphase coordination, resulting in more adequate adjustments of cycle durations to compensate for timing errors detected at the start of each cycle. In addition, error corrections were generally more pronounced in the active than in the relaxed condition. This activity-related difference was attributed to the associated bilateral neural control signals (as estimated using electromyography), which provided an additional reference (in terms of expected sensory consequences) for afference-based error corrections. An intimate relation was revealed between the (integrated) motor commands to both limbs and the processing of afferent feedback.

Analyzing gastrocnemius EMG-activity and sway data from quiet and perturbed standing

In an experiment, we combined force plate measurements and surface EMG in studying quiet and perturbed standing, involving MS (Multiple sclerosis) and controls. The aim of this paper is to report the results thus obtained on the relation between filtered gastrocnemius (GA) EMG and the anterior-posterior center-of-pressure (A/P COP) coordinate. The main finding is the good correspondence between A/P COP and the filtered GA EMG in the low frequency range. The EMG envelope was calculated using a zero-lag filter. Combining this with time shifts around 250-350 ms produced a high correlation (85.5+/-8.4%) between the GA-EMG envelope and the A/P COP. This EMG-COP relation was closest when using a low cut-off frequency value around 1 Hz in calculating the EMG envelope. Based on this filtering procedure we estimated the average EMG-COP time shift to be 283+/-43 ms between the GA-EMG envelope and A/P COP (which "lags" behind EMG envelope). This shift is consistent with the 1 Hz cut-off and phase shift produced by a corresponding critically damped second-order filter, and is about twice the corresponding twitch time. These results suggest that GA is to a large extent responsible for the phasic control of the anterior-posterior balance during quiet standing. A small difference (p<0.03) was found between mean time shift thus obtained for controls (n=4) and MS (n=6) while sway area showed a major difference (p<0.01). The paper also compares three alternative filters for numerical calculation of the EMG-envelope.

Can co-activation reduce kinematic variability? A simulation study

Impedance modulation has been suggested as a means to suppress the effects of internal 'noise' on movement kinematics. We investigated this hypothesis in a neuro-musculo-skeletal model. A prerequisite is that the muscle model produces realistic force variability. We found that standard Hill-type models do not predict realistic force variability in response to variability in stimulation. In contrast, a combined motor-unit pool model and a pool of parallel Hill-type motor units did produce realistic force variability as a function of target force, largely independent of how the force was transduced to the tendon. To test the main hypothesis, two versions of the latter model were simulated as an antagonistic muscle pair, controlling the position of a frictionless hinge joint, with a distal segment having realistic inertia relative to the muscle strength. Increasing the impedance through co-activation resulted in less kinematic variability, except for the lowest levels of co-activation. Model behavior in this region was affected by the noise amplitude and the inertial properties of the model. Our simulations support the idea that muscular co-activation is in principle an effective strategy to meet accuracy demands.

Explanatory limitations of the HKB model: Incentives for a two-tiered model of rhythmic interlimb coordination

The HKB model for rhythmic interlimb coordination has highlighted the importance of coordinative stability and loss of stability, and introduced, with this focus, a new set of explanatory constructs. However, the phenomenological character of both parts of this model (i.e., the potential and the associated system of coupled oscillators) precludes an understanding of how the observed stability characteristics are related to more specific (e.g., biomechanical and neurophysiological) aspects of the movement system. A two-tiered model (involving a distinction between 'neural' and 'effector' dynamics) is discussed that offers handles for addressing such underpinnings of the identified coordination dynamics. The promise of the model in this regard is illustrated by two recent studies showing how explicit accounts of the effector dynamics may help disclose why (and how) particular properties of the peripheral system affect the overall coordination dynamics.