56 research outputs found

    Inter-Joint Coordination Deficits Revealed in the Decomposition of Endpoint Jerk During Goal-Directed Arm Movement After Stroke

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    It is well documented that neurological deficits after stroke can disrupt motor control processes that affect the smoothness of reaching movements. The smoothness of hand trajectories during multi-joint reaching depends on shoulder and elbow joint angular velocities and their successive derivatives as well as on the instantaneous arm configuration and its rate of change. Right-handed survivors of unilateral hemiparetic stroke and neurologically-intact control participants held the handle of a two-joint robot and made horizontal planar reaching movements. We decomposed endpoint jerk into components related to shoulder and elbow joint angular velocity, acceleration, and jerk. We observed an abnormal decomposition pattern in the most severely impaired stroke survivors consistent with deficits of inter-joint coordination. We then used numerical simulations of reaching movements to test whether the specific pattern of inter-joint coordination deficits observed experimentally could be explained by either a general increase in motor noise related to weakness or by an impaired ability to compensate for multi-joint interaction torque. Simulation results suggest that observed deficits in movement smoothness after stroke more likely reflect an impaired ability to compensate for multi-joint interaction torques rather than the mere presence of elevated motor noise

    Submovements During Reaching Movements after Stroke

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    Neurological deficits after cerebrovascular accidents very frequently disrupt the kinematics of voluntary movements with the consequent impact in daily life activities. Robotic methodologies enable the quantitative characterization of specific control deficits needed to understand the basis of functional impairments and to design effective rehabilitation therapies. In a group of right handed chronic stroke survivors (SS) with right side hemiparesis, intact proprioception, and differing levels of motor impairment, we used a robotic manipulandum to study right arm function during discrete point-to-point reaching movements and reciprocal out-and-back movements to visual targets. We compared these movements with those of neurologically intact individuals (NI). We analyzed the presence of secondary submovements in the initial (i.e. outward) trajectory portion of the two tasks and found that the SS with severe impairment (F

    Measuring Multi-Joint Stiffness during Single Movements: Numerical Validation of a Novel Time-Frequency Approach

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    This study presents and validates a Time-Frequency technique for measuring 2-dimensional multijoint arm stiffness throughout a single planar movement as well as during static posture. It is proposed as an alternative to current regressive methods which require numerous repetitions to obtain average stiffness on a small segment of the hand trajectory. The method is based on the analysis of the reassigned spectrogram of the arm's response to impulsive perturbations and can estimate arm stiffness on a trial-by-trial basis. Analytic and empirical methods are first derived and tested through modal analysis on synthetic data. The technique's accuracy and robustness are assessed by modeling the estimation of stiffness time profiles changing at different rates and affected by different noise levels. Our method obtains results comparable with two well-known regressive techniques. We also test how the technique can identify the viscoelastic component of non-linear and higher than second order systems with a non-parametrical approach. The technique proposed here is very impervious to noise and can be used easily for both postural and movement tasks. Estimations of stiffness profiles are possible with only one perturbation, making our method a useful tool for estimating limb stiffness during motor learning and adaptation tasks, and for understanding the modulation of stiffness in individuals with neurodegenerative diseases

    Spatial patterns and broad-scale weather cues of beech mast seeding in Europe.

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    Mast seeding is a crucial population process in many tree species, but its spatio-temporal patterns and drivers at the continental scale remain unknown . Using a large dataset (8000 masting observations across Europe for years 1950-2014) we analysed the spatial pattern of masting across the entire geographical range of European beech, how it is influenced by precipitation, temperature and drought, and the temporal and spatial stability of masting-weather correlations. Beech masting exhibited a general distance-dependent synchronicity and a pattern structured in three broad geographical groups consistent with continental climate regimes. Spearman's correlations and logistic regression revealed a general pattern of beech masting correlating negatively with temperature in the summer 2 yr before masting, and positively with summer temperature 1 yr before masting (i.e. 2T model). The temperature difference between the two previous summers (DeltaT model) was also a good predictor. Moving correlation analysis applied to the longest eight chronologies (74-114 yr) revealed stable correlations between temperature and masting, confirming consistency in weather cues across space and time. These results confirm widespread dependency of masting on temperature and lend robustness to the attempts to reconstruct and predict mast years using temperature data

    How different human muscle models affect the estimation of lower limb joint stiffness during running

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    The dynamics of muscle force generation is directly related to the movement dynamics of the skeletal system. Thus, modelling muscle dynamics is important to fully understand the control of movement in humans. Abnormal movements caused by neuromuscular diseases such as stroke, Parkinson's disease, or multiple sclerosis to name a few have all in common the presence of some abnormal muscle tone. Muscle tone can be effectively represented via short-range stiffness. Since stiffness is difficult to measure in real time, it is convenient to use numerical models to assess muscle stiffness as function of muscle dynamics. In this work, two different implementations of the Hill-type muscle model are considered to estimate the lower limb joint stiffness during running. The obtained results are discussed to evaluate how the choices of muscle models affect the estimation of lower limb joint stiffness. We found that stiffness estimates are strongly dependent on the adopted muscle model. We observed different magnitude and timing of the estimated stiffness time profile with respect to each gait phase, as function of the model used. Furthermore, the two models produced substantially different joint stiffness time profiles for the ankle joint

    Effects of Reserve Actuators on Optimization Solutions: from Muscle Force to Joint Stiffness

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    This work presents a comparison between two optimization methods used to compute the muscle activation levels and corresponding forces that drives a set of generalized coordinates towards a set of desired trajectories. To improve the performance of musculoskeletal optimizations a supplemental set of actuators is often included in addition to the modeled muscles. Given a dynamic musculoskeletal model and five sets of reserve actuators, a series of numerical simulations have been performed using experimental data from a healthy male subject who executes a running movement at three different speeds. This is the first work to investigate the incidence of different reserve actuator sets on muscle activation-to-force optimization solutions, with respect to the estimation of the human lower limb muscle forces and corresponding joint stiffness. The results show significant differences between the obtained estimates, indicating a greater accuracy on the Computed Muscle Control solutions than pure Static Optimization solutions

    Analysis of Healthcare Push and Pull Task via JACK: Predicted Joint Accuracy during Full-Body Simulation

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    The posture accuracy of full-body dynamic simulation has been successfully evaluated in JACK Siemens software via analyzing two common push and pull tasks. The difference in joint angles between the actual and predicted human movement directly results in the strength of force exposed on the lumbar spine. In this study, the individual factors, such as body height, body weight, trunk and hip flexion, shoulder movement, and muscle strength between genders, have shown a strong association with the adopted postures and exposed spinal forces during task performance. To provide robust ergonomics analysis, these individual variables should be adequately considered in software design for the long-term goal of injury prevention in diverse occupational workplaces
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