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2009, Annual Reviews in Control
Human arm movement control theories are reviewed in the current paper. The motor planning problem stated as a generation of a time plan for the execution of a movement task, is a major concern of the current paper. It will be suggested that computational models of motor control have a strong potential for the use in the area of human motor rehabilitation. Their use can be discriminated in three main areas of application: the generation of correct trajectories to be demonstrated to human subjects during physiotherapy; the assessment of motion disorders and movement quality; and the devising of challenging interaction exercises to promote recovery.
IEEE Transactions on Medical Robotics and Bionics, 2021
Design and development of robotic-assistance must consider the abilities of individuals with disabilities. In this paper, a 8-DOF kinematic model of the upper limb complex is derived to evaluate the reachable workspace of the arm during interaction with a planar robot and to serve as the basis for rehabilitation strategies and assistive robotics. Through inverse differential kinematics and by taking account the physical limits of each arm joint, the model determines workspaces where the individual is able to perform tasks and those regions where robotic assistance is required. Next, a learning-from-demonstration strategy via a nonparametric potential field function is derived to teach the robot the required assistance based on demonstrations of functional tasks. The paper investigates two applications. First, in the context of rehabilitation, robotic assistance is only provided if the individual is required to move her arm in regions that are not reachable via voluntary motion. Second, in the context of assistive robotics, the demonstrated trajectory is scaled down to match the individual's voluntary range of motion through a nonlinear workspace mapping. Assistance is provided within that workspace only. Experimental results in 5 different experimental scenarios with a person with cerebral palsy confirm the suitability of the proposed framework.
2017
Stroke rehabilitation plays a vital role for people with limb disability because of stroke attack. Due to gradually increasing medical prices, the cost of rehabilitation devices existed in the hospital and rehab centre are simultaneously increased. These devices also lack the features that help to ease and increase the spirit of patients during the rehabilitation process. Thus, this paper aim to create an arm platform-based for upper limb rehabilitation, where the interactive game features also created by using Unity 2D software for the purpose of motivating patients during the rehabilitation process. The main target is to develop an arm platform, which is focused on proper controller design for the active exercises in early-stage therapy. The performance of the arm platform is examined in term of range of motion. Therefore, it will reduce patient’s pressure during the exercise and gradually improve their agility. In the proper control of the muscle tension, the designed upper limb ...
2018
Human civilization started with the invention of tools which enhanced and expanded human motor capability. With the recent development of virtual reality technology and artificial intelligence, the interaction between humans and machines has become more and more intricate. A better understanding of our motor system and the way it interacts with machines will allow us to better design intelligent devices. However, previous works in motor control modeling mostly focused on linear dynamics and had limitations in incorporating the process of learning. A musculoskeletal model based on mechanical principles and a motor control model based on Bayesian probability are proposed in this study. The probability-theoretical formulation of the problem not only facilitates the understanding of motor learning but also transforms nonlinear dynamics into linear problems. Using these models, the interactions in which both human and machine are capable of learning and adapting are formulated and analyz...
Using optimal control theory and dynamic programming, we reconstructed the command trajectory of the fast elbow joint movement with two musculoskeletal models of the elbow joint, one with linear areflexic and the other with nonlinear reflexic muscle representation. The goal of the optimization was to seek a command trajectory that best reproduced the experimentally derived movement trajectory. The estimation results showed that the command trajectory using the model with linear areflexic muscle representation manifested the triphasic response, while the results using the model with nonlinear reflexic muscle representation showed only biphasic response. The calculated command trajectories capture the characteristics of the measured EMG. The results revealed that the optimal control theory could be used to reconstruct, from the joint angle trajectory, a command trajectory compatible with the currently accepted concept of motor control.
Medical & Biological Engineering & Computing, 2011
This paper is focused on the multimodal analysis of patient performance, carried out by means of robotic technology and wearable sensors, and aims at providing quantitative measure of biomechanical and motion planning features of arm motor control following rehabilitation. Upper-limb robotic therapy was administered to 24 community-dwelling persons with chronic stroke. Performance indices on patient motor performance were computed from data recorded with the InMotion2 robotic machine and a magneto-inertial sensor. Motor planning issues were investigated by means of techniques of motion decomposition into submovements. A linear regression analysis was carried out to study correlation with clinical scales. Robotic outcome measures showed a significant improvement of kinematic motor performance; improvement of dynamic components was more significant in resistive motion and highly correlated with MP. The analysis of motion decomposition into submovements showed an important change with recovery of submovement number, amplitude and order, tending to patterns measured in healthy subjects. Preliminary results showed that arm biomechanical functions can be objectively measured by means of the proposed set of performance indices. Correlation with MP is high, while correlation with FM is moderate. Features related to motion planning strategies can be extracted from submovement analysis.
2002
Many different studies have proposed models for human arm trajectories, almost all of them agreed on invariant feature of these movements, such as smooth trajectories with straight line and uni-modal velocity profiles. We observed these characteristics in contact with a haptic interface that might modify the movement features. Significantly, our result showed similar characteristics for the human reaching and returning movement for one subject. We also used the data in comparison with the model based on the minimum jerk theory. The results obtained from our experiments are consistent with the model based on this theory, which suggests that our virtual trajectory is a good model of human arm movements. Further investigation, with more number of subjects are needed to prove these consistencies.
… , IEEE Transactions on, 2009
2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob), 2012
Abstract²This paper seeks to define the mechanisms by which the human motor system finds optimal reaching solutions, when one of the arm joints is locked in place. Specifically, the paper studies how people solve the problem of motion planning when they lose the ability to move their elbow joint. Our hypothesis is based on the idea that the governing rules of motion planning will be consistent even under the given joint constraint, i.e. the hand will follow the shortest path with a bell±shaped velocity profile, while reaching from a start to an end position. We present an experimental protocol with human subjects to compare their hand paths with the geodesic curve in Euclidean space. The speed profiles of these trajectories are also compared to the modified output of the so±called minimum jerk model of Flash and Hogan. Our results indicate that arm reaching paths with an elbow joint constraint at a certain angle closely follow the geodesic and has a bell shaped speed profile. The future work involves extending this research to the shoulder and wrist joints.
Human arm movements may be adversely affected in the event of stroke or spinal cord injuries, eventually causing the patient to lose control of arm movements. Electromyography (EMG) is con-sidered the most effective technique for the restoration of arm movement in such cases. The reha-bilitation period for such patients is usually long. Moreover, complex treatment techniques may demoralize them. Therefore, this study, attempts to contribute to the development of a relaxing rehabilitation environment through electromyography control of a computer model of the arm. The model is created using MATLAB® and Data LINK software and other requisite components for training the targeted participants to control their arm movements. Six male participants with no history of injury to the arms or back were selected using the set protocol. The results and data collected are analysed using three performance measures i.e. the number of target hits, average time to target, and path efficiency for each target. Then, the main results in terms of the obtained performance measures are discussed and compared with those of previous studies.
The role of the mechanical properties of the neu- romuscular system in motor control has been investigated for a long time in both human and animal subjects, mainly through the application of mechanical perturbations to the limb during natural movements and the observation of its corrective responses. These methods have provided a wealth of insight into how the central nervous system controls the limb. They suffer, however, from the fact that it is almost impossible to separate the active and passive components of the measured arm stiffness and that the measurement may themselves alter the stiffness characteristic of the arm. As a complement to these analyses, the implementation of a given neuroscientific hypothesis on a real mechanical sys- tem could overcome these measurement artifact and provide a tool that is, under full control of the experimenter, able to replicate the relevant functional features of the human arm. In this article, we introduce the NEURARM platform, a robotic arm intended to test hypotheses on the human motor con- trol system. As such, NEURARM satisfies two key require- ments. First, its kinematic parameters and inertia are similar to that of the human arm. Second, NEURARM mimics the main physical features of the human actuation system, spe- cifically, the use of tendons to transfer force, the presence of antagonistic muscle pairs, the passive elasticity of mus- cles in the absence of any neural feedback and the non-linear elastic behaviour. This article presents the design and char- acterization of the NEURARM actuation system. The result- ing mechanical behaviour, which has been tested in joint an...
Biological Cybernetics, 1999
The Journal of Neuroscience, 1985
This paper presents studies of the coordination of voluntary human arm movements. A mathematical model is formulated which is shown to predict both the qualitative features and the quantitative details observed experimentally in planar, multijoint arm movements. Coordination is modeled mathematically by defining an objective function, a measure of performance for any possible movement. The unique trajectory which yields the best performance is determined using dynamic optimization theory. In the work presented here, the objective function is the square of the magnitude of jerk (rate of change of acceleration) of the hand integrated over the entire movement. This is equivalent to assuming that a major goal of motor coordination is the production of the smoothest possible movement of the hand. Experimental observations of human subjects performing voluntary unconstrained movements in a horizontal plane are presented. They confirm the following predictions of the mathematical model: un...
2010 IEEE Antennas and Propagation Society International Symposium, 2010
Biological Cybernetics, 2006
In control, stability captures the reproducibility of motions and the robustness to environmental and internal perturbations. This paper examines how stability can be evaluated in human movements, and possible mechanisms by which humans ensure stability. First, a measure of stability is introduced, which is simple to apply to human movements and corresponds to Lyapunov exponents. Its application to real data shows that it is able to distinguish effectively between stable and unstable dynamics. A computational model is then used to investigate stability in human arm movements, which takes into account motor output variability and computes the force to perform a task according to an inverse dynamics model. Simulation results suggest that even a large time delay does not affect movement stability as long as the reflex feedback is small relative to muscle elasticity. Simulations are also used to demonstrate that existing learning schemes, using a monotonic antisymmetric update law, cannot compensate for unstable dynamics. An impedance compensation algorithm is introduced to learn unstable dynamics, which produces similar adaptation responses to those found in experiments.
Journal of Electromyography and Kinesiology, 1993
In a previous study the EMG records of shoulder and elbow muscles during goal-directed arm movements were discussed. Here an analysis of the kinematic signals is presented and the relation between EMG and kinematic signals is assessed in a correlation analysis. The displacement as a function of time (movement trace) is analyzed. The movement trace is described by a model with five parameters that are estimated using a least squares criterion. Four parameters describe the timing of a triphasic muscular input and a fifth parameter describes neuromuscular dynamics. The parameters provide a means to compare the shape of movement traces recorded under different experimental conditions. After scaling, the shapes of movement traces with different step sizes and velocities/durations can be compared. The scaled parameters reveal a significant dependence on the movement direction of maximally fast movements. Furthermore, the scaled parameters depend significantly on the maximum velocity obtained by the subjects. This dependence can be interpreted in terms of neural inputs and muscular dynamics, as the parameters have been defined in these terms. The parameters estimated from the kinematics have a high correlation with EMG timing. A further analysis of these correlations indicates that the movement obtained is closely coupled to activity of the four prime movers of the upper arm and of three out of four scapular muscles.
World Academy of Science, Engineering and Technology, International Journal of Medical, Health, Biomedical, Bioengineering and Pharmaceutical Engineering, 2017
This paper describes the development of a model of an impaired human arm performing a reaching motion, which will be used to predict hand path trajectories for people with reduced arm joint mobility. Assuming that the arm was in contact with a surface during the entire movement, the contact conditions at the initial and final task locations were determined and used to generate the entire trajectory. The model was validated by comparing it to experimental data, which simulated an arm joint impairment by physically constraining the joint motion with a brace. Future research will include using the model in the development of physical training protocols that avoid early recruitment of “healthy” Degrees-OfFreedom (DOF) for reaching motions, thus facilitating an Active Range-Of-Motion Recovery (AROM) for a particular impaired joint. Keywords—Higher order kinematic specifications, human motor coordination, impaired movement, kinematic synthesis.
2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012
This paper seeks to define the governing strategies by which the human central nervous system (CNS) finds optimal solutions for an arm reaching motion, when an elbow joint is constrained. The compensated arm reaching motion under the joint kinematic constraint is observed by human experiments. We present an experimental protocol, where subjects perform point-to-point reaching tasks with a lightweight elbow brace to restrict the elbow kinematics with minimal effect on the arm dynamics. The human compensatory strategy is analyzed in terms of hand path kinematics (i.e. spatial and temporal characteristics) and the arm postural configuration. The spatial and temporal characteristics of hand path are approximated by the Euclidean geodesic curves and the well known bell-shaped smooth profile, respectively. Furthermore, the contribution of each joint degree-of-freedom (DOF) motion is discussed and its relation to the arm posture selection is elaborated.
The article is the result of a preliminary study concerning the possibility to simulate human arm movements. The research work will be continued on a larger scale in the frame of an europena project -ANNIE. The objective of the work was to implement a neural network based methodology for simulating human movements in order to check and ensure ergonomical properties in differnet environments like work cells, cars (interior?) etc. If most of the studies are concerned with robot like movements, only a few have dealt with human movements. The neural networks potentiality s proved in this case, too: feed-forward nets are employed and the resilient backpropagation is used as training algorithm.
Biocybernetics and Biomedical Engineering, 2013
Rehabilitation of post stroke patients with upper extremity motor deficits is typically focused on relearning of motor abilities and functionalities requiring interaction with physiotherapists and/or rehabilitation robots. In a point-to-point movement training, the trajectories are usually arbitrarily determined without considering the motor impairment of the individual. In this paper, we used an optimal control model based on arm dynamics enabling also incorporation of muscle functioning constraints (i.e. simulation of muscle tightness) to find the optimal trajectories for planar arm reaching movements. First, we tested ability of the minimum joint torque cost function to replicate the trajectories obtained in previously published experimental trials done by neurologically intact subjects, and second, we predicted the optimal trajectories when muscle constraints were modeled. The resulting optimal trajectories show considerable similarity as compared to the experimental data, while on the other hand, the muscle constraints play a major role in determination of the optimal trajectories for stroke rehabilitation.
2018
The RETRAINER S1 system is an upper limb rehabilitation device designed to be used in repetitive task-oriented training. While the device itself is intrinsically controlled by the wearer, the execution of the training exercises is automatically controlled by a finite-state machine. This contribution discusses three different control strategies tested in a clinical environment.
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