On the intrinsic control properties of muscle and relexes: exploring the interaction between neural and musculoskeletal dynamics in the framework of the equilbrium-point hypothesis

The aim of this thesis is to examine the relationship between the intrinsic dynamics of the body and its neural control. Specifically, it investigates the influence of musculoskeletal properties on the control signals needed for simple goal-directed movements in the framework of the equilibriumpoint (EP) hypothesis. To this end, muscle models of varying complexity are studied in isolation and when coupled to feedback laws derived from the EP hypothesis. It is demonstrated that the dynamical landscape formed by non-linear musculoskeletal models features a stable attractor in joint space whose properties, such as position, stiffness and viscosity, can be controlled through differential- and co-activation of antagonistic muscles. The emergence of this attractor creates a new level of control that reduces the system’s degrees of freedom and thus constitutes a low-level motor synergy. It is described how the properties of this stable equilibrium, as well as transient movement dynamics, depend on the various modelling assumptions underlying the muscle model. The EP hypothesis is then tested on a chosen musculoskeletal model by using an optimal feedback control approach: genetic algorithm optimisation is used to identify feedback gains that produce smooth single- and multijoint movements of varying amplitude and duration. The importance of different feedback components is studied for reproducing invariants observed in natural movement kinematics. The resulting controllers are demonstrated to cope with a plausible range of reflex delays, predict the use of velocity-error feedback for the fastest movements, and suggest that experimentally observed triphasic muscle bursts are an emergent feature rather than centrally planned. Also, control schemes which allow for simultaneous control of movement duration and distance are identified. Lastly, it is shown that the generic formulation of the EP hypothesis fails to account for the interaction torques arising in multijoint movements. Extensions are proposed which address this shortcoming while maintaining its two basic assumptions: control signals in positional rather than force-based frames of reference; and the primacy of control properties intrinsic to the body over internal models. It is concluded that the EP hypothesis cannot be rejected for single- or multijoint reaching movements based on claims that predicted movement kinematics are unrealistic

Sensitivity of Motor Adaptation to the Statistical Properties of an Environmental Load

Linear, limited-memory models capture many important features of adaptive motor performance during reaching, stepping and pointing. A recent study in our lab found that a model fitted to data obtained from subjects reaching against elastic loads which varied from trial-to-trial later failed to fit the steady-state response behavior of subjects exposed to deterministic, step changes in load. Does motor adaptation depend on statistical properties of the environment (eg. mean load strength and variability)? Neurologically intact volunteers (n=14) made 6 blocks of 100 planar, ballistic, 10cm, out-and-back reaching movements against spring-like loads having equilibrium positions at the hand\u27s starting point. View of the limb was not allowed. Load stiffness varied trial-by-trial, and each block of movements differed in mean and/or variance such that three, 3-block contrasts were evaluated: increasing standard deviation (VAR), increasing mean (MEAN), and proportionally increasing standard deviation and mean (WEBER). In the VAR and MEAN contrasts, either the mean or the standard deviation of the load stiffness sequence was held constant while the other parameter varied systematically. In WEBER contrast, mean and standard deviation scaled proportionally over the contrast. The zero location of the transfer function moved toward the origin as variability increased. This trend in the zero location was the result of an unbalance in the decrease in the influence of previous load and the decrease of effective limb compliance with increasing variability. Specifically, the decrease in the influence of prior load was greater than the decrease in effective limb compliance. Effective limb compliance decreased to a larger extent in the MEAN and WEBER contrasts, which both presented an increase in mean load. In the MEAN contrast, the decrease in effective limb compliance with increasing mean load was balanced by an equivalent decrease in the influence of prior load, resulting in no significant change in the transfer function zero location. No changes in the influence of prior errors were observed in any of the contrasts. Thus, motor adaptation adjusts in two ways: the influence of prior load on subsequent movements decreases both when the environment is more variable and when effective limb compliance decreases with the mean load

Development and Biomechanical Analysis toward a Mechanically Passive Wearable Shoulder Exoskeleton

Shoulder disability is a prevalent health issue associated with various orthopedic and neurological conditions, like rotator cuff tear and peripheral nerve injury. Many individuals with shoulder disability experience mild to moderate impairment and struggle with elevating the shoulder or holding the arm against gravity. To address this clinical need, I have focused my research on developing wearable passive exoskeletons that provide continuous at-home movement assistance. Through a combination of experiments and computational tools, I aim to optimize the design of these exoskeletons. In pursuit of this goal, I have designed, fabricated, and preliminarily evaluated a wearable, passive, cam-driven shoulder exoskeleton prototype. Notably, the exoskeleton features a modular spring-cam-wheel module, allowing customizable assistive force to compensate for different proportions of the shoulder elevation moment due to gravity. The results of my research demonstrated that this exoskeleton, providing modest one-fourth gravity moment compensation at the shoulder, can effectively reduce muscle activity, including deltoid and rotator cuff muscles. One crucial aspect of passive shoulder exoskeleton design is determining the optimal anti-gravity assistance level. I have addressed this challenge using computational tools and found that an assistance level within the range of 20-30% of the maximum gravity torque at the shoulder joint yields superior performance for specific shoulder functional tasks. When facing a new task dynamic, such as wearing a passive shoulder exoskeleton, the human neuro-musculoskeletal system adapts and modulates limb impedance at the end-limb (i.e., hand) to enhance task stability. I have presented development and validation of a realistic neuromusculoskeletal model of the upper limb that can predict stiffness modulation and motor adaptation in response to newly introduced environments and force fields. Future studies will explore the model\u27s applicability in predicting stiffness modulation for 3D movements in novel environments, such as passive assistive devices\u27 force fields

Hierarchical neural control of human postural balance and bipedal walking in sagittal plane

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 177-192).The cerebrocerebellar system has been known to be a central part in human motion control and execution. However, engineering descriptions of the system, especially in relation to lower body motion, have been very limited. This thesis proposes an integrated hierarchical neural model of sagittal planar human postural balance and biped walking to 1) investigate an explicit mechanism of the cerebrocerebellar and other related neural systems, 2) explain the principles of human postural balancing and biped walking control in terms of the central nervous systems, and 3) provide a biologically inspired framework for the design of humanoid or other biomorphic robot locomotion. The modeling was designed to confirm neurophysiological plausibility and achieve practical simplicity as well. The combination of scheduled long-loop proprioceptive and force feedback represents the cerebrocerebellar system to implement postural balance strategies despite the presence of signal transmission delays and phase lags. The model demonstrates that the postural control can be substantially linear within regions of the kinematic state-space with switching driven by sensed variables.(cont.) A improved and simplified version of the cerebrocerebellar system is combined with the spinal pattern generation to account for human nominal walking and various robustness tasks. The synergy organization of the spinal pattern generation simplifies control of joint actuation. The substantial decoupling of the various neural circuits facilitates generation of modulated behaviors. This thesis suggests that kinematic control with no explicit internal model of body dynamics may be sufficient for those lower body motion tasks and play a common role in postural balance and walking. All simulated performances are evaluated with respect to actual observations of kinematics, electromyogram, etc.by Sungho JoPh.D

Concept of an exoskeleton for industrial applications with modulated impedance based on Electromyographic signal recorded from the operator

The introduction of an active exoskeleton that enhances the operator power in the manufacturing field was demonstrated in literature to lead to beneficial effects in terms of reducing fatiguing and the occurrence of musculo-skeletal diseases. However, a large number of manufacturing operations would not benefit from power increases because it rather requires the modulation of the operator stiffness. However, in literature, considerably less attention was given to those robotic devices that regulate their stiffness based on the operator stiffness, even if their introduction in the line would aid the operator during different manipulations respect with the exoskeletons with variable power. In this thesis the description of the command logic of an exoskeleton for manufacturing applications, whose stiffness is modulated based on the operator stiffness, is described. Since the operator stiffness cannot be mechanically measured without deflecting the limb, an estimation based on the superficial Electromyographic signal is required. A model composed of 1 joint and 2 antagonist muscles was developed to approximate the elbow and the wrist joints. Each muscle was approximated as the Hill model and the analysis of the joint stiffness, at different joint angle and muscle activations, was performed. The same Hill muscle model was then implemented in a 2 joint and 6 muscles (2J6M) model which approximated the elbow-shoulder system. Since the estimation of the exerted stiffness with a 2J6M model would be quite onerous in terms of processing time, the estimation of the operator end-point stiffness in realtime would therefore be questionable. Then, a linear relation between the end-point stiffness and the component of muscle activation that does not generate any end-point force, is proposed. Once the stiffness the operator exerts was estimated, three command logics that identifies the stiffness the exoskeleton is required to exert are proposed. These proposed command logics are: Proportional, Integral 1 s, and Integral 2 s. The stiffening exerted by a device in which a Proportional logic is implemented is proportional, sample by sample, to the estimated stiffness exerted by the operator. The stiffening exerted by the exoskeleton in which an Integral logic is implemented is proportional to the stiffness exerted by the operator, averaged along the previous 1 second (Integral 1 s) or 2 seconds (Integral 2 s). The most effective command logic, among the proposed ones, was identified with empirical tests conducted on subjects using a wrist haptic device (the Hi5, developed by the Bioengineering group of the Imperial College of London). The experimental protocol consisted in a wrist flexion/extension tracking task with an external perturbation, alternated with isometric force exertion for the estimation of the occurrence of the fatigue. The fatigue perceived by the subject, the tracking error, defined as the RMS of the difference between wrist and target angles, and the energy consumption, defined as the sum of the squared signals recorded from two antagonist muscles, indicated the Integral 1 s logic to be the most effective for controlling the exoskeleton. A logistic relation between the stiffness exerted by the subject and the stiffness exerted by the robotic devices was selected, because it assured a smooth transition between the maximum and the minimum stiffness the device is required to exert. However, the logistic relation parameters are subject-specific, therefore an experimental estimation is required. An example was provided. Finally, the literature about variable stiffness actuators was analyzed to identify the most suitable device for exoskeleton stiffness modulation. This actuator is intended to be integrated on an existing exoskeleton that already enhances the operator power based on the operator Electromyographic signal. The identified variable stiffness actuator is the DLR FSJ, which controls its stiffness modulating the preload of a single spring

Bio-inspired robotic joint and manipulator : from biomechanical experimentation and modeling to human-like compliant finger design and control

textOne of the greatest challenges in controlling robotic hands is grasping and manipulating objects in unstructured and uncertain environments. Robotic hands are typically too rigid to react against unexpected impacts and disturbances in order to prevent damage. The human hands have great versatility and robustness due, in part, to the passive compliance and damping. Designing mechanical elements that are inspired by the nonlinear joint compliance of human hands is a promising solution to achieve human-like grasping and manipulation. However, the exact role of biomechanical elements in realizing joint stiffness is unknown. We conducted a series of experiments to investigate nonlinear stiffness and damping of the metacarpophalangeal (MCP) joint at the index finger. We designed a custom-made mechanism to integrate electromyography sensors (EMGs) and a motion capture system to collect data from 19 subjects. We investigated the relative contributions of muscle-tendon units and the MCP capsule ligament complex to joint stiffness with subject-specific modeling. The results show that the muscle-tendon units provide limited contribution to the passive joint compliance. This findings indicate that the parallel compliance, in the form of the capsule-ligament complex, is significant in defining the passive properties of the hand. To identify the passive damping, we used the hysteresis loops to investigate the energy dissipation function. We used symbolic regression and principal component analysis to derive and interpret the damping models. The results show that the nonlinear viscous damping depends on the cyclic frequency, and fluid and structural types of damping also exist at the MCP joint. Inspired by the nonlinear stiffness of the MCP joint, we developed a miniaturized mechanism that uses pouring liquid plastic to design energy storing elements. The key innovations in this design are: a) a set of nonlinear elasticity of compliant materials, b) variable pulley configurations to tune the stiffness profile, and c) pretension mechanism to scale the stiffness profile. The design exhibits human-like passive compliance. By taking advantage of miniaturized joint size and additive manufacturing, we incorporated the novel joint design in a novel robotic manipulator with six series elastic actuators (SEA). The robotic manipulator has passive joint compliance with the intrinsic property of human hands. To validate the system, we investigated the Cartesian stiffness of grasping with low-level force control. The results show that that the overall system performs a great force tracking with position feedback. The parallel compliance decreases the motor efforts and can stabilize the system.Mechanical Engineerin

Mechanisms of motor learning: by humans, for robots

Whenever we perform a movement and interact with objects in our environment, our central nervous system (CNS) adapts and controls the redundant system of muscles actuating our limbs to produce suitable forces and impedance for the interaction. As modern robots are increasingly used to interact with objects, humans and other robots, they too require to continuously adapt the interaction forces and impedance to the situation. This thesis investigated the motor mechanisms in humans through a series of technical developments and experiments, and utilized the result to implement biomimetic motor behaviours on a robot. Original tools were first developed, which enabled two novel motor imaging experiments using functional magnetic resonance imaging (fMRI). The first experiment investigated the neural correlates of force and impedance control to understand the control structure employed by the human brain. The second experiment developed a regressor free technique to detect dynamic changes in brain activations during learning, and applied this technique to investigate changes in neural activity during adaptation to force fields and visuomotor rotations. In parallel, a psychophysical experiment investigated motor optimization in humans in a task characterized by multiple error-effort optima. Finally a computational model derived from some of these results was implemented to exhibit human like control and adaptation of force, impedance and movement trajectory in a robot

Analysis of Biodynamic Responses Associated with Upper Limb Reaching Movements under Whole-Body Vibration: Support for an Active Biodynamic Model.

Vehicle vibration is a well-recognized environmental stressor inducing discomfort, health risks, and performance degradation of the operator on board. More specifically, vibration transmitted by heavy transportation, construction, or military vehicles to the whole body of a seated occupant interferes with manual activities, which in turn may significantly compromise performance. Numerous approaches have attempted to understand the effects of vibration on the seated human for developing biomechanical models or to identify human reaching behaviors for developing human movement models. However, all these studies were limited to biomechanical models of the torso excluding the upper limbs, or to reach models based only on static conditions with no consideration of the interaction between environmental conditions of vibration and biodynamic characteristics of arm movements. The ultimate goal of this work is to provide a framework for an active biodynamic model of operators in vehicles based on empirical analyses of biodynamic responses of seated humans performing reaching movements under simplified whole-body vibration conditions. Hence, the present work investigates vibration transmission through multi-body segments as a function of vibration frequency and direction, identifies vibration-induced changes in reach kinematics of upper arm movements, analyzes the mechanisms of vibration transmission through a multi-body system as a function of posture and movement coordination, and proposes the integration of these empirical results for developing a biodynamic model. Five major results characterize our findings: a) vibration frequency is the dominant factor determining transmission characteristics through upper body segments, b) reach directions in three-dimensional space may be divided into three groups corresponding to transmission propagated through the upper limbs, c) visual compensation contributes to hand stabilization but does not modify significantly propagated transmission, d) elbow flexion contributes to the enhancement of hand stabilization by dissipating vibration energy, and e) biodynamic responses must be considered as three-dimensional tensors including the auto-axial and cross-axial transmissions. Furthermore, movement coordination and joint movement kinematics of reach movements are consistent between static and vibratory environments. The integration of these results may be used to support the structure of an active biodynamic model of the seated human.Ph.D.Mechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/75796/1/heonjeon_1.pd

Motor cortical activity related to the combined control of force and motion

Using tools, writing, and eating are all important behaviors that involve manipulating objects. Successful manipulation requires the control of both the force exerted on the object and its resultant motion. Both have been associated with neural activity in the motor cortex and we are interested in the extent to which neural firing rates in this brain region are related to their combined control. The mechanical relation between force and motion is impedance and we hypothesized that motor cortical activity encodes an impedance signal that reflects the force and motion demands of behavior. We examined this possibility with a paradigm in which subjects manipulated a handle that moved along a track. The handle was locked in place until the subject exerted enough force to cross a specific threshold; it was then released and moved along the track. We hypothesized that this ballistic-release task would encourage subjects to modify their arm impedance in anticipation of the upcoming movement. We modeled the behavior as a physical dynamical system and found that one component of model impedance, stiffness, varied in a way that matched the behavioral demands of the task and that stiffness could be dissociated from changes in force and displacement. We recorded activity from a population of motor cortical neurons and found that the temporal and time-averaged neural responses encoded information about motion and force. We also could decode model impedance parameters that we then used to approximate the time-varying force exerted on the handle. The force exerted on the handle and the model stiffness depended on muscle activity and we found components of muscle activity related to both force and model stiffness. Additional components of motor cortical activity were also related to both force and stiffness, suggesting a possible parceling of muscle-related representations in motor cortical activity. In addition to extending current models of neural activity to include manipulations, this study may be helpful in understanding how information encoded in motor cortical activity might be transformed into muscle activity during object interaction