Adaptive Control for Passive Kinesiotherapy ELLTIO

Exoskeletons are mechatronic devices used to increase human muscle strength and resistance. In the last decade these devices have become a very useful tool to assist active kinesiotherapy. This paper presents the design of exoskeleton focused on the rehabilitation of ankle and knee for the right leg. The construction of prototype like Exoskeleton for Lower Limb Training with Instrumented Orthoses （ELLTIO） using Series Elastic Actuator （SEA） to reduce the effort in the human joints, and a control law to perform a rehabilitation routine using an adaptive control scheme were first implemented in simulation to verify the control strategy and make a real rehabilitation test. The adaptive control law is proposed with the intention that the exoskeleton can adapt to user parameters at the time when performing the exercise. The results show the parameters estimation and tracking trajectory for the exoskeleton were proposed, and this trajectory could be a routine rehabilitation proposed by the therapist.     

Development and Analysis of an Electrically Actuated Lower Extremity Assistive Exoskeleton

An electrically actuated lower extremity exoskeleton is developed,in which only the knee joint is actuated actively while other joints linked by elastic elements are actuated passively.This paper describes the critical design criteria and presents the process of design and calculation of the actuation system.A flexible physical Human-Robot-Interaction (pHRI) measurement device is designed and applied to detect the human movement,which comprises two force sensors and two gasbags attached to the inner surface of the connection cuff.An online adaptive pHRI minimization control strategy is proposed and implemented to drive the robotic exoskeleton system to follow the motion trajectory of human limb.The measured pHRI information is fused by the Variance Weighted Average (VWA) method.The Mean Square Values (MSV) of pHRI and control torque are utilized to evaluate the performance of the exoskeleton.To improve the comfort level and reduce energy consumption,the gravity compensation is taken into consideration when the control law is designed.Finally,practical experiments are performed on healthy users.Experimental results show that the proposed system can assist people to walk and the outlined control strategy is valid and effective.     

Adaptive Control of Exoskeleton Robots for Periodic Assistive Behaviours Based on EMG Feedback Minimisation

In this paper we propose an exoskeleton control method for adaptive learning of assistive joint torque profiles in periodic tasks. We use human muscle activity as feedback to adapt the assistive joint torque behaviour in a way that the muscle activity is minimised. The user can then relax while the exoskeleton takes over the task execution. If the task is altered and the existing assistive behaviour becomes inadequate, the exoskeleton gradually adapts to the new task execution so that the increased muscle activity caused by the new desired task can be reduced. The advantage of the proposed method is that it does not require biomechanical or dynamical models. Our proposed learning system uses Dynamical Movement Primitives (DMPs) as a trajectory generator and parameters of DMPs are modulated using Locally Weighted Regression. Then, the learning system is combined with adaptive oscillators that determine the phase and frequency of motion according to measured Electromyography (EMG) signals. We tested the method with real robot experiments where subjects wearing an elbow exoskeleton had to move an object of an unknown mass according to a predefined reference motion. We further evaluated the proposed approach on a whole-arm exoskeleton to show that it is able to adaptively derive assistive torques even for multiple-joint motion.     

A Method for Numerical Simulation of Single Limb Ground Contact Events: Application to Heel-Toe Running

The objective of this work was to develop a method to simulate single-limb ground contact events, which may be applied to study musculoskeletal injuries associated with such movements. To achieve this objective, a three-dimensional musculoskeletal model was developed consisting of the equations of motion for the musculoskeletal system, and models for the muscle force generation and ground contact elements. An optimization framework and a weighted least-squares objective function were presented that generated muscle stimulation patterns that optimally reproduced subject-specific movement data. Experimental data were collected from a single subject to provide initial conditions for the simulation and tracking data for the optimization. As an example application, a simulation of the stance phase of running was generated. The results showed that the average difference between the simulation and subject's ground reaction force and joint angle data was less than two inter-trial standard deviations. Further, there was good agreement between the model's muscle excitation patterns and experimentally collected electromyography data. These results give confidence in the model to examine musculoskeletal loading during a variety of landing movements and to study the effects of various factors associated with injury. Limitations were examined and areas of improvement for the model were presented.     

Estimation of muscle response using three-dimensional musculoskeletal models before impact situation: a simulation study

When car crash experiments are performed using cadavers or dummies, the active muscles' reaction on crash situations cannot be observed. The aim of this study is to estimate muscles' response of the major muscle groups using three-dimensional musculoskeletal model by dynamic simulations of low-speed sled-impact. The three-dimensional musculoskeletal models of eight subjects were developed, including 241 degrees of freedom and 86 muscles. The muscle parameters considering limb lengths and the force-generating properties of the muscles were redefined by optimization to fit for each subject. Kinematic data and external forces measured by motion tracking system and dynamometer were then input as boundary conditions. Through a least-squares optimization algorithm, active muscles' responses were calculated during inverse dynamic analysis tracking the motion of each subject. Electromyography for major muscles at elbow, knee, and ankle joints was measured to validate each model. For low-speed sled-impact crash, experiment and simulation with optimized and unoptimized muscle parameters were performed at 9.4 m/h and 10 m/h and muscle activities were compared among them. The muscle activities with optimized parameters were closer to experimental measurements than the results without optimization. In addition, the extensor muscle activities at knee, ankle, and elbow joint were found considerably at impact time, unlike previous studies using cadaver or dummies. This study demonstrated the need to optimize the muscle parameters to predict impact situation correctly in computational studies using musculoskeletal models. And to improve accuracy of analysis for car crash injury using humanlike dummies, muscle reflex function, major extensor muscles' response at elbow, knee, and ankle joints, should be considered.     

Contribution of muscle short-range stiffness to initial changes in joint kinetics and kinematics during perturbations to standing balance: A simulation study

Simulating realistic musculoskeletal dynamics is critical to understanding neural control of muscle activity evoked in sensorimotor feedback responses that have inherent neural transmission delays. Thus, the initial mechanical response of muscles to perturbations in the absence of any change in muscle activity determines which corrective neural responses are required to stabilize body posture. Muscle short-range stiffness, a history-dependent property of muscle that causes a rapid and transient rise in muscle force upon stretch, likely affects musculoskeletal dynamics in the initial mechanical response to perturbations. Here we identified the contributions of short-range stiffness to joint torques and angles in the initial mechanical response to support surface translations using dynamic simulation. We developed a dynamic model of muscle short-range stiffness to augment a Hill-type muscle model. Our simulations show that short-range stiffness can provide stability against external perturbations during the neuromechanical response delay. Assuming constant muscle activation during the initial mechanical response, including muscle short-range stiffness was necessary to account for the rapid rise in experimental sagittal plane knee and hip joint torques that occurs simultaneously with very small changes in joint angles and reduced root mean square errors between simulated and experimental torques by 56% and 47%, respectively. Moreover, forward simulations lacking short-range stiffness produced unreasonably large joint angle changes during the initial response. Using muscle models accounting for short-range stiffness along with other aspects of history-dependent muscle dynamics may be important to advance our ability to simulate inherently unstable human movements based on principles of neural control and biomechanics.     

State Classification and Motion Description for the Lower Extremity Exoskeleton SJTU-EX

A lower extremity exoskeleton, SJTU-EX, is proposed, which mainly aims to help soldiers and workers to support a payload in motions. To solve the issues of the exoskeleton-environment and exoskeleton-human interactions, four types of foot contact are proposed based on their different kinematic characteristics. By the combination of single leg states, sixteen exo- skeleton states are presented using a series of meaningful notations from the topological point of view. The generalized function set （GF set） theory is employed to achieve the kinematic characteristics of the end effectors in different states. Moreover six mathematical formulations of the dynamics of the exoskeleton and its interactions with the human wearer are developed for different exoskeleton states. The applicability and potential of the proposed classification method are demonstrated by analyzing common lower limb motions, which are described concisely by a sequence of notations. Finally, a new concept of characteristic state is put forward to uniquely indicate the type of motion.     

Forward dynamic optimization of handle path and muscle activity for handle based isokinetic wheelchair propulsion: A simulation study

Push-rim wheelchair propulsion is biomechanically inefficient and physiologically stressful to the musculoskeletal structure of human body. This study focuses to obtain a new, optimized propulsion shape for wheelchair users, which is within the ergonomic ranges of joint motion, thus reducing the probability of injuries. To identify the propulsion movement, forward dynamic optimization was performed on a 3D human musculoskeletal model linked to a handle based propulsion mechanism, having shape and muscle excitations as optimization variables. The optimization resulted in a handle path shape with a circularity ratio of 0.95, and produced a net propulsion power of 34.7 watts for an isokinetic propulsion cycle at 50?rpm. Compared to push-rim propulsion, the compact design of the new propulsion mechanism along with the ergonomically optimized propulsion shape may help to reduce the risk of injuries and thus improve the quality of life for wheelchair users.     

Implementation of controlling strategy in a biomechanical lower limb model with active muscles for coupling multibody dynamics and finite element analysis

Computational biomechanics for human body modeling has generally been categorized into two separated domains: finite element analysis and multibody dynamics. Combining the advantages of both domains is necessary when tissue stress and physical body motion are both of interest. However, the method for this topic is still in exploration. The aim of this study is to implement unique controlling strategies in finite element model for simultaneously simulating musculoskeletal body dynamics and in vivo stress inside human tissues. A finite element lower limb model with 3D active muscles was selected for the implementation of controlling strategies, which was further validated against in-vivo human motion experiments. A unique feedback control strategy that couples together a basic Proportion-Integration-Differentiation (PID) controller and generic active signals from Computed Muscle Control (CMC) method of the musculoskeletal model or normalized EMG singles was proposed and applied in the present model. The results show that the new proposed controlling strategy show a good correlation with experimental test data of the normal gait considering joint kinematics, while stress distribution of local lower limb tissue can be also detected in real-time with lower limb motion. In summary, the present work is the first step for the application of active controlling strategy in the finite element model for concurrent simulation of both body dynamics and tissue stress. In the future, the present method can be further developed to apply it in various fields for human biomechanical analysis to monitor local stress and strain distribution by simultaneously simulating human locomotion.     

Estimation of accuracy of patient-specific musculoskeletal modelling: case study on a post polio residual paralysis subject

For patients with patterns ranging out of anthropometric standard values, patient-specific musculoskeletal modelling becomes crucial for clinical diagnosis and follow-up. However, patient-specific modelling using imaging techniques and motion capture systems is mainly subject to experimental errors. The aim of this study was to quantify these experimental errors when performing a patient-specific musculoskeletal model. CT scan data were used to personalise the geometrical model and its inertial properties for a post polio residual paralysis subject. After having performed a gait-based experimental protocol, kinematics data were measured using a VICON motion capture system with six infrared cameras. The musculoskeletal model was computed using a direct/inverse algorithm (LifeMod software). A first source of errors was identified in the segmentation procedure in relation to the calculation of personalised inertial parameters. The second source of errors was subject related, as it depended on the reproducibility of performing the same type of gait. The impact of kinematics, kinetics and muscle forces resulting from the musculoskeletal modelling was quantified using relative errors and the absolute root mean square error. Concerning the segmentation procedure, we found that the kinematics results were not sensitive to the errors (relative error < 1%). However, a strong influence was noted on the kinetics results (deviation up to 71%). Furthermore, the reproducibility error showed a significant influence (relative mean error varying from 5 to 30%). The present paper demonstrates that in patient-specific musculoskeletal modelling variations due to experimental errors derived from imaging techniques and motion capture need to be both identified and quantified. Therefore, the paper can be used as a guideline.     

Interactive computer graphics in the study of human body planar motion under free fall conditions

A computer program utilizing interactive graphics was developed in order to study the planar motion of a five-segment model of the human body. By providing instantaneous feedback and convenient graphical representation of the body, the program allows the user to quickly simulate and study body motions of interest. Consequently, the model is a useful tool for the researcher and may be readily employed for student instructional purposes.The configuration of the model, and the derivation and validation of the equations of motion, are included. Several options provided by the simulation are described.     

Robotics-based synthesis of human motion

The synthesis of human motion is a complex procedure that involves accurate reconstruction of movement sequences, modeling of musculoskeletal kinematics, dynamics and actuation, and characterization of reliable performance criteria. Many of these processes have much in common with the problems found in robotics research. Task-based methods used in robotics may be leveraged to provide novel musculoskeletal modeling methods and physiologically accurate performance predictions. In this paper, we present (i) a new method for the real-time reconstruction of human motion trajectories using direct marker tracking, (ii) a task-driven muscular effort minimization criterion and (iii) new human performance metrics for dynamic characterization of athletic skills. Dynamic motion reconstruction is achieved through the control of a simulated human model to follow the captured marker trajectories in real-time. The operational space control and real-time simulation provide human dynamics at any configuration of the performance. A new criteria of muscular effort minimization has been introduced to analyze human static postures. Extensive motion capture experiments were conducted to validate the new minimization criterion. Finally, new human performance metrics were introduced to study in details an athletic skill. These metrics include the effort expenditure and the feasible set of operational space accelerations during the performance of the skill. The dynamic characterization takes into account skeletal kinematics as well as muscle routing kinematics and force generating capacities. The developments draw upon an advanced musculoskeletal modeling platform and a task-oriented framework for the effective integration of biomechanics and robotics methods.     

The influence of an elastic tendon on the force producing capabilities of a muscle during dynamic movements

With increasing computer power, computer simulation of human movement has become a popular research tool. However, time to complete simulations can still be long even on powerful computers. One possibility for reducing simulation time, with models of musculo-skeletal system, is to simulate the muscle using a rigid tendon rather than the more realistic compliant tendon. This study examines the effect of tendon elasticity on muscle force output under different dynamic conditions. A single muscle, point mass model was used and simulations were performed varying the mass, the tendon length, the initial position, and the task. For simulations for relatively slow motion, as experienced for example in upper limb reaching motions or rising from a chair, tendon properties had little influence on muscle force, in contrast simulations of an explosive task similar to jumping or throwing tendon had a much larger effect.     

A simulation support system for solving large physiological models on microcomputers

Although physiological modeling and computer simulation have become useful research tools to test new scientific theories and to design and analyze laboratory experiments, developing a new model can be a tedious process because the investigator must often write very complex and specific routines for data input and output. To facilitate the design of new models (as well as the use of existing models), we have developed MODSIM, a FORTRAN-based simulation support system for the IBM PC computer than can accommodate very large dynamic models having up to several thousand equations. It provides the investigator with utilities for continuous on-line graphical and/or tubular output, as well as facilities for dynamic interaction with the model. The user must only supply a model as a list of mathematical equations written in FORTRAN, along with the initial values of the model variables and parameters. The model is precompiled, compiled, and then linked to the MODSIM utilities. Without further programming, the user can then solve the model, select variables for graphical output, and stop the model at any time to analyze the data or to change a parameter before resuming the simulation. This simulation system makes it very easy to develop new models that actively interact with the experimental research of the investigator.     

The influence of an elastic tendon on the force producing capabilities of a muscle during dynamic movements

With increasing computer power, computer simulation of human movement has become a popular research tool. However, time to complete simulations can still be long even on powerful computers. One possibility for reducing simulation time, with models of musculo-skeletal system, is to simulate the muscle using a rigid tendon rather than the more realistic compliant tendon. This study examines the effect of tendon elasticity on muscle force output under different dynamic conditions. A single muscle, point mass model was used and simulations were performed varying the mass, the tendon length, the initial position, and the task. For simulations for relatively slow motion, as experienced for example in upper limb reaching motions or rising from a chair, tendon properties had little influence on muscle force, in contrast simulations of an explosive task similar to jumping or throwing tendon had a much larger effect.     

A benchtop biorobotic platform for in vitro observation of muscle-tendon dynamics with parallel mechanical assistance from an elastic exoskeleton

We present a novel biorobotic framework comprised of a biological muscle-tendon unit (MTU) mechanically coupled to a feedback controlled robotic environment simulation that mimics in vivo inertial/gravitational loading and mechanical assistance from a parallel elastic exoskeleton. Using this system, we applied select combinations of biological muscle activation (modulated with rate-coded direct neural stimulation) and parallel elastic assistance (applied via closed-loop mechanical environment simulation) hypothesized to mimic human behavior based on previously published modeling studies. These conditions resulted in constant system-level force-length dynamics (i.e., stiffness), reduced biological loads, increased muscle excursion, and constant muscle average positive power output—all consistent with laboratory experiments on intact humans during exoskeleton assisted hopping. Mechanical assistance led to reduced estimated metabolic cost and MTU apparent efficiency, but increased apparent efficiency for the MTU + Exo system as a whole. Findings from this study suggest that the increased natural resonant frequency of the artificially stiffened MTU + Exo system, along with invariant movement frequencies, may underlie observed limits on the benefits of exoskeleton assistance. Our novel approach demonstrates that it is possible to capture the salient features of human locomotion with exoskeleton assistance in an isolated muscle-tendon preparation, and introduces a powerful new tool for detailed, direct examination of how assistive devices affect muscle-level neuromechanics and energetics.     

A novel two-layer, coupled finite element approach for modeling the nonlinear elastic and viscoelastic behavior of human erythrocytes

A novel finite element approach is presented to simulate the mechanical behavior of human red blood cells (RBC, erythrocytes). As the RBC membrane comprises a phospholipid bilayer with an intervening protein network, we propose to model the membrane with two distinct layers. The fairly complex characteristics of the very thin lipid bilayer are represented by special incompressible solid shell elements and an anisotropic viscoelastic constitutive model. Properties of the protein network are modeled with an isotropic hyperelastic third-order material. The elastic behavior of the model is validated with existing optical tweezers studies with quasi-static deformations. Employing material parameters consistent with literature, simulation results are in excellent agreement with experimental data. Available models in literature neglect either the surface area conservation of the RBC membrane or realistic loading conditions of the optical tweezers experiments. The importance of these modeling assumptions, that are both included in this study, are discussed and their influence quantified. For the simulation of the dynamic motion of RBC, the model is extended to incorporate the cytoplasm. This is realized with a monolithic fully coupled fluid-structure interaction simulation, where the fluid is described by the incompressible Navier–Stokes equations in an arbitrary Lagrangian Eulerian framework. It is shown that both membrane viscosity and cytoplasm viscosity have significant influence on simulation results. Characteristic recovery times and energy dissipation for varying strain rates in dynamic laser trap experiments are calculated for the first time and are found to be comparable with experimental data.     

Development and validation of a multi-body model of the canine stifle joint

Multi-body musculoskeletal models that can be used concurrently to predict joint contact pressures and muscle forces would be extremely valuable in studying the mechanics of joint injury. The purpose of this study was to develop an anatomically correct canine stifle joint model and validate it against experimental data. A cadaver pelvic limb from one adult dog was used in this study. The femoral head was subjected to axial motion in a mechanical tester. Kinematic and force data were used to validate the computational model. The maximum RMS error between the predicted and measured kinematics during the complete testing cycle was 11.9 mm translational motion between the tibia and the femur and 4.3° rotation between patella and femur. This model is the first step in the development of a musculoskeletal model of the hind limb with anatomically correct joints to study cartilage loading under dynamic conditions.     

Modulation of shoulder muscle and joint function using a powered upper-limb exoskeleton

Robotic-assistive exoskeletons can enable frequent repetitive movements without the presence of a full-time therapist; however, human-machine interaction and the capacity of powered exoskeletons to attenuate shoulder muscle and joint loading is poorly understood. This study aimed to quantify shoulder muscle and joint force during assisted activities of daily living using a powered robotic upper limb exoskeleton (ArmeoPower, Hocoma). Six healthy male subjects performed abduction, flexion, horizontal flexion, reaching and nose touching activities. These tasks were repeated under two conditions: (i) the exoskeleton compensating only for its own weight, and (ii) the exoskeleton providing full upper limb gravity compensation (i.e., weightlessness). Muscle EMG, joint kinematics and joint torques were simultaneously recorded, and shoulder muscle and joint forces calculated using personalized musculoskeletal models of each subject’s upper limb. The exoskeleton reduced peak joint torques, muscle forces and joint loading by up to 74.8% (0.113 Nm/kg), 88.8% (5.8%BW) and 68.4% (75.6%BW), respectively, with the degree of load attenuation strongly task dependent. The peak compressive, anterior and superior glenohumeral joint force during assisted nose touching was 36.4% (24.6%BW), 72.4% (13.1%BW) and 85.0% (17.2%BW) lower than that during unassisted nose touching, respectively. The present study showed that upper limb weight compensation using an assistive exoskeleton may increase glenohumeral joint stability, since deltoid muscle force, which is the primary contributor to superior glenohumeral joint shear, is attenuated; however, prominent exoskeleton interaction moments are required to position and control the upper limb in space, even under full gravity compensation conditions. The modeling framework and results may be useful in planning targeted upper limb robotic rehabilitation tasks.     

A multi-phase optimal control technique for the simulation of a human vertical jump

A multi-phase optimal control technique is presented that can be used to solve dynamic optimization problems involving musculoskeletal systems. The biomechanical model consists of a set of differential equations describing the dynamics of the multi-body system and the generation of the dynamic forces of the human muscles. Within the optimization technique, subintervals can be defined in which the differential equations are continuous. At the boundaries the dimension of the state- and control vector as well as the dimension of the right-hand side may change. The problem is solved by a multiple shooting approach which converts the problem into a non-linear program. The method is applied to simulate a human jump movement.