Coordination Control of a Dual-Arm Exoskeleton Robot Using Human Impedance Transfer Skills

This paper has developed a coordination control method for a dual-arm exoskeleton robot based on human impedance transfer skills, where the left (master) robot arm extracts the human limb impedance stiffness and position profiles, and then transfers the information to the right (slave) arm of the exoskeleton. A computationally efficient model of the arm endpoint stiffness behavior is developed and a co-contraction index is defined using muscular activities of a dominant antagonistic muscle pair. A reference command consisting of the stiffness and position profiles of the operator is computed and realized by one robot in real-time. Considering the dynamics uncertainties of the robotic exoskeleton, an adaptive-robust impedance controller in task space is proposed to drive the slave arm tracking the desired trajectories with convergent errors. To verify the robustness of the developed approach, a study of combining adaptive control and human impedance transfer control under the presence of unknown interactive forces is conducted. The experimental results of this paper suggest that the proposed control method enables the subjects to execute a coordination control task on a dual-arm exoskeleton robot by transferring the stiffness from the human arm to the slave robot arm, which turns out to be effective

Adaptive Compliance Shaping with Human Impedance Estimation

Human impedance parameters play an integral role in the dynamics of strength amplification exoskeletons. Many methods are used to estimate the stiffness of human muscles, but few are used to improve the performance of strength amplification controllers for these devices. We propose a compliance shaping amplification controller incorporating an accurate online human stiffness estimation from surface electromyography (sEMG) sensors and stretch sensors connected to the forearm and upper arm of the human. These sensor values along with exoskeleton position and velocity are used to train a random forest regression model that accurately predicts a person's stiffness despite varying movement, relaxation, and muscle co-contraction. Our model's accuracy is verified using experimental test data and the model is implemented into the compliance shaping controller. Ultimately we show that the online estimation of stiffness can improve the bandwidth and amplification of the controller while remaining robustly stable.Comment: 8 pages, 9 figures, Accepted for publication at the 2020 American Control Conference. Copyright IEEE 202

Design and tele-impedance control of a variable stiffness transradial hand prosthesis

According to theWorld Health Organization, only about the half of upper extremity amputees receive prosthetic limbs and only the half of this group consistently use their prosthetic limbs. The prominent reasons that hinder widespread adaptation of prosthetic devices are their high cost, non-intuitive control interface and insufficient dexterity for performing activities of daily living. This dissertation aims to address these challenges and presents the design, implementation, experimental characterization and human subject studies of a low cost, customizable, variable stiffness transradial hand prosthesis controlled through a natural human-machine interface. The transradial hand prosthesis features a low cost, robust, adaptive and lightweight design, thanks to its tendon-driven, under-actuated, compliant fingers and variable stiffness actuation. In particular, the underactuated compliant ngers feature high dexterity by naturally adapting to different object geometries and provide impact resistance. Antagonistically arranged Bowden-cable based variable stiffness actuation enables independent modulation of the impedance and position of the main tendon of prosthesis. Moreover, Bowden-cable based transmission allows for the actuator/ reduction/power module to be opportunistically placed remotely, away from the transradial hand prosthesis, helping significantly decrease the weight of the device. Furthermore, the transradial hand prosthesis, including the compliant fingers, can be implemented through simple and low-cost manufacturing processes, such as 3D printing, and each prosthesis can be customized to ensure an ideal fit to match the needs of the transradial amputee

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

Adaptive compliance shaping with human impedance estimation

Robotics has been a promising and popular research area for the past few decades. Among various applications of robotic, in many cases, human are involved in different manners. Therefore, as an important sub research area of robotics, human robot interaction has drawn decent attention recently. It has been deeply and widely studied. For human robot interaction, human play an important role. Undoubtedly, the more we know about human, the easier we can do human robot interaction and the better performance we can achieve in human robot interaction. One fascinating research topic of human robot interaction would be human in exoskeleton, where human play a key role in the mechanical design of exoskeleton as well as the control strategy design of exoskeleton. Among all those applications, the augmentation exoskeleton is especially interesting due to its ability to amplify human. As mentioned previously, human properties are important for the design of exoskeleton. Unfortunately, despite many inspiring and deep studies about human properties and various proposed human models, human remains to be a complicated system that is hard to predict and model. Furthermore, human is a dynamic system whose parameters keep changing with time, bringing more challenges. As we all know, limited understanding of the control plant will limit the performance of the controller and bring difficulties in the design of a controller. In fact, the performance of many existed controller for augmentation exoskeleton is limited by using conservative values of human property parameters. A straightforward way to solve this problem is to estimate human properties online. Under this circumstance, the main challenges are to develop a control strategy, whose performance can be exploited using the estimation of human properties and a reliable method to online estimate human properties. This thesis mainly presents an adaptive compliance shaping control strategy with human impedance estimation and a brief review of a newly proposed complex stiffness model of human.Mechanical Engineerin

Unobtrusive, natural support control of an adaptive industrial exoskeleton using force myography

Repetitive or tiring tasks and movements during manual work can lead to serious musculoskeletal disorders and, consequently, to monetary damage for both the worker and the employer. Among the most common of these tasks is overhead working while operating a heavy tool, such as drilling, painting, and decorating. In such scenarios, it is desirable to provide adaptive support in order to take some of the load off the shoulder joint as needed. However, even to this day, hardly any viable approaches have been tested, which could enable the user to control such assistive devices naturally and in real time. Here, we present and assess the adaptive Paexo Shoulder exoskeleton, an unobtrusive device explicitly designed for this kind of industrial scenario, which can provide a variable amount of support to the shoulders and arms of a user engaged in overhead work. The adaptive Paexo Shoulder exoskeleton is controlled through machine learning applied to force myography. The controller is able to determine the lifted mass and provide the required support in real time. Twelve subjects joined a user study comparing the Paexo driven through this adaptive control to the Paexo locked in a fixed level of support. The results showed that the machine learning algorithm can successfully adapt the level of assistance to the lifted mass. Specifically, adaptive assistance can sensibly reduce the muscle activity’s sensitivity to the lifted mass, with an observed relative reduction of up to 31% of the muscular activity observed when lifting 2 kg normalized by the baseline when lifting no mass

ReHand - a portable assistive rehabilitation hand exoskeleton

This dissertation presents a synthesis of a novel underactuated exoskeleton (namely ReHand2) thought and designed for a task-oriented rehabilitation and/or for empower the human hand. The first part of this dissertation shows the current context about the robotic rehabilitation with a focus on hand pathologies, which influence the hand capability. The chapter is concluded with the presentation of ReHand2. The second chapter describes the human hand biomechanics. Starting from the definition of human hand anatomy, passing through anthropometric data, to taxonomy on hand grasps and finger constraints, both from static and dynamic point of view. In addition, some information about the hand capability are given. The third chapter analyze the current state of the art in hand exoskeleton for rehabilitation and empower tasks. In particular, the chapter presents exoskeleton technologies, from mechanisms to sensors, passing though transmission and actuators. Finally, the current state of the art in terms of prototype and commercial products is presented. The fourth chapter introduces the concepts of underactuation with the basic explanation and the classical notation used typically in the prosthetic field. In addition, the chapter describe also the most used differential elements in the prosthetic, follow by a statical analysis. Moreover typical transmission tree at inter-finger level as well as the intra- finger underactuation are explained . The fifth chapter presents the prototype called ReHand summarizing the device description and explanation of the working principle. It describes also the kinetostatic analysis for both, inter- and the intra-finger modules. in the last section preliminary results obtained with the exoskeleton are shown and discussed, attention is pointed out on prototype’s problems that have carry out at the second version of the device. The sixth chapter describes the evolution of ReHand, describing the kinematics and dynamics behaviors. In particular, for the mathematical description is introduced the notation used in order to analyze and optimize the geometry of the entire device. The introduced model is also implemented in Matlab Simulink environment. Finally, the chapter presents the new features. The seventh chapter describes the test bench and the methodologies used to evaluate the device statical, and dynamical performances. The chapter presents and discuss the experimental results and compare them with simulated one. Finally in the last chapter the conclusion about the ReHand project are proposed as well as the future development. In particular, the idea to test de device in relevant environments. In addition some preliminary considerations about the thumb and the wrist are introduced, exploiting the possibility to modify the entire layout of the device, for instance changing the actuator location

Mechanisms of Impaired Motor Unit Firing Behavior in the Vastus Lateralis Muscle after Stroke

The purpose of this dissertation research project was to examine the role of impaired motor unit firing behavior on force generation after a stroke. We studied the relationship between intrinsic motoneuron properties and inhibitory sensory pathways to deficient motoneuron activity in the vastus lateralis muscle after a stroke. Individuals with stroke often have deficits with force generation and volitional relaxation. Current models of impaired force output after a stroke focus primarily on the pathology within the corticospinal pathway because of decreased descending drive. Though this is an important aspect of deficient motoneuron output, it is incomplete because motoneurons receive other inputs that can shape motor output. Because the motoneuron is the last site of signal integration for muscle contractions, using methods that study motor unit activity can provide a window to the activity in the spinal circuitry. This research study utilized a novel algorithm that decomposed electromyography (EMG) signals into the contributions of the individual motor units. This provided the individual firing instances for a large number of concurrently active motor units during isometric contractions of the knee extensors. In the first aim, the association between the hyperemic response and motor unit firing rate modulation to intermittent, fatiguing contractions was investigated. It was found that the magnitude of blood flow was lower for individuals with stroke compared to healthy controls, but both groups increased blood flow similarly in response to fatiguing contractions. This did not relate to changes in muscle fiber contractibility for the participants with stroke; rather, participants better able to increase blood flow showed greater modulation in motor unit firing rates. To further investigate how ischemic conditions impact motor unit output, the second aim used a blood pressure cuff to completely occlude blood flow through the femoral artery with the intent of activating inhibitory afferent pathways. We found that ischemic conditions had a greater inhibitory impact on motor unit output for individuals with stroke compared to healthy controls, possibly because of hyper-excitable group III/IV afferent pathways. The final aim investigated how stroke related changes in the intrinsic excitability of the motoneurons impacted prolonged motor unit firing during voluntary relaxation. A serotonin reuptake inhibitor was administered to quantify motoneuron sensitivity to neuromodulatory inputs. This study found that the serotonin reuptake inhibitor increased muscle relaxation and may have reduced persistent inward current contributions to prolonged motor unit firing. In conclusion, while damage to the corticospinal tract is a major component to poor functionality, the intrinsic properties of the motoneuron and sensory pathways to the motoneuron pool are essential for understanding deficient motor control after a stroke

Electromyography Based Human-Robot Interfaces for the Control of Artificial Hands and Wearable Devices

The design of robotic systems is currently facing human-inspired solutions as a road to replicate the human ability and flexibility in performing motor tasks. Especially for control and teleoperation purposes, the human-in-the-loop approach is a key element within the framework know as Human-Robot Interface. This thesis reports the research activity carried out for the design of Human-Robot Interfaces based on the detection of human motion intentions from surface electromyography. The main goal was to investigate intuitive and natural control solutions for the teleoperation of both robotic hands during grasping tasks and wearable devices during elbow assistive applications. The design solutions are based on the human motor control principles and surface electromyography interpretation, which are reviewed with emphasis on the concept of synergies. The electromyography based control strategies for the robotic hand grasping and the wearable device assistance are also reviewed. The contribution of this research for the control of artificial hands rely on the integration of different levels of the motor control synergistic organization, and on the combination of proportional control and machine learning approaches under the guideline of user-centred intuitiveness in the Human-Robot Interface design specifications. From the side of the wearable devices, the control of a novel upper limb assistive device based on the Twisted String Actuation concept is faced. The contribution regards the assistance of the elbow during load lifting tasks, exploring a simplification in the use of the surface electromyography within the design of the Human-Robot Interface. The aim is to work around complex subject-dependent algorithm calibrations required by joint torque estimation methods