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

Biomechatronics: Harmonizing Mechatronic Systems with Human Beings

This eBook provides a comprehensive treatise on modern biomechatronic systems centred around human applications. A particular emphasis is given to exoskeleton designs for assistance and training with advanced interfaces in human-machine interaction. Some of these designs are validated with experimental results which the reader will find very informative as building-blocks for designing such systems. This eBook will be ideally suited to those researching in biomechatronic area with bio-feedback applications or those who are involved in high-end research on manmachine interfaces. This may also serve as a textbook for biomechatronic design at post-graduate level

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

Development of a Wearable Exoskeleton for Arm Rehabilitation

With the increasing population of aging and disabled individuals, the need for a more effective and efficient solutions is at peak, Powered Exoskeletons are wearable robots that can be attached to the disabled limb with the goal of adding power to, or rectifying the limb functionality , one of its application is rehabilitation. This study review relevant research, technologies and products, while critically analyzing them and addressing some of the current problem faced by the researchers in this field, such as the use EMG signal as a primary input to the controller. This research propose an adaptive EMG-based upper limb exoskeleton that is built on a fuzzy controller. The paper strives to propose a wearable general-user Exoskeleton, Built around an interactive gaming interface to engage the patients in the rehabilitation process. The games and exoskeleton assistance degree can be preset – on medical supervision – to different training patterns. Ultimately, the project strives to afford normal daily life for those who needs it

Exoskeleton Technology in Rehabilitation: Towards an EMG-Based Orthosis System for Upper Limb Neuromotor Rehabilitation

The rehabilitation of patients should not only be limited to the first phases during intense hospital care but also support and therapy should be guaranteed in later stages, especially during daily life activities if the patient’s state requires this. However, aid should only be given to the patient if needed and as much as it is required. To allow this, automatic self-initiated movement support and patient-cooperative control strategies have to be developed and integrated into assistive systems. In this work, we first give an overview of different kinds of neuromuscular diseases, review different forms of therapy, and explain possible fields of rehabilitation and benefits of robotic aided rehabilitation. Next, the mechanical design and control scheme of an upper limb orthosis for rehabilitation are presented. Two control models for the orthosis are explained which compute the triggering function and the level of assistance provided by the device. As input to the model fused sensor data from the orthosis and physiology data in terms of electromyography (EMG) signals are used

Nonlinear control of a seven degrees-of-freedom exoskeleton robot arm

Advances in the field of robotics have allowed increasingly integrating robotic devices for rehabilitation of physical disabilities. This research work is encompassed into the field of rehabilitation robotics; it presents the development of the robot ETS-MARSE, a seven degrees-of-freedom exoskeleton designed to be worn in the human arm. The developments include the study and implementation of a relatively novel nonlinear control approach, as well as different rehabilitation schemes. One of the characteristics of a rehabilitation robot is that it deals with a wide number of patients that have different biomechanical and physiological conditions. The implementation of the nonlinear control technique known as Virtual Decomposition Control addresses this issue with its internal parameters’ adaptation that presents a robust behavior to different characteristics of the robot users. Besides, this technique simplifies the complexity of high degree-of-freedom robots by its innovative sub-systems decomposition. All of above, while ensuring the system asymptotic stability and excellent trajectory tracking. Between the different rehabilitation schemes, we can mention: passive, active-assistive and active rehabilitation. The first one follows predefined trajectories and relies on the efficiency of the controller. The two other schemes require understanding the user’s intention of movement and take an action in order to guide, restrain, correct or follow it. For this purpose, we present an approach that utilizes a force sensor as the human-robot interface in order to transform, via an admittance function, the forces that the user exert to the robot end-effector (handle), and execute active-assisted or active rehabilitation. Finally among the main developments of this work, an approach is presented in which the need of a force sensor to perform some active rehabilitation tasks is removed. By means of a nonlinear observer, the interaction forces are estimated and the user’s intention of movement followed. Experimental results show the effectiveness of all the proposed approaches. All the tests involving humans were tested with healthy subjects. Trajectory tracking of the robot is executed in joint space; some trajectories are given in Cartesian space and transformed to joint space by means of the pseudoinverse of the Jacobian technique. However this option is limited; a mandatory next step to improve many functionalities of the robot is to solve its inverse kinematics. Between other progresses that are in development, is an approach to process electromyographic signals in order to obtain information from the robot’s users. First results on this methodology are presented. Teleoperation and haptic capabilities are also in the initial stage of development

Two-Fingered Haptic Device for Robot Hand Teleoperation

A haptic feedback system is required to assist telerehabilitation with robot hand. The system should provide the reaction force measured in the robot hand to an operator. In this paper, we have developed a force feedback device that presents a reaction force to the distal segment of the operator's thumb, middle finger, and basipodite of the middle finger when the robot hand grasps an object. The device uses a shape memory alloy as an actuator, which affords a very compact, lightweight, and accurate device

Assessment of Myoelectric Controller Performance and Kinematic Behavior of a Novel Soft Synergy-Inspired Robotic Hand for Prosthetic Applications

Myoelectric artificial limbs can significantly advance the state of the art in prosthetics, since they can be used to control mechatronic devices through muscular activity in a way that mimics how the subjects used to activate their muscles before limb loss. However, surveys indicate that dissatisfaction with the functionality of terminal devices underlies the widespread abandonment of prostheses. We believe that one key factor to improve acceptability of prosthetic devices is to attain human likeness of prosthesis movements, a goal which is being pursued by research on social and human-robot interactions. Therefore, to reduce early abandonment of terminal devices, we propose that controllers should be designed so as to ensure effective task accomplishment in a natural fashion. In this work, we have analyzed and compared the performance of three types of myoelectric controller algorithms based on surface electromyography to control an underactuated and multi-degrees of freedom prosthetic hand, the SoftHand Pro. The goal of the present study was to identify the myoelectric algorithm that best mimics the native hand movements. As a preliminary step, we first quantified the repeatability of the SoftHand Pro finger movements and identified the electromyographic recording sites for able-bodied individuals with the highest signal-to-noise ratio from two pairs of muscles, i.e., flexor digitorum superficialis/extensor digitorum communis, and flexor carpi radialis/extensor carpi ulnaris. Able-bodied volunteers were then asked to execute reach-to-grasp movements, while electromyography signals were recorded from flexor digitorum superficialis/extensor digitorum communis as this was identified as the muscle pair characterized by high signal-to-noise ratio and intuitive control. Subsequently, we tested three myoelectric controllers that mapped electromyography signals to position of the SoftHand Pro. We found that a differential electromyography-to-position mapping ensured the highest coherence with hand movements. Our results represent a first step toward a more effective and intuitive control of myoelectric hand prostheses