Robotics rehabilitation of the elbow based on surface electromyography signals

Physical rehabilitation based on robotic systems has the potential to cover the patient’s need of improvement of upper extremity functionalities. In this article, the state of the art of resistant and assistive upper limb exoskeleton robots and their control are thoroughly investigated. Afterward, a single-degree-of-freedom exoskeleton matching the elbow–forearm has been advanced to grant a valid rehabilitation therapy for persons with physical disability of upper limb motion. The authors have focused on the control system based on the use of electromyography signals as an input to drive the joint movement and manage the robotics arm. The correlation analysis between surface electromyography signal and the force exerted by the subject was studied in objects’ grasping tests with the purpose of validating the methodology. The authors developed an innovative surface electromyography force–based active control that adjusts the force exerted by the device during rehabilitation. The control was validated by an experimental campaign on healthy subjects simulating disease on an arm, with positive results that confirm the proposed solution and that open the way to future researches

A sEMG-driven Musculoskeletal Model to Control Exoskeleton Robot Used in Lower Extremity Rehabilitation

A control system framework of lower extremity rehabilitation exoskeleton robot is presented. It is based on the Neuro-Musculo-Skeletal biological model. Its core composition module, the motion intent parser part, mainly comprises of three distinct parts. The first part is signal acquisition of surface electromyography (sEMG) that is the summation of motor unit action potential (MUAP) starting from central nervous system (CNS).sEMG can be used to decode action intent of operator to make the patient actively participate in specific training .As another composition part, a muscle dynamics model that is comprised of activation and contraction dynamic model is developed. It is mainly used to calculate muscle force. The last part is the skeletal dynamic model that is simplified as a linked segment mechanics. Combined with muscle dynamic model, the joint torque exerted by internal muscles can be exported, which can be used to do a exoskeleton controller design. The developed control framework can make exoskeleton offer assistance to operators during rehabilitation by guiding motions on correct training rehabilitation trajectories, or give force support to be able to perform certain motions. Though the presentation is orientated towards the lower extremity exoskeleton, it is generic and can be applied to almost any part of the human body

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

Non-linear actuators and simulation tools for rehabilitation devices

Mención Internacional en el título de doctorRehabilitation robotics is a field of research that investigates the applications of robotics in motor function therapy for recovering the motor control and motor capability. In general, this type of rehabilitation has been found effective in therapy for persons suffering motor disorders, especially due to stroke or spinal cord injuries. This type of devices generally are well tolerated by the patients also being a motivation in rehabilitation therapy. In the last years the rehabilitation robotics has become more popular, capturing the attention at various research centers. They focused on the development more effective devices in rehabilitation therapy, with a higher acceptance factor of patients tacking into account: the financial cost, weight and comfort of the device. Among the rehabilitation devices, an important category is represented by the rehabilitation exoskeletons, which in addition to the human skeletons help to protect and support the external human body. This became more popular between the rehabilitation devices due to the easily adapting with the dynamics of human body, possibility to use them such as wearable devices and low weight and dimensions which permit easy transportation. Nowadays, in the development of any robotic device the simulation tools play an important role due to their capacity to analyse the expected performance of the system designed prior to manufacture. In the development of the rehabilitation devices, the biomechanical software which is capable to simulate the behaviour interaction between the human body and the robotics devices, play an important role. This helps to choose suitable actuators for the rehabilitation device, to evaluate possible mechanical designs, and to analyse the necessary controls algorithms before being tested in real systems. This thesis presents a research proposing an alternative solution for the current systems of actuation on the exoskeletons for robotic rehabilitation. The proposed solution, has a direct impact, improving issues like device weight, noise, fabrication costs, size an patient comfort. In order to reach the desired results, a biomechanical software based on Biomechanics of Bodies (BoB) simulator where the behaviour of the human body and the rehabilitation device with his actuators can be analysed, was developed. In the context of the main objective of this research, a series of actuators have been analysed, including solutions between the non-linear actuation systems. Between these systems, two solutions have been analysed in detail: ultrasonic motors and Shape Memory Alloy material. Due to the force - weight characteristics of each device (in simulation with the human body), the Shape Memory Alloy material was chosen as principal actuator candidate for rehabilitation devices. The proposed control algorithm for the actuators based on Shape Memory Alloy, was tested over various configurations of actuators design and analysed in terms of energy eficiency, cooling deformation and movement. For the bioinspirated movements, such as the muscular group's biceps-triceps, a control algorithm capable to control two Shape Memory Alloy based actuators in antagonistic movement, has been developed. A segmented exoskeleton based on Shape Memory Alloy actuators for the upper limb evaluation and rehabilitation therapy was proposed to demosntrate the eligibility of the actuation system. This is divided in individual rehabilitation devices for the shoulder, elbow and wrist. The results of this research was tested and validated in the real elbow exoskeleton with two degrees of freedom developed during this thesis.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Eduardo Rocón de Lima.- Secretario: Concepción Alicia Monje Micharet.- Vocal: Martin Stoele

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

Design and development of the sEMG-based exoskeleton strength enhancer for the legs

This paper reviews the different exoskeleton designs and presents a working prototype of a surface electromyography (EMG) controlled exoskeleton to enhance the strength of the lower leg. The Computer Aided Design (CAD) model of the exoskeleton is designed,3D printed with respect to the golden ratio of human anthropometry, and tested structurally. The exoskeleton control system is designed on the LabVIEW National Instrument platform and embedded in myRIO. Surface EMG sensors (sEMG) and flex sensors are usedcoherently to create different state filters for the EMG, human body posture and control for the mechanical exoskeleton actuation. The myRIO is used to process sEMG signals and send control signals to the exoskeleton. Thus,the complete exoskeleton system consists of sEMG as primary sensor and flex sensor as a secondary sensor while the whole control system is designed in LabVIEW. FEA simulation and tests show that the exoskeleton is suitable for an average human weight of 62 kg plus excess force with different reactive spring forces. However, due to the mechanical properties of the exoskeleton actuator, it will require an additional liftto provide the rapid reactive impulse force needed to increase biomechanical movement such as squatting up. Finally, with the increasing availability of such assistive devices on the market, the important aspect of ethical, social and legal issues have also emerged and discussed in this paper

Single Lead EMG signal to Control an Upper Limb Exoskeleton Using Embedded Machine Learning on Raspberry Pi

Post-stroke can cause partial or complete paralysis of the human limb. Delayed rehabilitation steps in post-stroke patients can cause muscle atrophy and limb stiffness. Post-stroke patients require an upper limb exoskeleton device for the rehabilitation process. Several previous studies used more than one electrode lead to control the exoskeleton. The use of many electrode leads can lead to an increase in complexity in terms of hardware and software. Therefore, this research aims to develop single lead EMG pattern recognition to control an upper limb exoskeleton. The main contribution of this research is that the robotic upper limb exoskeleton device can be controlled using a single lead EMG. EMG signals were tapped at the biceps point with a sampling frequency of 2000 Hz. A Raspberry Pi 3B+ was used to embed the data acquisition, feature extraction, classification and motor control by using multithread algorithm. The exoskeleton arm frame is made using 3D printing technology using a high torque servo motor drive. The control process is carried out by extracting EMG signals using EMG features (mean absolute value, root mean square, variance) further extraction results will be trained on machine learning (decision tree (DT), linear regression (LR), polynomial regression (PR), and random forest (RF)). The results show that machine learning decision tree and random forest produce the highest accuracy compared to other classifiers. The accuracy of DT and RF are of 96.36±0.54% and 95.67±0.76%, respectively. Combining the EMG features, shows that there is no significant difference in accuracy (p-value 0.05). A single lead EMG electrode can control the upper limb exoskeleton robot device well