Development of a model for sEMG based joint-torque estimation using Swarm techniques

© 2016 IEEE. Over the years, numerous researchers have explored the relationship between surface electromyography (sEMG) signal with joint torque that would be useful to develop a suitable controller for rehabilitation robot. This research focuses on the transformation of sEMG signal by adopting a mathematical model to find the estimated joint torque of knee extension. Swarm techniques such as Particle Swarm Optimization (PSO) and Improved Particle Swarm Optimization (IPSO) were adapted to optimize the mathematical model for estimated joint torque. The correlation between the estimated joint torque and actual joint torque were determined by Coefficient of Determination (R2) and fitness value of Sum Squared Error (SSE). The outcome of the research shows that both the PSO and IPSO have yielded promising results

ARCTiC LawE: armed robotic control for training in civilian law enforcement

Much of this thesis looked at performing a cogent literature review of exoskeletons to determine the state-of-the-art and to determine the remaining needs in exoskeletal design. The literature review of over 80 journals, allowed the researcher to determine the lack of research in upper body exoskeletons for training in civilian, military, and law enforcement personnel. Thus the genesis of the Armed Robotic Control for Training in Civilian Law Enforcement, or ARCTiC LawE, an upper body exoskeleton designed to assist civilian, military, and law enforcement personnel in accurate, precise, and reliable handgun techniques. This exoskeleton training utilizes a laser based handgun with similar dimensions, trigger pull, and break action to a Glock ® 19 pistol, common to both public and private security sectors. The project aims to train and test subjects with no handgun training/experience with the ARCTiC LawE, and without, and compare the results of accuracy, precision, and speed. Ultimately, the exoskeleton greatly impacts sensory motor learning and the biomechanical implications are confirmed via both performance and physiological measurements. The researchers believe the ARCTiC LawE to be a viable substitute for training with live fire hand guns to reduce the cost of training time and munitions and will increase accuracy and precisions for typical law enforcement and military live fire drills. Additionally, this project increases the breadth of knowledge for exoskeletons as a tool for training

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

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

Reviewing high-level control techniques on robot-assisted upper-limb rehabilitation

This paper presents a comprehensive review of high-level control techniques for upper-limb robotic training. It aims to compare and discuss the potentials of these different control algorithms, and specify future research direction. Included studies mainly come from selected papers in four review articles. To make selected studies complete and comprehensive, especially some recently-developed upper-limb robotic devices, a search was further conducted in IEEE Xplore, Google Scholar, Scopus and Web of Science using keywords (‘upper limb*’ or ‘upper body*’) and (‘rehabilitation*’ or ‘treatment*’) and (‘robot*’ or ‘device*’ or ‘exoskeleton*’). The search is limited to English-language articles published between January 2013 and December 2017. Valuable references in related publications were also screened. Comparative analysis shows that high-level interaction control strategies can be implemented in a range of methods, mainly including impedance/admittance based strategies, adaptive control techniques, and physiological signal control. Even though the potentials of existing interactive control strategies have been demonstrated, it is hard to identify the one leading to maximum encouragement from human users. However, it is reasonable to suggest that future studies should combine different control strategies to be application specific, and deliver appropriate robotic assistance based on physical disability levels of human users

Machine Learning in Robot Assisted Upper Limb Rehabilitation: A Focused Review

Robot-assisted rehabilitation, which can provide repetitive, intensive and high-precision physics training, has a positive influence on motor function recovery of stroke patients. Current robots need to be more intelligent and more reliable in clinical practice. Machine learning algorithms (MLAs) are able to learn from data and predict future unknown conditions, which is of benefit to improve the effectiveness of robot-assisted rehabilitation. In this paper, we conduct a focused review on machine learning-based methods for robot-assisted upper limb rehabilitation. Firstly, the current status of upper rehabilitation robots is presented. Then, we outline and analyze the designs and applications of MLAs for upper limb movement intention recognition, human-robot interaction control and quantitative assessment of motor function. Meanwhile, we discuss the future directions of MLAs-based robotic rehabilitation. This review article provides a summary of MLAs for robotic upper limb rehabilitation and contributes to the design and development of future advanced intelligent medical devices

Development of a Procedure to Optimize the Geometric and Dynamic Designs of Assistive Upper Limb Exoskeletons

RÉSUMÉ La faiblesse musculaire chez les patients atteints de maladies neuromusculaires peut réduire leur capacité à réaliser des activités quotidiennes primordiales telles que manger ou se laver. Les dispositifs d'assistance disponibles offrent des fonctionnalités limitées et ne permettent pas de restaurer l'autonomie des patients. D'autre part, la fatigue musculaire chez les travailleurs œuvrant dans un environnement éprouvant peut provoquer des blessures et une mauvaise qualité de vie. Bien qu'il existe de nombreux outils pour les aider, l'effort requis peut tout de même être hautement exigeant. Les exosquelettes d’assistance sont bien adaptés pour aider ces deux populations, car ils visent à supporter l'utilisateur en diminuant l'effort nécessaire pour accomplir ses tâches quotidiennes. Le développement de tels dispositifs est une tâche fastidieuse, car les interactions en 3D entre le corps humain et l'exosquelette ainsi que le choix des caractéristiques du système de transmission de puissance, c'est-à-dire les moteurs ou les éléments passifs, sont très complexes et interdépendants. Pour ajouter à cette difficulté, il existe très peu de lignes directrices ou de procédures claires pour soutenir la synthèse géométrique et dynamique d'exosquelettes d’assistance et portable des membres supérieurs. Les paramètres géométriques sont les dimensions de l'exosquelette tandis que les paramètres dynamiques sont les caractéristiques des moteurs et des éléments passifs, tels que des ressorts. L'objectif de ce mémoire de maîtrise est de développer une procédure de synthèse géométrique et dynamique pour soutenir la conception d'un exosquelette de membre supérieur. Tout d'abord, une optimisation géométrique des dimensions de l'exosquelette a permis de maximiser la fermeture de la boucle cinématique et d'éviter les collisions avec les segments du corps tout en réalisant des tâches fonctionnelles spécifiques. Ensuite, grâce à un problème de contrôle optimal, les caractéristiques dynamiques de l'exosquelette ont été obtenues en minimisant les couples articulaires de l'utilisateur pour les mêmes tâches fonctionnelles. Les dimensions optimisées de l'exosquelette ont permis de réussir la fermeture de boucles pour toutes les tâches, soit 10,8 % de plus qu'avec une identification visuelle des dimensions. Quant à eux, les paramètres dynamiques ont pu réduire le couple articulaire de l'utilisateur à moins de 10,6 % des simulations sans exosquelettes pour presque toutes les articulations et les tâches. En conclusion, ces résultats ont montré que la procédure de synthèse était réussie. Cela pourra permettre le développement d'exosquelettes plus légers et plus petits ayant le potentiel d'être commercialisés à court terme. Les perspectives de cette recherche sont de développer une procédure d'optimisation où les paramètres géométriques et dynamiques sont optimisés simultanément et de minimiser les forces musculaires plutôt que les couples articulaires de l'utilisateur pour soutenir des objectifs de design et des objectifs cliniques.----------ABSTRACT Muscular weakness for patients affected by neuromuscular diseases can reduce their ability to realize primordial daily activities such as eating or washing themselves. The available assistance devices offer limited functionalities and do not restore autonomy for the patients. On the other hand, muscular fatigue for workers in tough physical environments can cause injuries and poor quality of life. While there are a lot of tools to help them, the required effort can still be very demanding. Assistive exoskeletons are well suited to help both these populations as they aim to assist the user by lowering the effort necessary to accomplish his everyday tasks. The development of such devices is a tedious task as the 3D human-exoskeleton interactions and the selection of the power transmission system characteristics, i.e. motors or passive elements, are highly complex and interdependent. To add to this complexity, there are very little to no guidelines or clear procedures for supporting the geometric and dynamic synthesis of wearable and assistive upper limb exoskeletons. The geometric parameters are the dimensions of the exoskeleton while the dynamic parameters are the characteristics of motors and passive elements such as springs. The objective of this master thesis was to develop a geometric and dynamic synthesis procedure to support the design of an upper limb exoskeleton. First, a geometric optimization of the exoskeleton dimensions enabled to maximize the kinematic loops closure and to avoid collisions with the body segments while carrying out specific functional tasks. Then, through an optimal control problem, the exoskeleton dynamic characteristics were obtained by minimizing the user joint torques for the same functional tasks. The optimized exoskeleton dimensions could reach loop closure for all tasks, 10.8% more than with a visual identification of the dimensions. The resulting dynamic parameters could reduce the user’s joint torque to less than 10.6% of the human-only simulations for nearly all joints and tasks. To conclude, these results showed that the synthesis procedure was successful. This is important as it can enable the development of lighter and smaller exoskeletons that have the potential to reach commercialization. The future perspectives are to build an optimization framework where the geometric and dynamic parameters are optimized together and to minimize the muscle force instead of the user’s joint torques to support clinical and design purposes

Comparative study of actuation systems for portable upper limb exoskeletons.

During the last two decades, a large variety of upper limb exoskeletons have been developed. Out of these, majority are platform based systems which might be the reason for not being widely adopted for post-stroke rehabilitation. Despite the potential benefits of platform-based exoskeletons as being rugged and reliable, stroke patients prefer to have a portable and user-friendly device that they can take home. However, the types of actuator as well as the actuation mechanism used in the exoskeleton are the inhibiting factors why portable exoskeletons are mostly non-existent for patient use. This paper presents a quantitative analysis of the actuation systems available for developing portable upper arm exoskeletons with their specifications. Finally, it has been concluded from this research that there are not many stand-alone arm exoskeletons which can provide all forms of rehabilitation, therefore, a generic solution has been proposed as the rehabilitation strategy to get best out of the portable arm exoskeletons