Kinematical and dynamical modeling of a multipurpose upper limbs rehabilitation robot

Knowing accurate model of a system is always beneficial to design a robust and safe control while allowing reduction of sensors-related cost as the system outputs are predictable using the model. In this context, this paper addresses the kinematical and dynamical model identification of the multipurpose rehabilitation robot, Universal Haptic Pantograph (UHP), and present experimental validations of the identified models. The UHP is a Pantograph based innovative robot actuated by two SEAs (Series Elastic Actuator), aiming at training impaired upper limbs after a stroke. This novel robot, thanks to its lockable/unlockable joints, can change its mechanical structure so that it enables stroke patient to perform different training exercises of the shoulder, elbow and wrist. This work focuses on the ARM mode, which is a training mode used to rehabilitate elbow and shoulder. The kinematical model of UHP is identified based on the loop vector equations, while the dynamical model is derived based on the Lagrangian formulation. To demonstrate the accuracy of the models, several experimental tests were performed. The results reveal that the mean position error between estimated values with the model and actual measured values stays in 3 mm (less than 2% of the maximum motion range). Moreover, the error between estimated and measured interaction force is smaller than 10% of maximum force range. So, the developed models can be adopted to estimate motion and force of UHP as well as control it without the need of additional sensors such as a force sensor, resulting in the reduction of total robot cost.This work was supported in part by the Basque Country Governments (GV/EJ) under grant PRE-2014-1-152, UPV/EHU’s PPG17/56 project, Basque Country Governments IT914-16 project, Spanish Ministry of Economy and Competitiveness’ MINECO & FEDER inside DPI- 2012-32882 projects, Spanish Ministry of Economy and Competitiveness BES-2013-066142 grant, Euskampus, FIK

Kinematical and dynamical modelling of a multipurpose upper limbs rehabilitation robot

Knowing accurate model of a system is always beneficial to design a robust and safe control while allowing reduction of sensors-related cost as the system outputs are predictable using the model. In this context, this paper addresses the kinematical and dynamical model identification of the multipurpose rehabilitation robot, Universal Haptic Pantograph (UHP), and present experimental validations of the identified models. The UHP is a Pantograph based innovative robot actuated by two SEAs (Series Elastic Actuator), aiming at training impaired upper limbs after a stroke. This novel robot, thanks to its lockable/unlockable joints, can change its mechanical structure so that it enables stroke patient to perform different training exercises of the shoulder, elbow and wrist. This work focuses on the ARM mode, which is a training mode used to rehabilitate elbow and shoulder. The kinematical model of UHP is identified based on the loop vector equations, while the dynamical model is derived based on the Lagrangian formulation. To demonstrate the accuracy of the models, several experimental tests were performed. The results reveal that the mean position error between estimated values with the model and actual measured values stays in 3 mm (less than 2% of the maximum motion range). Moreover, the error between estimated and measured interaction force is smaller than 10% of maximum force range. So, the developed models can be adopted to estimate motion and force of UHP as well as control it without the need of additional sensors such as a force sensor, resulting in the reduction of total robot cost.This work was supported in part by the Basque Country Governments (GV/EJ) under grant PRE-2014-1-152, UPV/EHU’s PPG17/56 project, Basque Country Governments IT914-16 project, Spanish Ministry of Economy and Competitiveness’ MINECO & FEDER inside DPI2012-32882 projects, Spanish Ministry of Economy and Competitiveness BES-2013-066142 grant, Euskampus, FIK

Robotic Platforms for Assistance to People with Disabilities

People with congenital and/or acquired disabilities constitute a great number of dependents today. Robotic platforms to help people with disabilities are being developed with the aim of providing both rehabilitation treatment and assistance to improve their quality of life. A high demand for robotic platforms that provide assistance during rehabilitation is expected because of the health status of the world due to the COVID-19 pandemic. The pandemic has resulted in countries facing major challenges to ensure the health and autonomy of their disabled population. Robotic platforms are necessary to ensure assistance and rehabilitation for disabled people in the current global situation. The capacity of robotic platforms in this area must be continuously improved to benefit the healthcare sector in terms of chronic disease prevention, assistance, and autonomy. For this reason, research about human–robot interaction in these robotic assistance environments must grow and advance because this topic demands sensitive and intelligent robotic platforms that are equipped with complex sensory systems, high handling functionalities, safe control strategies, and intelligent computer vision algorithms. This Special Issue has published eight papers covering recent advances in the field of robotic platforms to assist disabled people in daily or clinical environments. The papers address innovative solutions in this field, including affordable assistive robotics devices, new techniques in computer vision for intelligent and safe human–robot interaction, and advances in mobile manipulators for assistive tasks

Robot de rehabilitación configurable para terapias del miembro superior

La rehabilitación basada en dispositivos robóticos precisa de un robot capaz de adaptarse al estado de recuperación motora del paciente. En este trabajo se presenta un robot de rehabilitación reconfigurable denominado Universal Haptic Pantograph (UHP). Este dispositivo robótico, gracias a su estructura multiconfigurable, permite la rehabilitación del miembro superior (hombro, codo y muñeca) con un único dispositivo. Además, ha sido diseñado para trabajar con diferentes modalidades de interacción como son las asistidas, correctoras y opositoras, pudiendo así adaptarse al estado funcional progresivo del paciente durante el proceso de rehabilitación. Con el objetivo de garantizar el correcto funcionamiento de este sistema robótico se han realizado diferentes ensayos experimentales. Los resultados demuestran que el robot de rehabilitación UHP funciona correctamente con diferentes tareas de rehabilitación, realizando movimientos suaves que garantizan la seguridad del usuario en todo momento.Este trabajo ha sido parcialmente financiado por el Ministerio de Economía y Competitividad MINECO & FEDER en el marco del proyecto DPI-2012-32882, así como por la beca PRE-2014-1-152 y el proyecto IT914-16 del Gobierno Vasco, el proyecto PPG17/56 de la UPV/EHU y por Euskampus Fundazioa. Además, los autores desean expresar su agradecimiento al centro de investigación Tecnalia por su colaboración y por prestar su robot de rehabilitación UHP

On Neuromechanical Approaches for the Study of Biological Grasp and Manipulation

Biological and robotic grasp and manipulation are undeniably similar at the level of mechanical task performance. However, their underlying fundamental biological vs. engineering mechanisms are, by definition, dramatically different and can even be antithetical. Even our approach to each is diametrically opposite: inductive science for the study of biological systems vs. engineering synthesis for the design and construction of robotic systems. The past 20 years have seen several conceptual advances in both fields and the quest to unify them. Chief among them is the reluctant recognition that their underlying fundamental mechanisms may actually share limited common ground, while exhibiting many fundamental differences. This recognition is particularly liberating because it allows us to resolve and move beyond multiple paradoxes and contradictions that arose from the initial reasonable assumption of a large common ground. Here, we begin by introducing the perspective of neuromechanics, which emphasizes that real-world behavior emerges from the intimate interactions among the physical structure of the system, the mechanical requirements of a task, the feasible neural control actions to produce it, and the ability of the neuromuscular system to adapt through interactions with the environment. This allows us to articulate a succinct overview of a few salient conceptual paradoxes and contradictions regarding under-determined vs. over-determined mechanics, under- vs. over-actuated control, prescribed vs. emergent function, learning vs. implementation vs. adaptation, prescriptive vs. descriptive synergies, and optimal vs. habitual performance. We conclude by presenting open questions and suggesting directions for future research. We hope this frank assessment of the state-of-the-art will encourage and guide these communities to continue to interact and make progress in these important areas

On neuromechanical approaches for the study of biological and robotic grasp and manipulation

abstract: Biological and robotic grasp and manipulation are undeniably similar at the level of mechanical task performance. However, their underlying fundamental biological vs. engineering mechanisms are, by definition, dramatically different and can even be antithetical. Even our approach to each is diametrically opposite: inductive science for the study of biological systems vs. engineering synthesis for the design and construction of robotic systems. The past 20 years have seen several conceptual advances in both fields and the quest to unify them. Chief among them is the reluctant recognition that their underlying fundamental mechanisms may actually share limited common ground, while exhibiting many fundamental differences. This recognition is particularly liberating because it allows us to resolve and move beyond multiple paradoxes and contradictions that arose from the initial reasonable assumption of a large common ground. Here, we begin by introducing the perspective of neuromechanics, which emphasizes that real-world behavior emerges from the intimate interactions among the physical structure of the system, the mechanical requirements of a task, the feasible neural control actions to produce it, and the ability of the neuromuscular system to adapt through interactions with the environment. This allows us to articulate a succinct overview of a few salient conceptual paradoxes and contradictions regarding under-determined vs. over-determined mechanics, under- vs. over-actuated control, prescribed vs. emergent function, learning vs. implementation vs. adaptation, prescriptive vs. descriptive synergies, and optimal vs. habitual performance. We conclude by presenting open questions and suggesting directions for future research. We hope this frank and open-minded assessment of the state-of-the-art will encourage and guide these communities to continue to interact and make progress in these important areas at the interface of neuromechanics, neuroscience, rehabilitation and robotics.The electronic version of this article is the complete one and can be found online at: https://jneuroengrehab.biomedcentral.com/articles/10.1186/s12984-017-0305-

Robot de rehabilitación configurable para terapias del miembro superior

La rehabilitación basada en dispositivos robóticos precisa de un robot capaz de adaptarse al estado de recuperación motora del paciente. En este trabajo se presenta un robot de rehabilitación reconfigurable denominado Universal Haptic Pantograph (UHP). Este dispositivo robótico, gracias a su estructura multiconfigurable, permite la rehabilitación del miembro superior (hombro, codo y muñeca) con un único dispositivo. Además, ha sido diseñado para trabajar con diferentes modalidades de interacción como son las asistidas, correctoras y opositoras, pudiendo así adaptarse al estado funcional progresivo del paciente durante el proceso de rehabilitación. Con el objetivo de garantizar el correcto funcionamiento de este sistema robótico se han realizado diferentes ensayos experimentales. Los resultados demuestran que el robot de rehabilitación UHP funciona correctamente con diferentes tareas de rehabilitación, realizando movimientos suaves que garantizan la seguridad del usuario en todo momento.Este trabajo ha sido parcialmente financiado por el Ministerio de Economía y Competitividad MINECO & FEDER en el marco del proyecto DPI-2012-32882, así como por la beca PRE-2014-1-152 y el proyecto IT914-16 del Gobierno Vasco, el proyecto PPG17/56 de la UPV/EHU y por Euskampus Fundazioa. Además, los autores desean expresar su agradecimiento al centro de investigación Tecnalia por su colaboración y por prestar su robot de rehabilitación UHP

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

Technology-supported training of arm-hand skills in stroke

Impaired arm-hand performance is a serious consequence of stroke that is associated with reduced self-efficacy and poor quality of life. Task-oriented arm training is a therapy approach that is known to improve skilled arm-hand performance, even in chronic stages after stroke. At the start of this project, little knowledge had been consolidated regarding taskoriented arm training characteristics, especially in the field of technology-supported rehabilitation. The feasibility and effects of technology-supported client-centred task-oriented training on skilled arm-hand performance had not been investigated but to a very limited degree. Reviewing literature on rehabilitation and motor learning in stroke led to the identification of therapy oriented criteria for rehabilitation technology aiming to influence skilled arm-hand performance (chapter 2). Most rehabilitation systems reported in literature to date are robotic systems that are aimed at providing an engaging exercise environment and feedback on motor performance. Both, feedback and engaging exercises are important for motivating patients to perform a high number of exercise repetitions and prolonged training, which are important factors for motor learning. The review also found that current rehabilitation technology is focussed mainly on providing treatment at a function level, thereby improving joint range of motion, muscle strength and parameters such as movement speed and smoothness of movement during analytical movements. However, related research has found no effects of robot-supported training at the activity level. The review concluded that a challenge exists for upper extremity rehabilitation technology in stroke patients to also provide more patienttailored task-oriented arm-hand training in natural environments to support the learning of skilled arm-hand performance. Besides mapping the strengths of different technological solutions, the use of outcome measures and training protocols needs to become more standardized across similar interventions, in order to help determine which training solutions are most suitable for specific patient categories. Chapter 4 contributes towards such a standardization of outcome measurement. A concept is introduced which may guide the clinician/researcher to choose outcome measures for evaluating specific and generalized training effects. As an initial operationalization of this concept, 28 test batteries that have been used in 16 task-oriented training interventions were rated as to whether measurement components were measured by the test. Future research is suggested that elaborates the concept with information on the relative weighing of components in each test, with more test batteries (which may lead to additional components) and by adding more test properties into the concept (e.g. psychometric properties of the tests, possible floor- or ceiling effects). Task-oriented training is one of the training approaches that has been shown to be beneficial for skilled arm-hand performance after stroke. Important mechanisms for motor learning that are identified are patient motivation for such training, and the learning of efficient goaloriented movement strategies and task-specific problem solving. In this thesis we operationalize task-oriented training in terms of 15 components (chapter 3). A systematic review that included 16 randomized controlled trials using task-oriented training in stroke patients, evaluated the effects of these training components on skilled arm-hand performance. The number of training components used in an intervention aimed at improving arm-hand performance after stroke was not associated with the post-treatment effect size. Distributed practice and feedback were associated with the largest post-intervention effect sizes. Random practice and use of clear functional training goals were associated with the largest follow-up effect sizes. It may be that training components that optimize the storage of learned motor performance in the long-term memory are associated with larger treatment effects. Unfortunately, feedback, random practice and distributed practice were reported in very few of the included randomized controlled trials (in only 6,3 and 1 out of the 17 studies respectively). Client-centred training, i.e. training on exercises that support goals that are selected by the patients themselves, improves patient motivation for training. Motivation in turn has proven to positively influence motor learning in stroke patients, as attention during training is heightened and storage of information in the long-term memory improves. Chapter 5 reports on an interview of 40 stroke patients, investigating into training preferences. A list of 46 skills, ranked according to descending training preference scores, was provided that can be used for implementation of exercises in rehabilitation technology, in order for technologysupported training to be client-centred. Chapter 6 introduces T-TOAT, a technology supported task-oriented arm training method that was developed together with colleagues at Adelante (Hoensbroek, NL). T-TOAT enables the implementation of exercises that support task-oriented training in rehabilitation technology. The training method is applicable for different technological systems, e.g. robot and sensor systems, or in combination with functional electrical stimulation, etc. To enable the use of TTOAT for training with the Haptic Master Robot (MOOG-FCS, NL), special software named Haptic TOAT was developed in Adelante together with colleagues at the Centre of Technology in Care of Zuyd University (chapter 6). The software enables the recording of the patient’s movement trajectories, given task constraints and patient possibilities, using the Haptic Master as a recording device. A purpose-made gimbal was attached to the endeffector, leaving the hand free for the use and manipulating objects. The recorded movement can be replayed in a passive mode or in an active mode (active, active-assisted or activeresisted). Haptic feedback is provided when the patient deviates from the recorded movement trajectory, as the patient receives the sensation of bouncing into a wall, as well as feeling a spring that pulls him/her back to the recorded path. The diameter of the tunnel around the recorded trajectory (distance to the wall), and the spring force can be adjusted for each patient. An ongoing clinical trial in which chronic stroke patients train with Haptic-TOAT examines whether Haptic Master provides additional value compared to supporting the same exercises by video-instruction only. Together with Philips Research Europe (Eindhoven,Aachen), the T-TOAT method has been implemented in a sensor based prototype, called Philips Stroke Rehabilitation Exerciser. This system included movement tracking sensors and an exercise board interacting with real life objects. A very strong feature of the system is that feedback is provided to patients (real-time and after exercise performance), based on a comparison of the patient’s exercise performance to individual targets set by the therapist. Chapter 7 reports on a clinical trial investigating arm-hand treatment outcome and patient motivation for technology-supported task-oriented training in chronic stroke patients. It was found that 8 weeks of T-TOAT training improved arm-hand performance in chronic stroke patients significantly on Fugl-Meyer, Action Research Arm Test, and Motor Activity Log. An improvement was found in health-related quality of life. Training effects lasted at least 6 months post-training. Participants reported feeling intrinsically motivated and competent to use the system. The results of this study showed that T-TOAT is feasible. Despite the small number of stroke patients tested (n=9), significant and clinically relevant improvements in skilled arm-hand performance were found. In conclusion, this thesis has made several contributions. It motivated the need for clientcentred task-oriented training, which it has operationalized in terms of 15 components. Four of these 15 components were identified as most beneficial for the patient. A prioritized inventory of arm-hand training preferences of stroke patients was compiled by means of an interview study of 40 subacute and chronic stroke patients. T-TOAT, a method for technology-supported, client-centred, task-oriented training, was conceived and implemented in two target technologies (Haptic Master and Philips Stroke Rehabilitation Exerciser). Its feasibility was demonstrated in a clinical trial showing substantial and durable benefits for the stroke patients. Finally, the thesis contributes towards the standardization of outcome measures which is necessary for charting progress and guiding future developments of technology-supported stroke rehabilitation. Methodological considerations were discussed and several suggestions for future research were presented. The variety of treatment approaches and the various ways of support and challenge that are offered by existing rehabilitation technologies hold a large potential for offering a variety of extra training opportunities to stroke patients that may improve their arm-hand performance. Such solutions will be of increasing importance, to alleviate therapists and reduce economic pressure on the health care system, as the stroke incidence is increasing rapidly over the coming decades

Computational Intelligence in Electromyography Analysis

Electromyography (EMG) is a technique for evaluating and recording the electrical activity produced by skeletal muscles. EMG may be used clinically for the diagnosis of neuromuscular problems and for assessing biomechanical and motor control deficits and other functional disorders. Furthermore, it can be used as a control signal for interfacing with orthotic and/or prosthetic devices or other rehabilitation assists. This book presents an updated overview of signal processing applications and recent developments in EMG from a number of diverse aspects and various applications in clinical and experimental research. It will provide readers with a detailed introduction to EMG signal processing techniques and applications, while presenting several new results and explanation of existing algorithms. This book is organized into 18 chapters, covering the current theoretical and practical approaches of EMG research