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The restoration of gait is a key goal after stroke, traumatic brain injury and spinal cord injury. Conventional training methods, e.g. treadmill training, require great physical effort from the therapists to assist the patient After the successful development and application of a mechanised gait trainer, a new research project of constructing a sensorised robot gait trainer is under way. The aim of this project is to build a robotic device which enables the therapist to let the machine move the patients feet, fixed on two footplates, on programmable foot trajectories (e.g. walking on the ground, stepping stairs up and down, disturbances during walking). Furthermore impedance control algorithms will be incorporated for online adaptation of the foot trajectories to the patients walking capabilities. Another important feature is the compliance control to simulate virtual ground conditions, i.e. the machine acts as a haptic foot device. Due to the partially high dynamic foot movements during normal walking, conventional industrial robots are not suitable for this task. This paper describes development aspects and problems that have to be dealt with during the design process of the robotised gait training machine.
This revised, updated, and substantially expanded third edition provides an accessible, practical overview of major areas of research, technical development and clinical application in the field of neurorehabilitation movement therapy. The initial section provides the basic framework and a rationale for technology application in movement therapy by summarizing recent findings in neuroplasticity and motor learning. The following section provides a detailed overview of the movement physiology of various neurologic conditions, illustrating how this knowledge has been used to design various neurorehabilitation technologies. The third section then explains the principles of human-machine interaction for movement rehabilitation. The fourth section provides an overview of assessment technology and predictive modeling in neurorehabilitation. The fifth section provides a survey of technological approaches to neurorehabilitation, including spinal cord stimulation, functional electrical stimulation, virtual reality, wearable sensing, brain computer interfaces, mobile technologies, and telerehabilitation. The final two sections examine in greater detail the ongoing revolution in robotic therapy for upper extremity movement and walking, respectively. The promises and limitations of these technologies in neurorehabilitation are discussed, including an Epilogue which debates the impact and utility of robotics for neurorehabilitation. Throughout the book the chapters provide detailed practical information on state-of-the-art clinical applications of these devices following stroke, spinal cord injury, and other neurologic disorders and future developments in the field. The text is illustrated throughout with photographs and schematic diagrams which serve to clarify the information for the reader. Neurorehabilitation Technology, Third Edition is a valuable resource for neurologists, biomedical engineers, roboticists, rehabilitation specialists, physiotherapists, occupational therapists and those training in these fields. Chapter “Spinal Cord Stimulation to Enable Leg Motor Control and Walking in People with Spinal Cord Injury is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Repetitive and task-oriented movements can strengthen muscles and improve walking capabilities among patients experiencing gait impairments due to neurological disorders. The demand for effective rehabilitation is high, given the large number of patients suffering from gait impairments. The traditional physiotherapy is laborious, may not provide the desired cadence and gait patterns, and requires constant presence of physiotherapists. This often leads to delayed treatment for many patients due to the high demand and a shortage of physiotherapists. Early phase post-stroke gait rehabilitation is crucial, as the ability to recuperate lost muscular abilities reduces over time. Lower limb wearable rehabilitation robots have shown promise in improving the locomotor capabilities of patients experiencing gait impairments and reducing the burden on physiotherapists. However, the high cost of commercially available robots makes this technology inaccessible to many hospitals and rehabilitation centers. To address this issue, ongoing research is focusing on improving existing rehabilitation robots in terms of ease of use, innovative design, and cost reduction. Closed-loop linkage mechanisms have recently drawn attention in the development of gait rehabilitation robots due to their ability to address the drawbacks of commercially available robot orthoses. These mechanisms are affordable and capable of providing suitable trajectories for gait training therapy. One of the challenging aspects in designing linkage-based robots is determining and calculating linkage parameters that will produce the required gait trajectories. This thesis presents an innovative approach to synthesizing the linkage dimensions to provide natural gait trajectories. Additionally, it introduces a novel and affordable robotic orthosis based on Stephenson III's six-bar linkage. The developed gait rehabilitation orthosis is a bilateral system powered by a single actuator on each side of the leg, capable of providing naturalistic knee and ankle joint motions relative to the hip joint, which are required during therapeutic gait training. This orthosis can be used in clinical settings and is actuated using only a single motor, yet it is capable of providing complex lower limb trajectory motions at its end-effector. The initial design optimization was carried out using a genetic algorithm (GA), and a deep generative neural network model was developed for the linkage synthesis problem. This model represents an advancement in current kinematic synthesis methods, enabling it to generate dimensions of the links that satisfy various required target human lower limb trajectories during walking in a short period. It will assist designers in determining optimal linkage dimensions to generate the required end-effector trajectories within a single mechanism. To enhance the mechanism's velocity regulation control scheme and address fluctuations that may occur during operation due to external disturbances such as fixed patient's leg and inertia in closed loop linkage mechanisms, a Deep Reinforcement Learning control scheme was proposed to regulate the speed of the input crank to reach satisfactory performance needed for gait rehabilitation training. Experimental evaluations with healthy human subjects were conducted to demonstrate that the mechanism is capable of directing lower limbs on naturalistic gait trajectories with a required walking speed. Furthermore, given the varied disability levels among neurologically impaired patients, the orthosis incorporates a patient cooperative control strategy. This is achieved through the application of impedance learning control, operating on an "assist-as-needed" principle. This innovative approach enables the robot to modify the assistive force it provides during gait cycle aligning with the patient's disability level and contributing towards active participation during the gait rehabilitation training. The proposed control scheme was evaluated in two distinct gait training modes while being worn by a human subject. In the "passive" mode subjects refrained from moving their legs, allowing the robot to guide their movements. While during the second 'active' mode, the subject engaged in normal walking activity while wearing the robot. Experimental results with healthy human subjects indicated reduced robot torques consequent to an increase in human torque. These results substantiate that customized robotic assistance based on the individual needs of patients can enhance their participation, which is essential to improve the treatment outcomes. The concept of this research lies in the development of a novel, affordable, and adaptable robotic orthosis based on Stephenson III's six-bar linkage mechanism, capable of delivering naturalistic individualized lower limb motion. It advances the fields of dimensional synthesis of closed loop linkage mechanisms rehabilitation robotics with the use of deep generative neural network and a Deep Reinforcement Learning control scheme for enhanced velocity regulation. Moreover, the application of impedance learning control encourages active patient participation in gait rehabilitation training by customizing assistive force based on the patient's disability level. With these advancements, the research contributes significantly to the development of more cost-effective, adaptable, and efficient robotic gait rehabilitation systems, presenting a promising solution for improving therapeutic outcomes for patients with gait impairments due to neurological disorders.
This chapter focuses on rehabilitation robotics which can be used to augment the clinician's toolbox in order to deliver meaningful restorative therapy for an aging population, as well as on advances in orthotics to augment an individual's functional abilities beyond neurorestoration potential. The interest in rehabilitation robotics and orthotics is increasing steadily with marked growth in the last 10 years. This growth is understandable in view of the increased demand for caregivers and rehabilitation services escalating apace with the graying of the population. We provide an overview on improving function in people with a weak limb due to a neurological disorder who cannot properly control it to interact with the environment (orthotics); we then focus on tools to assist the clinician in promoting rehabilitation of an individual so that s/he can interact with the environment unassisted (rehabilitation robotics). We present a few clinical results occurring immediately poststroke as well as during the chronic phase that demonstrate superior gains for the upper extremity when employing rehabilitation robotics instead of usual care. These include the landmark VA-ROBOTICS multisite, randomized clinical study which demonstrates clinical gains for chronic stroke that go beyond usual care at no additional cost.
This book reports on the latest technological and clinical advances in the field of neurorehabilitation. It is, however, much more than a conventional survey of the state-of-the-art in neurorehabilitation technologies and therapies. It was formed on the basis of a week of lively discussions between curious PhD students and leading research experts during the summer school on neurorehabilitation (SSNR2012), September 16-21 in Nuévalos, Zaragoza (Spain). Its unconventional format makes it a perfect guide for all PhD students, researchers and professionals interested in gaining a multidisciplinary perspective on current and future neurorehabilitation scenarios. The book covers various aspects of neurorehabilitation research and practice, organized into different parts. The first part discusses a selection of common impairments affecting brain function, such as stroke, cerebral palsy and Parkinson’s disease; the second deals with both spinal cord and brain plasticity. The third part covers the most recent rehabilitation and diagnostics technologies, including robotics, neuroprostheses, brain-machine interfaces and electromyography systems. Practical examples and case studies related to the application of some of the latest techniques in realistic clinical scenarios are covered in the fourth part.
Rehabilitation Robotics gives an introduction and overview of all areas of rehabilitation robotics, perfect for anyone new to the field. It also summarizes available robot technologies and their application to different pathologies for skilled researchers and clinicians. The editors have been involved in the development and application of robotic devices for neurorehabilitation for more than 15 years. This experience using several commercial devices for robotic rehabilitation has enabled them to develop the know-how and expertise necessary to guide those seeking comprehensive understanding of this topic. Each chapter is written by an expert in the respective field, pulling in perspectives from both engineers and clinicians to present a multi-disciplinary view. The book targets the implementation of efficient robot strategies to facilitate the re-acquisition of motor skills. This technology incorporates the outcomes of behavioral studies on motor learning and its neural correlates into the design, implementation and validation of robot agents that behave as ‘optimal’ trainers, efficiently exploiting the structure and plasticity of the human sensorimotor systems. In this context, human-robot interaction plays a paramount role, at both the physical and cognitive level, toward achieving a symbiotic interaction where the human body and the robot can benefit from each other’s dynamics. Provides a comprehensive review of recent developments in the area of rehabilitation robotics Includes information on both therapeutic and assistive robots Focuses on the state-of-the-art and representative advancements in the design, control, analysis, implementation and validation of rehabilitation robotic systems