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The first finding, that providing an intermediate amount of freedom to the pelvis can interfere with gait training, suggests that future devices should have very high amounts of freedom or very restricted pelvic motions. The final finding, that damping fields can be used to induce gait adaptations using a much lower force, can drastically change exoskeleton design and how robotic therapy is provided. Exoskeletons can be made lighter as a result of the force being highly reduced so that lighter weight components can be used, and the dissipative nature of the force reduces dependence on heavy power sources because regenerative breaking can be used to power the device. These factors also make it possible to for devices to be used overground, which may make training more transferable to the real world.
Neurologic injuries, such as stroke and spinal cord injuries (SCI), cause damage to neural systems and motor function, which results in lower limb impairment and gait disorders. Subjects with gait disorders require specific training to regain functional mobility. Traditionally, manual physical therapy is used for the gait training of neurologically impaired subjects which has limitations, such as the excessive workload and fatigue of physical therapists. The rehabilitation engineering community is working towards the development of robotic devices and control schemes that can assist during the gait training. The initial prototypes of these robotic gait training orthoses use conventional, industrial actuators that are either extremely heavy or have high endpoint impedance (stiffness). Neurologically impaired subjects often suffer from severe spasms. These stiff actuators may produce forces in response to the undesirable motions, often causing pain or discomfort to patients. The control schemes used by the initial prototypes of robotic gait training orthoses also have a limited ability to provide seamless, adaptive, and customized robotic assistance. This requires new design and control methods to be developed to increase the compliance and adaptability of these automated gait training devices. This research introduces the development of a new robotic gait training orthosis that is intrinsically compliant. Novel, assist-as-needed (AAN) control strategies are proposed to provide adaptive and customized robotic assistance to subjects with different levels of neurologic impairments. The new robotic gait training orthosis has six degrees of freedom (DOFs), which is powered by pneumatic muscle actuators (PMA). The device provides naturalistic gait pattern and safe interaction with subjects during gait training. New robust feedback control schemes are proposed to improve the trajectory tracking performance of PMAs. A dynamic model of the device and a human lower limb musculoskeletal model are established to study the dynamic interaction between the device and subjects. In order to provide adaptive, customized robot assisted gait training and to enhance the subject's voluntary participation in the gait training process, two new control schemes are proposed in this research. The first control scheme is based on the impedance control law. The impedance control law modifies the robotic assistance based on the human subject's active joint torque contributions. The levels of robot compliance can be selected by the physical therapist during the impedance control scheme according to the disability level and stage of rehabilitation of neurologically impaired subjects. The second control scheme is proposed to overcome the shortcomings of impedance control scheme and to provide seamless adaptive, AAN gait training. The adaptive, AAN gait training scheme is based on the estimation of the disability level of neurologically impaired subjects based on the kinematic error and adapts the robotic assistance accordingly. All the control schemes have been evaluated on neurologically intact subjects and the results show that these control schemes can deliver their intended effects. Rigorous clinical trials with neurologically impaired subjects are required to prove the therapeutic efficacy of the proposed robotic orthosis and the adaptive gait training schemes. The concept of intrinsically compliant robotic gait training orthosis, together with the trajectory tracking and impedance control of robotic gait training orthosis are the important contributions of this research. The algorithms and models developed in this research are applicable to the development of other robotic devices for rehabilitation and assistive purposes. The major contribution of the research lies in the development of a seamless, adaptive AAN gait training strategy. The research will help in evolving the field of compliant actuation of rehabilitation robots along with the development of new control schemes for providing seamless, adaptive AAN gait training.
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
Stroke is one of the leading causes of physical disability around the world, resulting in significant motor deficits and ultimately reduced gait performance. In order to regain or improve motor function, stroke patients will undergo rehabilitation. Current rehabilitation techniques are labour-intensive and time-consuming for both the therapist and the patient. Therefore, not all patients receive the recommended quantity and quality of rehabilitation. To improve the gait rehabilitation process, robot-assisted gait rehabilitation has been receiving increased interest over the past few years. The research in this thesis aims to demonstrate feasibility of robotic gait rehabilitation devices which are designed to be easy to use, simple and compact. The Linkage-based Gait Trainer (LGT) was the first device developed and is an overground gait rehabilitation device consisting of a four-bar linkage end-effector mechanism. The literature review suggested the design could be an effective gait rehabilitation device while minimising the components required. The design of the LGT was validated with a healthy human participant, and kinematic data showed that the device successfully constrained the user’s foot motion to a pre-defined gait trajectory. The imposed trajectory of the LGT is set by the linkage design and cannot be changed. To allow for modification to the trajectory a subsequent device (robotic Re-Link Trainer [rRLT]) was developed. The rRLT also uses a four-bar linkage, however the spatiotemporal parameters of gait, such as walking speed, stride length and cadence, can be varied to accommodate a wider range of users with different limb lengths and desired walking speeds. A trial with healthy participants was carried out to validate the rRLT’s design and its function. The results confirmed the device’s ability to vary the spatiotemporal parameter of the gait pattern the device imposes on the user. One of the limitations of both the LGT and rRLT is that the constrained gait path is not variable. To make the device available for more users with different gait trajectories, a new gait rehabilitation device with a five-bar linkage called PRO-GaiT was developed. A trial with healthy participants confirmed the ability to change and constrain different gait trajectories during walking exercises. The research in this thesis confirmed the ability of a linkage-based overground gait rehabilitation device to constrain a user’s footpath to a desired trajectory. Such devices can vary the footpath and spatiotemporal parameters of gait to accommodate many different users. The devices developed in this research could improve the effectiveness of the gait rehabilitation by potentially increasing the time and intensity of each session while reducing the number of staff required. A rehabilitation device based on this research could be compact, easy to use and low cost thus can be widely adopted by many hospitals and clinics.
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.
The 9-volume set LNAI 14267-14275 constitutes the proceedings of the 16th International Conference on Intelligent Robotics and Applications, ICIRA 2023, which took place in Hangzhou, China, during July 5–7, 2023. The 413 papers included in these proceedings were carefully reviewed and selected from 630 submissions. They were organized in topical sections as follows: Part I: Human-Centric Technologies for Seamless Human-Robot Collaboration; Multimodal Collaborative Perception and Fusion; Intelligent Robot Perception in Unknown Environments; Vision-Based Human Robot Interaction and Application. Part II: Vision-Based Human Robot Interaction and Application; Reliable AI on Machine Human Reactions; Wearable Sensors and Robots; Wearable Robots for Assistance, Augmentation and Rehabilitation of Human Movements; Perception and Manipulation of Dexterous Hand for Humanoid Robot. Part III: Perception and Manipulation of Dexterous Hand for Humanoid Robot; Medical Imaging for Biomedical Robotics; Advanced Underwater Robot Technologies; Innovative Design and Performance Evaluation of Robot Mechanisms; Evaluation of Wearable Robots for Assistance and Rehabilitation; 3D Printing Soft Robots. Part IV: 3D Printing Soft Robots; Dielectric Elastomer Actuators for Soft Robotics; Human-like Locomotion and Manipulation; Pattern Recognition and Machine Learning for Smart Robots. Part V: Pattern Recognition and Machine Learning for Smart Robots; Robotic Tactile Sensation, Perception, and Applications; Advanced Sensing and Control Technology for Human-Robot Interaction; Knowledge-Based Robot Decision-Making and Manipulation; Design and Control of Legged Robots. Part VI: Design and Control of Legged Robots; Robots in Tunnelling and Underground Space; Robotic Machining of Complex Components; Clinically Oriented Design in Robotic Surgery and Rehabilitation; Visual and Visual-Tactile Perception for Robotics. Part VII: Visual and Visual-Tactile Perception for Robotics; Perception, Interaction, and Control of Wearable Robots; Marine Robotics and Applications; Multi-Robot Systems for Real World Applications; Physical and Neurological Human-Robot Interaction. Part VIII: Physical and Neurological Human-Robot Interaction; Advanced Motion Control Technologies for Mobile Robots; Intelligent Inspection Robotics; Robotics in Sustainable Manufacturing for Carbon Neutrality; Innovative Design and Performance Evaluation of Robot Mechanisms. Part IX: Innovative Design and Performance Evaluation of Robot Mechanisms; Cutting-Edge Research in Robotics.
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.
Rehabilitation Robotics summarizes the rationale for robot-assisted therapy and presents the technological steps in the evolution of the design and development of lower and upper extremity rehabilitation robots. After presenting the basic mechanisms of natural and artificial movement restoration, and the rationale for robot-aided movement therapy, it shows several design criteria that are relevant for the development of effective and safe rehabilitation robots.