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Author: Sai Kumar Banala
Publisher: ProQuest
ISBN: 9780549387237
Category : Gait disorders
Languages : en
Pages :
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Book Description
Robotic rehabilitation for physical therapy has several advantages over conventional manual rehabilitation, especially in the aspects of accuracy and repeatability. Initial attempts at robotic rehabilitation focused on training muscles by moving limbs in a fixed repetitive pattern. Later it was realized that such an approach could be suboptimal. Better approach would be the use of 'assist-as-needed' paradigm, where an orthotic device provides just enough assistance to enable the patient to move his leg under his own control. However, at this time, lower extremity devices which can apply appropriate forces to implement this paradigm are still in research and not commercially available. The goal of this work is to develop lower extremity orthotic devices using assist-as-needed paradigm for robotic rehabilitation. To achieve this goal two orthotic devices were developed. They are Gravity Balancing leg Orthosis (GBO) and Active Leg EXoskeleton (ALEX). GBO assists persons with hemiparesis to walk by reducing or eliminating the effects of gravity on the affected limb. The amount of assistance provided can be tuned by the therapist from 0% to 100% gravity balancing. For a quantitative evaluation of the performance of the device several experiments were conducted. These experiments were performed on five healthy subjects and three stroke patients. The results showed that with the GBO set to 100% balancing the EMG activity from the rectus femoris and hamstring muscles was reduced by 75%, during static hip and knee flexion, respectively. For leg-raising tasks the average torque for static positioning reduced by 66.8% at hip joint and 47.3% at knee joint, however if transient portion of the leg raising task is included, the average torque at hip reduced by 61.3% and at knee increased by 2.7% at knee joints. In the walking experiment there was a positive impact on the range of movement at the hip and knee joints, especially for stroke patients, the range of movement increased by more than 57% at hip joint and by more than 73% at the knee joint. These results show that the GBO provides assistance which can be used for rehabilitation. An intensive training of a stroke patient was performed to study the long term effects of GBO, the training lasting for six weeks. The training started out with maximum assistance of 100% gravity balancing and gradually reduced to 0% by the end of training. Patient is also shown visual display of his gait pattern in real time and summary performance after individual sessions. Some of the effects of the training were, increase in patients preferred speed of treadmill walking from 2.72 km/h to 3.04 km/h, patient's preferred overground speed increased from 3.38 km/h to 3.86 km/h by the last evaluation. An improvement of gait pattern was seen where the patients gait pattern became more like a healthy subject's pattern. The patient was able to increase weight bearing on the hemiparetic leg and was more symmetric in his walk. ALEX, on the other hand, is a motorized orthotic device. To achieve the goal of 'assist-as-needed' paradigm for ALEX, Force-Field controller was developed. This controller generates "virtual walls'' in the plane containing human thigh and shank segments. These virtual walls guide and assist the subject's foot along the prescribed trajectory. Linear actuators were used at hip and knee joints of the device. To make the actuators back-drivable, friction compensation was used. Gait training studies with healthy subjects were conducted to measure the effectiveness of ALEX in retraining modified gait pattern. The results show that a healthy human leg muscles can be trained in about 45 to 60 minutes to a modified pattern of foot trajectory. A 15-day long gait training was conducted with a stroke patient using ALEX, the results indicate that using ALEX and force-field controller, the patient's gait pattern improved significantly in many aspects. His gait speed improved both on treadmill from 1.45 km/h to 2.57 km/h and overground from 1.82 km/h to 2.50 km/h. His foot trajectory increased and got about 85% closer to a healthy subject's foot trajectory. Knee flexion increased from 27.2 deg to 47.5 deg and ankle dorsi-flexion increased from 1.9 deg to 5.9 deg by the end of the training. All these results indicate that by using these devices suitably and implementing a long term gait training can help patients with walking disability in a speedy recovery.
Author: Sai Kumar Banala
Publisher: ProQuest
ISBN: 9780549387237
Category : Gait disorders
Languages : en
Pages :
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Book Description
Robotic rehabilitation for physical therapy has several advantages over conventional manual rehabilitation, especially in the aspects of accuracy and repeatability. Initial attempts at robotic rehabilitation focused on training muscles by moving limbs in a fixed repetitive pattern. Later it was realized that such an approach could be suboptimal. Better approach would be the use of 'assist-as-needed' paradigm, where an orthotic device provides just enough assistance to enable the patient to move his leg under his own control. However, at this time, lower extremity devices which can apply appropriate forces to implement this paradigm are still in research and not commercially available. The goal of this work is to develop lower extremity orthotic devices using assist-as-needed paradigm for robotic rehabilitation. To achieve this goal two orthotic devices were developed. They are Gravity Balancing leg Orthosis (GBO) and Active Leg EXoskeleton (ALEX). GBO assists persons with hemiparesis to walk by reducing or eliminating the effects of gravity on the affected limb. The amount of assistance provided can be tuned by the therapist from 0% to 100% gravity balancing. For a quantitative evaluation of the performance of the device several experiments were conducted. These experiments were performed on five healthy subjects and three stroke patients. The results showed that with the GBO set to 100% balancing the EMG activity from the rectus femoris and hamstring muscles was reduced by 75%, during static hip and knee flexion, respectively. For leg-raising tasks the average torque for static positioning reduced by 66.8% at hip joint and 47.3% at knee joint, however if transient portion of the leg raising task is included, the average torque at hip reduced by 61.3% and at knee increased by 2.7% at knee joints. In the walking experiment there was a positive impact on the range of movement at the hip and knee joints, especially for stroke patients, the range of movement increased by more than 57% at hip joint and by more than 73% at the knee joint. These results show that the GBO provides assistance which can be used for rehabilitation. An intensive training of a stroke patient was performed to study the long term effects of GBO, the training lasting for six weeks. The training started out with maximum assistance of 100% gravity balancing and gradually reduced to 0% by the end of training. Patient is also shown visual display of his gait pattern in real time and summary performance after individual sessions. Some of the effects of the training were, increase in patients preferred speed of treadmill walking from 2.72 km/h to 3.04 km/h, patient's preferred overground speed increased from 3.38 km/h to 3.86 km/h by the last evaluation. An improvement of gait pattern was seen where the patients gait pattern became more like a healthy subject's pattern. The patient was able to increase weight bearing on the hemiparetic leg and was more symmetric in his walk. ALEX, on the other hand, is a motorized orthotic device. To achieve the goal of 'assist-as-needed' paradigm for ALEX, Force-Field controller was developed. This controller generates "virtual walls'' in the plane containing human thigh and shank segments. These virtual walls guide and assist the subject's foot along the prescribed trajectory. Linear actuators were used at hip and knee joints of the device. To make the actuators back-drivable, friction compensation was used. Gait training studies with healthy subjects were conducted to measure the effectiveness of ALEX in retraining modified gait pattern. The results show that a healthy human leg muscles can be trained in about 45 to 60 minutes to a modified pattern of foot trajectory. A 15-day long gait training was conducted with a stroke patient using ALEX, the results indicate that using ALEX and force-field controller, the patient's gait pattern improved significantly in many aspects. His gait speed improved both on treadmill from 1.45 km/h to 2.57 km/h and overground from 1.82 km/h to 2.50 km/h. His foot trajectory increased and got about 85% closer to a healthy subject's foot trajectory. Knee flexion increased from 27.2 deg to 47.5 deg and ankle dorsi-flexion increased from 1.9 deg to 5.9 deg by the end of the training. All these results indicate that by using these devices suitably and implementing a long term gait training can help patients with walking disability in a speedy recovery.
Author: Julio Salvador Lora Millán
Publisher: Springer Nature
ISBN: 3031576160
Category :
Languages : en
Pages : 154
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Book Description
Author: Spencer Ambrose Murray
Publisher:
ISBN:
Category : Electronic dissertations
Languages : en
Pages : 93
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Book Description
Author: Carlos A. Cifuentes
Publisher: Springer Nature
ISBN: 3030796302
Category : Technology & Engineering
Languages : en
Pages : 384
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Book Description
The concepts represented in this textbook are explored for the first time in assistive and rehabilitation robotics, which is the combination of physical, cognitive, and social human-robot interaction to empower gait rehabilitation and assist human mobility. The aim is to consolidate the methodologies, modules, and technologies implemented in lower-limb exoskeletons, smart walkers, and social robots when human gait assistance and rehabilitation are the primary targets. This book presents the combination of emergent technologies in healthcare applications and robotics science, such as soft robotics, force control, novel sensing methods, brain-computer interfaces, serious games, automatic learning, and motion planning. From the clinical perspective, case studies are presented for testing and evaluating how those robots interact with humans, analyzing acceptance, perception, biomechanics factors, and physiological mechanisms of recovery during the robotic assistance or therapy. Interfacing Humans and Robots for Gait Assistance and Rehabilitation will enable undergraduate and graduate students of biomedical engineering, rehabilitation engineering, robotics, and health sciences to understand the clinical needs, technology, and science of human-robot interaction behind robotic devices for rehabilitation, and the evidence and implications related to the implementation of those devices in actual therapy and daily life applications.
Author: Manuel Cardona
Publisher: Springer Nature
ISBN: 9811547327
Category : Science
Languages : en
Pages : 103
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Book Description
This book addresses cutting-edge topics in robotics and related technologies for rehabilitation, covering basic concepts and providing the reader with the information they need to solve various practical problems. Intended as a reference guide to the application of robotics in rehabilitation, it covers e.g. musculoskeletal modelling, gait analysis, biomechanics, robotics modelling and simulation, sensors, wearable devices, and the Internet of Medical Things.
Author: Fahad Hussain
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
The field of robot-assisted physical rehabilitation and robotics technology for providing support to the elderly population is rapidly evolving. Lower limb robot aided rehabilitation and assistive technology have been a focus for the engineering community over the last three decades as several robotic lower limb exoskeletons have been proposed in the literature as well as some being commercially available. One of the most important aspects of developing exoskeletons is the selection of the appropriate material. Strength to weight ratio is the most important factor to be considered before selection of a manufacturing material. The material selection strongly influences the overall weight and performance of the exoskeleton robot. In addition to material selection the type of mechanism and the actuation strongly effect the overall weight of the lower limb robotic exoskeleton. Most of the lower limb exoskeleton provided in the literature use a parallel mechanism, are properly actuated and either use aluminium or steel as their manufacturing materials. All these factors significantly increase the weight of the lower limb robot exoskeleton and make the device heavy, bulky, and uncomfortable for the wearer. Furthermore, an increase in weight contributes to a decrease of energy efficiency, reduces the energy efficiency of the final product, and increase the running cost of the designed robot devices. This thesis explores the wide-ranging potential of lower limb robot exoskeletons in the context of physical rehabilitation. Implementation and testing of a lightweight and high strength material without effecting the reliability was the main research objective of the present work. In this research, a linkage based under-actuated mechanism was used for the development of a lightweight design. Structural and mechanical load analysis of the mechanism was performed by using an advanced approach of finite element analysis. Three materials, namely structural steel, aluminium, and carbon reinforced fibre were compared as the manufacturing materials of the modelled mechanism. After that, a weight estimation was carried out for all three materials and the material which exhibits the best response under mechanical load analysis was selected. From the weight comparison, the carbon reinforced fibre provided the least weight for the digital twin of a lower limb exoskeleton. After material selection, the next step was the topology optimisation to further decrease the mass of the designed prototype without effecting the mechanical performance. The optimisation was carried out by using a multi-mode single objective genetic algorithm (GA) and a reduction of 30 % in the weight of the designed prototype was obtained. The selected material, which is carbon fibre, is a type of polymer material that is highly anisotropic, meaning it shows different material behaviour in different orientations of applied force. The next stage of the research work was the material characterization of the manufacturing material, which was carried out both analytically and experimentally. For defining the optimal criteria for fiber orientation, Hashin's Failure Criteria is considered, and experimental work is performed to determine the most suitable fibre orientation. The material monotonic tensile properties were experimentally determined by experimental work and used to select a suitable orientation to manufacture a physical prototype model of the lower limb robot exoskeleton. After that the manufacturing process was carried out which is divided into three main steps. The first step was the use of the suitable lightweight and high strength material, which was selected by weight comparison in the design stage. The second step was the use of a single actuator to actuate the whole mechanical system and the final step was the use fabrication method to get a strong and reliable structure. Shaping of the different exoskeleton parts was carried out by CNC milling and parts were assembled to build a robotic prototype. A DC motor was used to actuate the complete prototype, which includes hip, knee, and ankle joints. In the end, a reliability analysis was carried out by using a machine learning based approach. A machine learning framework was developed for time-dependent reliability analysis of the developed robot. A neural network algorithm was designed to estimate the time-dependent reliability of the joint displacement and the positions of the end-effector first. From the above methodology, a lightweight and high strength lower limb robot exoskeleton was just not only conceptualized but a significant work was done to get a physical model starting from the material selection and concluding with the fabrication of a physical prototype. The reliability analysis gives an overview of the mechanism safety as a function of joint displacement. The designed prototype of carbon reinforced fibre was four times lighter in weight as compared to steel and three times lighter than aluminium, which is expected to give the wearer a comfortable wearing experience and improves the overall physical rehabilitation experience for the patients.
Author: José L. Pons
Publisher: John Wiley & Sons
ISBN: 0470987650
Category : Technology & Engineering
Languages : en
Pages : 358
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Book Description
A wearable robot is a mechatronic system that is designed around the shape and function of the human body, with segments and joints corresponding to those of the person it is externally coupled with. Teleoperation and power amplification were the first applications, but after recent technological advances the range of application fields has widened. Increasing recognition from the scientific community means that this technology is now employed in telemanipulation, man-amplification, neuromotor control research and rehabilitation, and to assist with impaired human motor control. Logical in structure and original in its global orientation, this volume gives a full overview of wearable robotics, providing the reader with a complete understanding of the key applications and technologies suitable for its development. The main topics are demonstrated through two detailed case studies; one on a lower limb active orthosis for a human leg, and one on a wearable robot that suppresses upper limb tremor. These examples highlight the difficulties and potentialities in this area of technology, illustrating how design decisions should be made based on these. As well as discussing the cognitive interaction between human and robot, this comprehensive text also covers: the mechanics of the wearable robot and it’s biomechanical interaction with the user, including state-of-the-art technologies that enable sensory and motor interaction between human (biological) and wearable artificial (mechatronic) systems; the basis for bioinspiration and biomimetism, general rules for the development of biologically-inspired designs, and how these could serve recursively as biological models to explain biological systems; the study on the development of networks for wearable robotics. Wearable Robotics: Biomechatronic Exoskeletons will appeal to lecturers, senior undergraduate students, postgraduates and other researchers of medical, electrical and bio engineering who are interested in the area of assistive robotics. Active system developers in this sector of the engineering industry will also find it an informative and welcome resource.
Author: Kazuto Kora
Publisher:
ISBN:
Category : Cerebrovascular disease
Languages : en
Pages : 100
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Book Description
Stroke is one of the leading cause of physical disability in New Zealand and many suffer paralysis to their limbs. Unfortunately, fewer than 50% of survivors regaining their independence after 6 months particularly due to the inability to walk properly. One of the reason for the slow recovery of the gait function is that the current rehabilitation technique used is labour intensive and time consuming for the therapists and difficult to perform it effectively. In order to improve the gait rehabilitation process, robot assisted gait rehabilitation has gained much interest over the past years. There have been many prototypes and commercial products for the robot assisted rehabilitation, but many had limitations. One of which is being bulky and had uncomfortable attachment for the patients. Improper attachment not only create uncomfortable feeling and pain for the patient but also causes human-robot axis misalignment which could lead to an injury with long term use. Another limitation is the lack of mechanical compliance which is the key to improve the safety of the operation and comfort for the patient. In order to address the limitations identified, a new robot orthosis, Human-inspired Robotic Exoskeleton (HuREx) was developed. HuREx consists of a compact exoskeleton parts custom fit for each individual patient manufactured using a rapid prototyping technique. Pneumatic Muscle Actuators (PMA) were used as they exhibit natural compliance and configured antagonistically. The design of the orthosis and the actuation mechanism made the system highly nonlinear. Therefore, an advanced model-based feedforward (FF) controller was designed and implemented to achieve the speed and accuracy of the response required. Many experiments were carried out to observe the performance and verify the proof of concept. The contributions of this research are the development of new robotic exoskeleton device designed to be light weight, comfortable and safe to use for gait rehabilitation for stroke patients, which were lacking in the existing devices. Another contribution is the establishment of new manufacturing technique that allow custom exoskeleton component for each individual patient. Finally the development of advanced model-based FF controller that achieves fast and accurate tracking performance.
Author: Shahid Hussain
Publisher:
ISBN:
Category : Gait disorders
Languages : en
Pages : 176
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Book Description
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.
Author: Akim Kapsalyamov
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
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.
