Post-stroke neurorehabilitation based on virtual therapies are performed completing repetitive exercises shown in visual electronic devices, whose content represents imaginary or daily life tasks. ...Currently, there are two ways of visualization of these task. 3D virtual environments are used to get a three dimensional space that represents the real world with a high level of detail, whose realism is determinated by the resolucion and fidelity of the objects of the task. Furthermore, 2D virtual environments are used to represent the tasks with a low degree of realism using techniques of bidimensional graphics. However, the type of visualization can influence the quality of perception of the task, affecting the patient's sensorimotor performance. The purpose of this paper was to evaluate if there were differences in patterns of kinematic movements when post-stroke patients performed a reach task viewing a virtual therapeutic game with two different type of visualization of virtual environment: 2D and 3D. Nine post-stroke patients have participated in the study receiving a virtual therapy assisted by PUPArm rehabilitation robot. Horizontal movements of the upper limb were performed to complete the aim of the tasks, which consist in reaching peripheral or perspective targets depending on the virtual environment shown. Various parameter types such as the maximum speed, reaction time, path length, or initial movement are analyzed from the data acquired objectively by the robotic device to evaluate the influence of the task visualization. At the end of the study, a usability survey was provided to each patient to analysis his/her satisfaction level. For all patients, the movement trajectories were enhanced when they completed the therapy. This fact suggests that patient's motor recovery was increased. Despite of the similarity in majority of the kinematic parameters, differences in reaction time and path length were higher using the 3D task. Regarding the success rates were very similar. In conclusion, the using of 2D environments in virtual therapy may be a more appropriate and comfortable way to perform tasks for upper limb rehabilitation of post-stroke patients, in terms of accuracy in order to effectuate optimal kinematic trajectories.
This paper presents the concept, design process, and the prototype of a novel haptics-based lower-extremity rehabilitation robot for bed-ridden stroke patients. This system, named Virtual Gait ...Rehabilitation Robot (ViGRR), is required to provide the average gait motion training as well as other targeted exercises such as leg press, stair stepping and motivational gaming, in order to facilitate motor learning and enable the training of daily activities such as walking and maintaining balance. The system requirements are laid out and linked to the design of a redundant planar 4DOF robot concept prototype. An iterative design optimization loop was setup to obtain the robot kinematic and dynamic parameters as well as the actuators. The robot’s mechanical design, model, safety features, admittance controllers, and the architecture of the haptic controller are presented. Preliminary experiments were planned and performed to evaluate the capability of the system in delivering task-based virtual-reality exercises and trajectory following scenarios.
Recent breakthroughs in computer vision areas, ranging from detection, segmentation, to classification, rely on the availability of large-scale representative training datasets. Yet, robotic vision ...poses new challenges towards applying visual algorithms developed from these datasets because the latter implicitly assume a fixed set of categories and time-invariant distribution of tasks. In practice, assistive robots should be able to operate in dynamic environments with everyday changes. The variations of four commonly observed factors, including illumination, occlusion, camera-object distance/angles and clutter, could make lifelong/continual learning in computer vision more challenging. Large-scale datasets previously made publicly available were relatively simple, and rarely include such real-world challenges in data collection. Benefited from the recent released OpenLORIS-Object dataset, which explicitly includes these real-world challenges in the lifelong object recognition task, we evaluate three most adopted regularization methods in lifelong/continual learning (Learning without Forgetting, Elastic Weights Consolidation, and Synaptic Intelligence). Their performances were compared with the naive and cumulative training modes as the lower bound and upper bound of performances, respectively. The experiments conducted on the dataset focused on task incremental learning, i.e., incremental difficulty based on the four environment of factors. However, all the three most reported lifelong/continual learning algorithms have failed with the increase in encountered batches across various metrics with indistinguishable performance comparing to the naive training mode. Our results highlight the current challenges in lifelong object recognition for assistive robots to operate in real-world dynamic scene.
Gait symmetry training plays an essential role in the rehabilitation of hemiplegic patients. Robotics-based gait training has been widely accepted by patients and clinicians. Reference trajectory ...generation for the affected side using the motion data of the unaffected side is an important way to achieve this. However, online generation of gait reference trajectory requires the algorithm to provide correct gait phase delay and could reduce the impact of measurement noise from sensors and input uncertainty from users. Based on an active knee orthosis (AKO) prototype, this work presents an adaptive symmetric gait trajectory generation framework for the gait rehabilitation of hemiplegic patients. Using the adaptive nonlinear frequency oscillators (ANFO) and movement primitives, we implement online gait pattern encoding and adaptive phase delay according to the real-time user input. A shared autonomy (SA) module with online input validation and arbitration has been designed to prevent undesired movements from being transmitted to the actuator on the affected side. The experimental results demonstrate the feasibility of the framework. Overall, this work suggests that the proposed method has the potential to perform gait symmetry rehabilitation in an unstructured environment and provide a kinematic reference for torque-assistance AKO.
Background. Modular lower extremity robotics may offer a valuable avenue for restoring neuromotor control after hemiparetic stroke. Prior studies show that visually guided and visually evoked ...practice with an ankle robot (anklebot) improves paretic ankle motor control that translates into improved overground walking. Objective. To assess the feasibility and efficacy of daily anklebot training during early subacute hospitalization poststroke. Methods. Thirty-four inpatients from a stroke unit were randomly assigned to anklebot (n = 18) or passive manual stretching (n = 16) treatments. All suffered a first stroke with residual hemiparesis (ankle manual muscle test grade 1/5 to 4/5), and at least trace muscle activation in plantar- or dorsiflexion. Anklebot training employed an “assist-as-needed” approach during >200 volitional targeted paretic ankle movements, with difficulty adjusted to active range of motion and success rate. Stretching included >200 daily mobilizations in these same ranges. All sessions lasted 1 hour and assessments were not blinded. Results. Both groups walked faster at discharge; however, the robot group improved more in percentage change of temporal symmetry (P = .032) and also of step length symmetry (P = .038), with longer nonparetic step lengths in the robot (133%) versus stretching (31%) groups. Paretic ankle control improved in the robot group, with increased peak (P ≤ .001) and mean (P ≤ .01) angular speeds, and increased movement smoothness (P ≤ .01). There were no adverse events. Conclusion. Though limited by small sample size and restricted entry criteria, our findings suggest that modular lower extremity robotics during early subacute hospitalization is well tolerated and improves ankle motor control and gait patterning.
This paper presents a novel, smart, and portable active knee rehabilitation orthotic device (AKROD) that provides variable damping at the knee joint, controlled in ways that can facilitate motor ...recovery in poststroke and other neurological disease patients, and to accelerate recovery in knee injury patients. The key features of AKROD include a compact, lightweight design, with highly tunable resistive torque capabilities through a variable damper component that is achieved through an electrorheological fluid (ERF) smart brake. Closed-loop torque and velocity controllers based on adaptive nonlinear control methodologies were developed and successfully implemented on the ERF brake. Preliminary testing of AKROD was performed using nine healthy subjects executing a set of isokinetic and isotonic exercises. These results were compared with exactly the same tests performed on a modern day computer controlled rehabilitation resistance machine, a Biodex System 3. The results showed comparable accuracy and repeatability between the two devices.
Virtual reality (VR) rehabilitation systems have been proposed to enable prosthetic hand users to perform training before receiving their prosthesis. Improving pre-prosthetic training to be more ...representative and better prepare the patient for prosthesis use is a crucial step forwards in rehabilitation. However, existing VR platforms lack realism and accuracy in terms of the virtual hand and the forces produced when interacting with the environment. To address these shortcomings, this work presents a VR training platform based on accurate simulation of an anthropomorphic prosthetic hand, utilising an external robot arm to render realistic forces that the user would feel at the attachment point of their prosthesis. Experimental results with non-disabled participants show that training with this platform leads to a significant improvement in Box and Block scores compared to training in VR alone and a control group with no prior training. Results performing pick-and-place tasks with a wider range of objects demonstrates that training in VR alone negatively impacts performance, whereas the proposed platform has no significant impact on performance. User perception results highlight that the platform is much closer to using a physical prosthesis in terms of physical demand and effort, however frustration is significantly higher during training.
Aiming at solving the problems of the existing lower limb rehabilitation robots on aspects of configuration limitations, human-machine compatibility, gravity compensation, and multimodal ...rehabilitation, a movable cable-driven lower limb rehabilitation robot (MCLR) is proposed in this paper, which can realize the gait training and walking training in passive mode, initiative mode, and assistive mode. First, the structure and working principle of MCLR is introduced. The traction type is further optimized. Second, the key control problems of the passive force servo system are analyzed in detail. In order to improve the loading accuracy and speed during the initiative training, the dynamic model of the cable-driven unit is established. Based on this model, an active force control strategy is proposed. Finally, the speed control strategy and the active force control strategy are studied experimentally. The experimental results show that the speed servo system has good tracking ability, which can meet the requirements of the passive rehabilitation. The active force control strategy can significantly improve the loading accuracy and the dynamic performance of the force servo system. The force servo system has good tracking ability in the normal rehabilitation frequency band, which can meet the requirements of the initiative rehabilitation.
Ankle dysfunction is common in the public following injuries, especially for stroke patients. Most of the current robotic ankle rehabilitation devices are driven by rigid actuators and have problems ...such as limited degrees of freedom, lack of safety and compliance, and poor flexibility. In this letter, we design a new type of compliant ankle rehabilitation robot redundantly driven by pneumatic muscles (PMs) and cables to provide full range of motion and torque ability for the human ankle with enhanced safety and adaptability, attributing to the PM's high power/mass ratio, good flexibility and lightweight advantages. The ankle joint can be compliantly driven by the robot with full three degrees of freedom to perform the dorsiflexion/plantarflexion, inversion/ eversion, and adduction/abduction training. In order to keep all PMs and cables in tension which is essential to ensure the robot's controllability and patient's safety, Karush-Kuhn-Tucker (KKT) theorem and analytic-iterative algorithm are utilized to realize a hierarchical force-position control (HFPC) scheme with optimal force distribution for the redundant compliant robot. Experiment results demonstrate that all PMs are kept in tension during the control while the position tracking accuracy of the robot is acceptable, which ensures controllability and stability throughout the compliant robot-assisted rehabilitation training.
There have been significant advances in the technologies for robot-assisted lower limb rehabilitation in the past decade. However, the development of similar systems for children has been slow ...despite the fact that children with conditions, such as cerebral palsy, spina bifida, and spinal cord injury (SCI), can benefit greatly from these technologies. Robotic-assisted gait therapy (RAGT) has emerged as a way to increase gait training duration and intensity while decreasing the risk of injury to therapists. Robotic walking devices can be coupled with motion sensing, electromyography, scalp electroencephalography, or other noninvasive methods of acquiring information about the user's intent to design brain-computer interfaces (BCI) for neuromuscular rehabilitation and control of powered exoskeletons. For users with SCI, BCIs could provide a method of overground mobility closer to the natural process of the brain controlling the body's movement during walking than mobility by wheelchair. For adults, there are currently four Food and Drug Administration (FDA) approved lower limb exoskeletons that could be incorporated into such a BCI system, but there are no similar devices specifically designed for children, who present additional physical, neurological, and cognitive developmental challenges. The current state-of-the-art for pediatric RAGT relies on large clinical devices with high costs that limit accessibility. This can reduce the amount of therapy a child receives and slow the rehabilitation progress. In many cases, the lack of gait training can result in a reduction in the mobility, independence, and overall quality of life for children with lower limb disabilities. Thus, it is imperative to facilitate and accelerate the development of pediatric technologies for gait rehabilitation, including their regulatory path. In this article, an overview of the U.S. FDA clearance/approval process is presented. An example device has been used to navigate important questions facing device developers focused on providing lower limb rehabilitation to children in home based or other settings beyond the clinic.
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