The Intuitive Leg Assist Device (I-LAD) is designed to address a demographic of people with lower extremity weakness. It optimizes cost, weight, and functionality, and provides the power and support needed to perform natural ambulation. The design mimics the human gait cycle by coupling the actuation of the knee and hip via a dual four-bar linkage system modified from a crank rocker system, with a 12.8% and 14.1% error in the hip and knee movement, respectively. The patient supports the device using an over the shoulder harness and modified work belt, both connected to an acrylic plate. The plate serves as the mounting for the motor, planetary gear system, and electrical components that drive the linkage system. The linkage system is connected to a knee brace and ankle foot orthosis that minimizes the effect of foot drop. The design implements feedback and safety by incorporating four sensor inputs-two force sensors beneath the feet and two goniometers on the hips-and a microprocessor, which controls motor actuation. The program logic ensures that the device shuts down upon unintended user movement, minimizing safety hazards.

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Rehabilitation for recovering the nerve motor system of patients with neuromuscular damage, such as those due to spinal cord injury and spasm, has been based on extremely labour intensive physiotherapy procedures. A potential solution for helping patients to expedite their recovery from neurological disorders and improve their ability in performing activities of daily living would be by using mechatronic-assistive devices that can be controlled by the patients themselves. The inclusion of modern input devices such as Head Mouse or brain-computer interface technology with neurological stimulation to help neural modulation has been advocated by others in the related research community. This paper introduces a power-assisted exoskeleton prototype system for producing elbow flexion-extension motion by using a Head Mouse as an input of control commands by the patient. Experiments were conducted to evaluate the effectiveness (Position, Velocity, Acceleration, and Torque) of the exoskeleton. Results demonstrate that the device would be a useful rehabilitation tool for patients with neuromuscular disorder.

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Background: While sparsely researched, funding structures may play an important role in use of and satisfaction with prostheses and related health services.

Objectives: The objectives of this study were to (1) quantify the direct costs of prosthesis wear, (2) explore variations in funding distribution, and (3) describe the role of affordability in prosthesis selection and wear.

Study design: An anonymous, online cross-sectional descriptive survey was administered.

Methods: Analyses were conducted of qualitative and quantitative data extracted from an international sample of 242 individuals with upper limb absence.

Results: Access to prosthesis funding was variable and fluctuated with age, level of limb absence and country of care. Of individuals who gave details on prosthetic costs, 63% (n = 69) were fully reimbursed for their prosthetic expenses, while 37% (n=40) were financially disadvantaged by the cost of components (mean [SD] US$9,574 [$9,986]) and their ongoing maintenance (US$1,936 [$3,179]). Of the 71 non-wearers in this study, 48% considered cost an influential factor in their decision not to adopt prosthesis use.

Conclusions: Prosthesis funding is neither homogeneous nor transparent and can be influential in both the selection and use of a prosthetic device.

Clinical relevance

Inequitable access to prosthesis funding is evident in industrialized nations and may lead to prosthesis abandonment and/or diminished quality of life for individuals with upper limb absences. Increased efforts are required to ensure equitable access to upper limb prosthetics and related services in line with individuals’ needs.

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This paper presents a sensor fusion strategy to estimate the absolute position and to identify the gait events of an active ankle-foot orthosis (AAFO). Sensor fusion is implemented using a Kalman filter with the signals of a gyroscope and an accelerometer, both present in an inertial measurement unit (IMU), besides the signals of three force sensitive resistors (FSRs) mounted in a sole of shoe. For correcting the gyroscope-based position, the redundant accelerometer-based position must be used only under reliable conditions, which are obtained by a proposed switching logic to enable the Kalman filter. Experimental results of the AAFO confirm the efficiency of the proposed sensor fusion strategy.

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Patients with damage to the cerebellum make reaching movements that are uncoordinated, or ataxic — movements can be misdirected, over- or under-shoot targets, and more variable than the movements of healthy people. In addition, it is thought that cerebellar patients cannot adapt to (learn) new dynamics. This dissertation explores models of cerebellar ataxia and the use of robotic tools to improve human motor performance. We began by developing a dynamic model of the human arm and a robot exoskeleton. This model was populated with parameter values obtained through direct measurement, system identification, and use of Dempster’s anthropometric table [1]. This system was then used to conduct three studies.

In the first study, we used an exoskeleton robot to record the movements of cerebellar patients performing a targeted reaching task. These data and our dynamic model were used to test hypotheses proposed in the literature about the role of the cerebellum. We found evidence supporting the general hypothesis that the cerebellum functions as an internal model for planning movements and that damage to the cerebellum results in a biased (inaccurate) model, although the model does not completely explain cerebellar behavior. Computer simulations found optimal, patient-specific perturbations to actual limb dynamics that are predicted to reduce root-mean-squared directional reaching errors by an average of 41%.

In the second study, we used the same robot to implement a change in dynamics predicted to assist each patient. This required a controller design, the addition of accelerometers to the robot, and characterization of the robot’s ability to render acceleration-dependent forces. We found that this approach may improve the reaching of some cerebellar patients and not for others, and there was no evidence of motor learning.

In the third study, we investigated how a different assistive controller can be used to improve reaching behavior. We used the robot to render force channels to constrain arm movements during reaching, and explored how the ordering of null (robot passive) and channel (robot active) trial blocks affected motor learning. We found that force channels resulted in significant improvements in reaching performance in the directions both parallel and orthogonal to the force channel. However, we found no evidence that reaching practice in these channels results in improved reaching performance after the channels are removed.

The use of tools from the field of robotics allows precise measurements and interventions to understand and treat human motor deficits. We believe that model-based and patient-specific robot assistance and rehabilitation paradigms will lead to an increased understanding of the brain and improved patient outcomes.

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