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The structural design, control system, and integrated biofeedback for a wearable exoskeletal robot for upper extremity stroke rehabilitation are presented. Assisted with clinical evaluation, designers, engineers, and scientists have built a device for robotic assisted upper extremity repetitive therapy (RUPERT). Intense, repetitive physical rehabilitation has been shown to be beneficial overcoming upper extremity deficits, but the therapy is labor intensive and expensive and difficult to evaluate quantitatively and objectively. The RUPERT is developed to provide a low cost, safe and easy-to-use, robotic-device to assist the patient and therapist to achieve more systematic therapy at home or in the clinic. The RUPERT has four actuated degrees-of-freedom driven by compliant and safe pneumatic muscles (PMs) on the shoulder, elbow, and wrist. They are programmed to actuate the device to extend the arm and move the arm in 3-D space. It is very important to note that gravity is not compensated and the daily tasks are practiced in a natural setting. Because the device is wearable and lightweight to increase portability, it can be worn standing or sitting providing therapy tasks that better mimic activities of daily living. The sensors feed back position and force information for quantitative evaluation of task performance. The device can also provide real-time, objective assessment of functional improvement. We have tested the device on stroke survivors performing two critical activities of daily living (ADL): reaching out and self feeding. The future improvement of the device involves increased degrees-of-freedom and interactive control to adapt to a user's physical conditions.

A unique, robust, robotic transtibial prosthesis with regenerative kinetics was successfully built and a 6-month human subject trial was conducted on one male below-the-knee amputee under linear walking conditions. This paper presents the quasistatic system modeling, DC motor and transmission modeling and analyses, design methodology, and model verification. It also outlines an approach to the design and development of a robotic transtibial prosthesis. The test data will show that the true power and energy requirement predicted in the modeling and analyses is in good agreement with the measured data, verifying that the approach satisfactorily captures the physical system. The modeling and analyses in this paper describes a process to determine an optimal combination of motors, springs, gearboxes, and rotary to linear transmissions to significantly minimize the power and energy consumption. This kinetic minimization allows the downsizing of the actuation system and the battery required for daily use to a self-portable level.

A robotic tendon is a spring based, linear actuator in which the stiffness of the spring is crucial for its successful use in a lightweight, energy efficient, powered ankle orthosis. Like its human analog, the robotic tendon uses its inherent elastic nature to reduce both peak power and energy requirements for its motor. In the ideal example, peak power required of the motor for ankle gait is reduced from 250 W to just 77 W. In addition, ideal energy requirements are reduced from nearly 36 J to just 21 J. Using this approach, an initial prototype has provided 100% of the power and energy necessary for ankle gait in a compact 0.95 kg package, seven times less than an equivalent motor/gearbox system.

With microprocessing power greatly increasing, hardware is no longer a hurdle in the development of controllers for wearable robotic systems, specifically lower limb robots. The challenge remains in developing smart algorithms that are able to detect which task a person is about to perform and then determine the correct desired movements for the robotic system. This paper reflects on four existing control algorithms for the task of level ground walking, and then presents theory and test results of a novel control algorithm based on phase plane invariants. The goal of this paper is to produce the correct motor reference command in a continuous fashion rather than based on determining distinct states for a given task.