When I joined the Marine Corps, I wore a helmet, flak jacket, two canteens with cup, and a first aid kit. I had two magazine pouches that held six rifle magazines, and I could carry two fragmentation grenades on each of the magazine pouches. That was the extent of my load. In the mid-1990s, we hit a technological explosion and are still being buried by great combat gear. Today I wear a different helmet, an interceptor vest with small arms protective inserts, and have really increased what I carry, quadrupled what I have to be able to do, and decreased tenfold the amount of time that I have to learn all of my required skills. On 24 May 2004, there was an article in the Marine Times discussing hot new gear proposed by the Marine Corps Warfighting Laboratory (MCWL). This article identified even more gear to come the infantryman’s way. This is not a ridiculous thought either. These are mission essential equipment identified over years of actual missions and detailed analysis. Without delving into the training time required just for the equipment additions, we should seriously consider the combat load of the individual. In 2001, the Infantry Operational Advisory Group recommended key weights during different times of movement toward the enemy. But based on actual experiences, there is no reasonable way to follow these combat load guidelines. The answer to our increasing dilemma of combat load may have been identified in Robert A. Heinlein’s book Starship Troopers. In the story, one man had a strength-enhancing exoskeleton suit that protected him from the environment, to include chemical or biological worries. It allowed the wearer to jump over buildings and run across countrysides faster than today’s vehicles. There were built-in communications, optics, protection, and strength. In many ways Heinlein’s projection has been accurate. What we have not done is attacked the basic problem of the equipment load that he has to carry. This may be about to change.

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This paper describes the development of a pneumatic robot for functional movement training of the arm and hand after stroke. The device is based on the Wilmington Robotic Exoskeleton (WREX), a passive, mobile arm support developed for children with arm weakness caused by a debilitative condition. Previously, we scaled WREX for use by adults, instrumented it with potentiometers, and incorporated a simple grip strength sensor. The resulting passive device (Training WREX or «T-WREX») allows individuals with severe motor impairment to practice functional movements (reaching, eating, and washing) in a simple virtual reality environment called Java Therapy 2.0. However, the device is limited since it can only apply a fixed pattern of assistive forces to the arm. In addition, its gravity balance function does not restore full range of motion. Therefore, we are also developing a robotic version of WREX named Pneu-WREX, which can apply a wide range of forces to the arm during naturalistic movements. Pneu-WREX uses pneumatic actuators, non-linear force control, and passive counter-balancing to allow application of a wide range of forces during naturalistic upper extremity movements. Besides a detailed description of the mechanical design and kinematics of Pneu-WREX, we present results from a survey of 29 therapists on the use of such a robotic device.

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The potential for using an exoskeleton to support mobility has been considered for some time. The paper describes the procedures associated with the analysis, design and implementation of a model for a lightweight design of such an exoskeletonand shows how the integration of motion analysis with modelling supported the development of the concept. It then proceeds to consider the implementation of the identified control and operational strategies in model form and how the basic concepts developed are being deployed in support of an implementation of system to support the rehabilitation of the lower limbs.

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The development of a prototype robotic system to facilitate upper extremity (UE) rehabilitation in individuals who sustain neurological impairments such as cervical level spinal cord injuries (SCI), acquired brain injuries (ABIs) or stroke (CVA) is described. A control system based on electromyography (EMG) signals has been implemented to provide the appropriate amount of assistance or resistance necessary to progress a patient’s movement recovery. Use of EMG signals has potential advantages over systems based only on torque and position sensors. The prototype system includes programmable mechanical impedance, adjustable thresholds and control gains. This robotic rehabilitation device would be used to provide repeated motor practice in an effort to promote neurological recovery and improve functional use of the UE.

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LOPES aims for an active role of the patient by selective and partial support of gait functions during robotic treadmill training sessions. Virtual model control (VMC) was applied to the robot as an intuitive method for translating current treadmill gait rehabilitation therapy programs into robotic rehabilitation therapy. Virtual models are proposed for the selective control of gait functions during treadmill training. From this collection of models several, representing the extremes of the entire set of virtual models, were implemented. The results show that VMC is a promising method for the control of a gait rehabilitation robot.

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