Two novel designs for a rehabilitation robotic glove are detailed. The paper focuses of the design and implementation of these devices. The main aim is to explore lightweight, low profile gloves that can facilitate movement of fingers that have lost strength or nerve control. This has been by achieved by using an exoskeleton to provide the actuation for flexion, thereby limiting the number of active actuators required. Pneumatic muscle actuators were used to provide flexion force, and force sensors used to supply control inputs by the user. Control methods have been implemented that would help lead to the development of rehabilitation programs. The glove can also be used as an assistive device in order to allow the patient to grasp and pick up objects. Prototype I, with 1 DOF, was found to successfully actuate a hand in order to grasp a shape similar in size to a golf ball. Prototype II, with 3 DOF, achieved actuation of a single finger from fully flexed to at rest elongation.

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Термин «интерфе йс» поисходит от английского слова Interface (поверхность раздела, перегородка). Представляет совокупность средств, методов и правил взаимодействия между элементами целого. Приставка «нейро-» (Neuro-) указывает на связь с нервами или нервной системой.

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In recent years, detecting upper-limb motion intention has attracted growing research attention in order to improve the manipulation of a prosthetic hand. Recording of forearm muscle activity has been used as a signal source to detect wrist and hand motions using different pattern recognition techniques. However, it is difficult to take in consideration body coordinated motions from these signals alone; therefore the movement of the artificial limb can be unnatural, if consider as a part of the whole body coordination, and a dynamical coupling between the user and the prosthesis is impos-sible. Also, using only forearm muscle activities to drive the artificial limb leaves aside the possibi-lity for higher level amputees to use these systems.

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Limited research has been done on exoskeletons to enable faster movements of the lower extremities. An exoskeleton’s mechanism can actually hinder agility by adding weight, inertia and friction to the legs; compensating inertia through control is particularly difficult due to instabili-ty issues. The added inertia will reduce the natural frequency of the legs, probably leading to lower step frequency during walking. We present a control method that produces an approximate compensation of an exoskeleton’s inertia. The aim is making the natural frequency of the exoskeleton-assisted leg larger than that of the unaided leg. The method uses admittance control to compensate for the weight and friction of the exoskeleton. Inertia compensation is emulated by adding a feedback loop consisting of low-pass filtered acceleration multiplied by a negative gain. This gain simulates negative inertia in the low-frequency range. We tested the controller on a statically supported, single-degree-of-freedom exoskeleton that assists swing movements of the leg. Subjects performed movement sequences, first unassisted and then using the exoskeleton, in the context of a computer-based task resembling a race. With zero inertia compensation, the steady-state frequency of the leg swing was consistently reduced. Adding inertia compensation enabled subjects to recover their normal frequency of swing.

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This study was conducted to compare a modified load (ML) configuration (total mass = 36.5 kg) to a heavier load (total mass = 42.2 kg) comprised of currently issued items (SL) used by U.S. Army dismounted warfighters in theater. Both loads were compared to a baseline, i.e., a no-load (NL) condition (total mass = 9.1 kg). Fourteen Army Infantry Soldiers participated in this study, completing a series of tests in each load configuration. Oxygen uptake and gait kinematics and kinetics were recorded as participants walked (1.34 m/s on 0, 9, and 18% grades) and ran (2.46 m/s on a 0% grade). Rifle marksmanship (prone, kneeling, and standing firing positions) and grenade throws were assessed for accuracy and timeliness or accuracy and precision, respectively. Maximal effort physical activities were completed, consisting of five continuous 30-m rushes and obstacle course runs. Range of motion measurements and participants’ assessments of the load configurations were also included. Results: Mean oxygen uptake scaled to percentage of 2OVmax was significantly higher during walking and running for the ML and the SL conditions compared with the NL. Also, for walking at 9% grade, oxygen uptake for the ML was significantly lower than that for the SL. The kinematic and kinetic data generally revealed favorable significant differences for the NL compared with the ML and the SL configurations. On the shooting performance tasks and the maximal effort tasks, performance with the SL configuration differed from that with the NL to a greater extent than the ML configuration did. Participants rated the ML as their preferred configuration.

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