Наука потихоньку догоняет природу, помогая людям возвращаться к нормальной жизни. Ученые из Университета Мичигана (University of Michigan) – Арт Куо (Art Kuo) и Стив Коллинз (Steve Collins) – исследуя проблемы современных протезных систем, пришли к выводу, что наиболее «запущенными» по части удобства для человека являются протезы лодыжки.

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One of the embodiments of the invention is an actuator system for extending and flexing a joint. The actuator system includes a multi-motor assembly for providing a rotational output, a rotary-to-linear mechanism including a screw that accepts the rotational output of the multi-motor assembly and a nut that cooperates with the screw to convert rotational movement of the screw to linear movement of the nut, and a moving rail with a latch that functions to translate linear movement of the nut in both the extension and flexion directions into an extension and flexion of the joint. The actuator has been specifically designed for extending and flexing a joint (such as an ankle, a knee, an elbow, or a shoulder) of a human. The actuator system may, however, be used to move any suitable object through any suitable movement (linear, rotational, or otherwise).

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An actuator system for extending and flexing a joint, including a multi-motor assembly for providing a rotational output, a rotary-to-linear mechanism for converting the rotational output from the multi-motor assembly into an extension and flexion of the joint, and a controller for operating the actuator system in several operational modes. The multi-motor assembly preferably combines power from two different sources, such that the multi-motor assembly can supply larger forces at slower speeds (“Low Gear”) and smaller forces at higher speeds (“High Gear”). The actuator has been specifically designed for extending and flexing a joint (such as an ankle, a knee, an elbow, or a shoulder) of a human. The actuator system may, however, be used to move any suitable object through any suitable movement (linear, rotational, or otherwise).

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A lower extremity exoskeleton (100) includes: at least one power unit (201); two leg supports (101, 102) designed to rest on the ground (130); two knee joints (107, 108) configured to allow flexion and extension between respective shank (105, 106) and thigh links (103, 104) of the leg supports (101, 102); an exoskeleton trunk (109) rotatably connectable to the leg supports (101, 102); and two hip actuators (145, 146) configured to create torques between the exoskeleton trunk (109) and the leg supports (101, 102). In use, the hip actuators (145, 146) create a torque to move the leg supports (101, 102) backward relative to the exoskeleton trunk ( 109) during a stance phase, which pushes the exoskeleton trunk (109) forward. A second torque may be used to move the leg supports (101, 102) forward relative to the exoskeleton trunk (109) into a swing phase. Additionally, a swing torque may be generated during the swing phase to move the leg support (101, 102) forward relative to the exoskeleton trunk (109). This results in decreased oxygen consumption and heart rate of a user wearing the exoskeleton (100).

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Human-robot control interfaces have received increased attention during the past decades. With the introduction of robots in everyday life, especially in providing services to people with special needs (i.e., elderly, people with impairments, or people with disabilities), there is a strong necessity for simple and natural control interfaces. In this paper, electromyographic (EMG) signals from muscles of the human upper limb are used as the control interface between the user and a robot arm. EMG signals are recorded using surface EMG electrodes placed on the user’s skin, making the user’s upper limb free of bulky interface sensors or machinery usually found in conventional human-controlled systems. The proposed interface allows the user to control in real time an anthropomorphic robot arm in 3-D space, using upper limb motion estimates based only on EMG recordings. Moreover, the proposed interface is robust to EMG changes with respect to time, mainly caused by muscle fatigue or adjustments of contraction level. The efficiency of the method is assessed through real-time experiments, including random arm motions in the 3-D space with variable hand speed profiles.

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