This paper presents a new hand motion assist robot for rehabilitation therapy. The robot is an exoskeleton with 18 DOFs and a self-motion control, which allows the impaired hand of a patient to be driven by his or her healthy hand on the opposite side. To provide such potential that the impaired hand is able to recover its ability to the level of a functional hand, the hand motion assist robot is designed to support the flexion/extension and abduction/adduction motions of fingers and thumb independently as well as the opposability of the thumb. Moreover, it is designed to support a combination motion of the hand and the wrist. The design specifications and experimental results are shown.

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Many places in the world are too rugged or enclosed for vehicles to access. Even today, material transport to such areas is limited to manual labor and beasts of burden. Modern advancements in wearable robotics may make those methods obsolete. Lower extremity exoskeletons seek to supplement the intelligence and sensory systems of a human with the significant strength and endurance of a pair of wearable robotic legs that support a payload. This article first outlines the use of Clinical Gait Analysis data as the framework for the design of such a system at UC Berkeley. This data is used to design the exoskeleton degrees of freedom and size its actuators. It will then give an overview of one of the control schemes implemented on the BLEEX. The control algorithm described here increases the system closed loop sensitivity to its wearer’s forces and torques without any measurement fromthe wearer (such as force, position, or electromyogram signal). The control algorithm uses the inverse dynamics of the exoskeleton, scaled by a number smaller than unity, as a positive feedback controller. This controller almost destabilizes the system since it leads to an overall loop gain slightly smaller than unity and results in a large sensitivity to all wearer’s forces and torques thereby allowing the exoskeleton to shadow its wearer.

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Microelectromechanical systems (MEMS) are revolutionizing a multitude of industries world wide, from consumer products to the scientific community. Rehabilitation robotics is a robotic field specially interested in using the advantages of inertial sensors. The essential aspect in this area is the intrinsic interaction between human and robot, which imposes several restrictions in the design of this sort of robots. This paper addresses the analysis of the application of inertial sensors as sensing technologies in controlled orthotic devices with a detailed analysis with two biomechatronic robotics rehabilitation exoskeletons, one for the upper and other for the lower limb. Eventually, the results and conclusion of the experiments are given.

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It is proposed that copepods grow between one moult and the next in much the same fashion as established by Klaus Anger and others for decapod crustacean larvae. The analogy is justified by commonality of approximately isochronal development patterns, potential for continuously exponential growth at stage-to-stage resolution, and demonstrated points of reserve saturation. Thus, as for crab zoeae, the copepod pattern should be very fast initial growth, then slowing as activity shifts to preparation of the new exoskeleton prior to moult. As much as 80% of growth may occur in the first half of the moult cycle, with no growth at all in the last third. Establishing the exact patterns for copepods faces difficulties not presented by decapod larvae, and some solutions to these problems are suggested. Obtaining precise data will help to predict and interpret (model correctly) the effects of food limitation in the field.

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We propose a novel control method for lower-limb assist that produces a virtual modification of the mechanical impedance of the human limbs. This effect is accomplished by making the exoskeleton display active impedance properties. Active impedance control emphasizes control of the exoskeleton’s dynamics and regulation of the transfer of energy between the exoskeleton and the user. Its goal is improving the dynamic response of the human limbs without sacrificing the user’s control authority. The proposed method is an alternative to myoelectrical exoskeleton control, which is based on estimating muscle torques from electromyographical (EMG) activity. Implementation of an EMG-based controller is a complex task that involves modeling the user’s musculoskeletal system and requires recalibration. In contrast, active impedance control is less dependent on estimation of the user’s attempted motion, thereby avoiding conflicts resulting from inaccurate estimation. In this paper we also introduce a new form of human assist based on improving the kinematic response of the limbs. Reduction of average muscle torques is a common goal of research in human assist. However, less emphasis has been placed so far on improving the user’s agility of motion. We aim to use active impedance control to attain such effects as increasing the user’s average speed of motion, and improving their acceleration capabilities in order to compensate for perturbations from the environment.

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