This paper deals with the design and the testing of an exoskeleton system able to catch the angular deflections of every phalanges of three fingers. It has to be placed on the back of the human hand, giving the possibility to measure with great precision the rotation of every phalange. The system is composed of a mechanical exoskeleton, working with a micro-encoder like position sensor. A smart unit based on a microprocessor, endowed with a dedicated card, was also designed in order to make the system more compatible with every computer. The system is studied as a standalone device sending and receiving data through the RS232 serial line, and is able to calibrate and to interpret commands by means of dedicated software. This way the system is flexible and precise

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This paper presents design, implementation and control of a 3RPS-R exoskeleton, specifically built to impose targeted therapeutic exercises to forearm and wrist. Design of the exoskeleton features enhanced ergonomy, enlarged workspace and optimized device performance when compared to previous versions of the device. Passive velocity field control (PVFC) is implemented at the task space of the manipulator to provide assistance to the patients, such that the exoskeleton follows a desired velocity field asymptotically while maintaining passivity with respect to external applied torque inputs. PVFC is augmented with virtual tunnels and resulting control architecture is integrated into a virtual flight simulator with force-feedback. Experimental results are presented indicating the applicability and effectiveness of using PVFC on 3RPS-R exoskeleton to deliver therapeutic movement exercises.

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As the operation of robotic systems moves away from solely manufacturing environments to arenas where they must operate alongside humans, so the essential characteristics of their design has transformed. A move from traditional robot designs to more inherently safe concepts is required. Studying biological systems to determine how they achieve safe interactions is one approach being used. This then seeks to mimic the ingredients that make this interaction safe in robotics systems. This is often achieved through softness both in terms of a soft fleshy external covering and through motor systems that introduce joint compliance for softer physical Human-Robot Interaction (pHRI). This has led to the development of new actuators with performance characteristics that at least on a macroscopic level try to emulate the function of organic muscle. One of the most promising among these is the pneumatic Muscle Actuator (pMA). However, as with organic muscle, these soft actuators are more susceptible to damage than many traditional actuators. Whilst organic muscle can regenerate and recover, artificial systems do not possess this ability. This article analyzes how organic muscle is able to operate even after extreme trauma and shows how functionally similar techniques can be used with pMAs.

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Surface electromyogram (SEMG) signal driven exoskeleton system is now gaining more research interests due to the promise of offering a faster response haptic system than the traditional position or force driven exoskeleton system. However, the technology to control and drive the exoskeleton system using myosignal is still not well established. The major problem of implementing the SEMG signal into the system comes from its naturally random and inconsistence properties. This research work investigates the optimal use of SEMG signal acquisition to drive an exoskeleton system. Two major criteria are identified as the essential conditions for the acquired SEMG signal as being suitable for driving an exoskeleton system robustly. Firstly, the magnitudes of measured SEMG signals have to show significant positive changes with increasing of external load. Secondly, the patterns of SEMG signal are required to be consistent for a particular muscle action. The former part of this paper shows some essential procedures for satisfying the first criteria along with the different configurations of the experimental set-up that were performed. The results were compared so as to determine the best settings for the SEMG signal recording in order to obtain the consistent muscle activity measuring in Biceps Brachii and Brachioradialis muscles.

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This paper introduces an exoskeleton assistive hand that supports human hand and wrist activities by using user’s bioelectric potential to control the exoskeleton movement. The exoskeleton has three active joints for an index finger, three active joints for combination of a middle finger, a ring finger and a little finger and two active joints for a thumb. It also has two passive joints between the index finger part and the combined part of the three fingers. Our proposed poly-articular tendon drive mechanism simulates a mechanical compliance of a human finger so that the exoskeleton could realize comfortable and stable grasping. This paper proposes a new mechanism «dual sensing system» and a new control algorithm «bioelectric potential-based switching control» so that the exoskeleton could synchronize wearer’s hand activities without any force sensor. A tendon-driven mechanism and a dual sensing system enable wearer’s fingers to move freely when they does need power assist but precise position control or force control. A bioelectric potential-based switching control enables the exoskeleton to augment their grasping force only when wearer’s fingers generate a relatively large grasping force. A five-parallel-link mechanism is used to assist wrist activities of a wearer. Through experiments it is confirmed that the exoskeleton does not disturb a wear’s pinch of a small object and that it augments grasping force for a heavy work.

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