Background: It is the purpose of this article to iden-tify and review criteria that rehabilitation technology should meet in order to offer arm-hand training to stroke patients, based on recent principles of motor learning. Methods: A literature search was conducted in PubMed, MEDLINE, CINAHL, and EMBASE (1997–2007). Results: One hundred and eighty seven scientific pa-pers/book references were identified as being relevant. Rehabilitation approaches for upper limb training after stroke show to have shifted in the last decade from being analytical towards being focussed on envi-ronmentally contextual skill training (task-oriented training). Training programmes for enhancing motor skills use patient and goal-tailored exercise schedules and individual feedback on exercise performance. Therapist criteria for upper limb rehabilitation technology are suggested which are used to evaluate the strengths and weaknesses of a number of current technological systems. Conclusion: This review shows that technology for supporting upper limb training after stroke needs to align with the evolution in rehabi-litation training approaches of the last decade. A major challenge for related technological developments is to provide engaging patient-tailored task oriented arm-hand training in natural environments with pa-tient-tailored feedback to support (re) learning of motor skills.

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The work presented in this paper is our first step toward the develop-ment of an exoskeleton for human gait support. The device we foresee should be suitable for assisting walking in paralyzed subjects and should be based on myoelectrical muscular signals (EMGs) as a communi-cation channel between the human and the machine. This paper concentrates on the design of a biomechanical model of the human lower extremity. The system predicts subject’s intentions from the analysis of his/her electromyographical activity. Our model takes into account three main factors. Firstly, the main muscles spanning the knee articulation. Secondly, the gravity affecting the leg during its movement. Finally, it considers the limits within which the leg swings. Furthermore, it is capable of estimating several knee parameters such as joint moment, angular acceleration, angular velocity, and angular position. In order to have a visual feedback of the predicted movements we have implemented a three-dimensional graphical simulation of a human leg which moves in response to the commands computed by the model.

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If a teleoperation scenario foresees complex and fine manipulation tasks a multi-fingered telemanipulation system is required. In this paper a multi-fingered telemanipulation system is presented, whereby the human hand controls a three-finger robotic gripper and force feedback is provided by using an exoskeleton. Since the human hand and robotic grippers have different kinematic structures, appropriate mappings for forces and positions are applied. A point-to-point position mapping algorithm as well as a simple force mapping algorithm are presented and evaluated in a real experimental setup.

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An exoskeleton interface apparatus includes five rigid links (2-6) arranged in series, capable of rotating reciprocally at the respective ends for monitoring angular movements of the arm, of the forearm and the wrist of an user (60) and having at the tip an handgrip (30) for engaging with the user (60) by reflecting a force feedback. The rigid links (2-6) can rotate at their ends about rotational joints (11-14) having rotational axes (31-34) incident in the intersection point of the physiological axes of the shoulder. The rotational joints (11-14) are brought into rotation about the respective rotational axes (31-34) by means of respective motors (21-24), for example servo-motor such as torque motors. All the motors (21-24) are mounted on the fixed base link (2) in order to minimize the mass of the parts in movement and the inertia reflected on the user (60). A plurality of idle pulleys (50) is provided, spatially arranged for orienting the tendons (41-44), which brake the free movement of the relative rotational joint, responsive to signals corresponding to constraints on the slave in case of teleoperation or to constraints created by virtual reality systems.

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This paper presents the results of a clinical trial employing the PERCRO L-Exos (Light-Exoskeleton) system, which is a 5-DoF force-feedback exoskeleton for the right arm, for robotic-assisted rehabilitation. The device has demonstrated itself suitable for robotic arm rehabilitation therapy when integrated with a Virtual Reality (VR) system. Three different schemes of therapy in VR have been tested in the clinical evaluation trial, which was conducted at the Santa Chiara Hospital in Pisa with nine chronic stroke patients. The results of this clinical trial, both in terms of patients performance improvements in the proposed exercises and in terms of improvements in the standard clinical scales which have been used to monitor patients progresses will be reported and discussed throughout the paper. It is to be noted that statistically significant improvements have been demonstrated in terms of Fugl-Meyer scores, Ashworth scale and increments of active and passive ROMs on shoulder, elbow and wrist joints of the impaired limb.

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