A Method for measuring the upper limb motion and computing a compatible exoskeleton trajectory

International audienceThis paper deals with the problem of computing trajectories for an exoskeleton that match a motion recorded on a given subject. Literature suggests that this problem can be solved by reconstructing the subject's joint motion using one of the numerous models available, and then feeding the exoskeleton with the joint trajectories. This is founded on the assumption that the exoskeleton kinematics reproduces the human kinematics. In practice, though, mismatches are unavoidable and lead to inaccuracies. We thus developed a method that is primarily based on an appropriate mechanical design: passive mechanisms are used to connect the exoskeleton with splints wore by the subject, in such a way that, within the workspace, there always exists a posture of the exoskeleton compatible with a given position and orientation of the splints. The trajectory computing method, by itself, consists of recording the position and orientation of the splints thanks to a conventional 3D motion tracker and to exploit standard robotics tools in order to compute an exoskeleton posture compatible with the measured human posture. Conclusive experimental results involving an existing 4 DoF upper-limb exoskeleton are shown

A survey of haptics in serious gaming

Serious gaming often requires high level of realism for training and learning purposes. Haptic technology has been proved to be useful in many applications with an additional perception modality complementary to the audio and the vision. It provides novel user experience to enhance the immersion of virtual reality with a physical control-layer. This survey focuses on the haptic technology and its applications in serious gaming. Several categories of related applications are listed and discussed in details, primarily on haptics acts as cognitive aux and main component in serious games design. We categorize haptic devices into tactile, force feedback and hybrid ones to suit different haptic interfaces, followed by description of common haptic gadgets in gaming. Haptic modeling methods, in particular, available SDKs or libraries either for commercial or academic usage, are summarized. We also analyze the existing research difficulties and technology bottleneck with haptics and foresee the future research directions

Robotics rehabilitation of the elbow based on surface electromyography signals

Physical rehabilitation based on robotic systems has the potential to cover the patient’s need of improvement of upper extremity functionalities. In this article, the state of the art of resistant and assistive upper limb exoskeleton robots and their control are thoroughly investigated. Afterward, a single-degree-of-freedom exoskeleton matching the elbow–forearm has been advanced to grant a valid rehabilitation therapy for persons with physical disability of upper limb motion. The authors have focused on the control system based on the use of electromyography signals as an input to drive the joint movement and manage the robotics arm. The correlation analysis between surface electromyography signal and the force exerted by the subject was studied in objects’ grasping tests with the purpose of validating the methodology. The authors developed an innovative surface electromyography force–based active control that adjusts the force exerted by the device during rehabilitation. The control was validated by an experimental campaign on healthy subjects simulating disease on an arm, with positive results that confirm the proposed solution and that open the way to future researches

Positive effects of robotic exoskeleton training of upper limb reaching movements after stroke

This study, conducted in a group of nine chronic patients with right-side hemiparesis after stroke, investigated the effects of a robotic-assisted rehabilitation training with an upper limb robotic exoskeleton for the restoration of motor function in spatial reaching movements. The robotic assisted rehabilitation training was administered for a period of 6 weeks including reaching and spatial antigravity movements. To assess the carry-over of the observed improvements in movement during training into improved function, a kinesiologic assessment of the effects of the training was performed by means of motion and dynamic electromyographic analysis of reaching movements performed before and after training. The same kinesiologic measurements were performed in a healthy control group of seven volunteers, to determine a benchmark for the experimental observations in the patients’ group. Moreover degree of functional impairment at the enrolment and discharge was measured by clinical evaluation with upper limb Fugl-Meyer Assessment scale (FMA, 0–66 points), Modified Ashworth scale (MA, 0–60 pts) and active ranges of motion. The robot aided training induced, independently by time of stroke, statistical significant improvements of kinesiologic (movement time, smoothness of motion) and clinical (4.6 ± 4.2 increase in FMA, 3.2 ± 2.1 decrease in MA) parameters, as a result of the increased active ranges of motion and improved cocontraction index for shoulder extension/flexion. Kinesiologic parameters correlated significantly with clinical assessment values, and their changes after the training were affected by the direction of motion (inward vs. outward movement) and position of target to be reached (ipsilateral, central and contralateral peripersonal space). These changes can be explained as a result of the motor recovery induced by the robotic training, in terms of regained ability to execute single joint movements and of improved interjoint coordination of elbow and shoulder joints

A new robotic exoskeleton system for upper limb rehabilitation by gaze tracking

E' stato condotto lo sviluppo, implementazione e sperimentazione di un sistema innovativo per la riabilitazione dell'arto superiore, basato su un robot esoscheletrico guidato mediante tecniche di gaze tracking. Sono stati ideati, sviluppati e valutati sperimentalmente nuovi algoritmi di controllo per la pianificazione adattiva della traiettoria di un robot esoscheletrico, in grado di fornire all'utente una guida attiva nei compiti di raggiungimento ed afferraggio di oggetti, attraverso la lettura dell'intenzione di movimento del soggetto tramite riconoscimento dello sguardo. Gli algortimi di guida proposti soddisfano i requisiti di sicurezza ed ergonomia dell'applicazione riabilitativa, e sono strutturati per consentire il loro aggiornamento in funzione delle variazioni rilevate nello spazio di lavoro e nel comportamento dell'utente (es. spostamento di target/ostacoli e/o del punto di vista) attraverso un sistema di telecamere ed un dispositivo di eye-tracking indossabile, che sono stati integrati all'interno del sistema robotico

Using Kinect for hand tracking and rendering in wearable haptics

Wearable haptic devices with poor position sensing are combined with the Kinect depth sensor by Microsoft. A heuristic hand tracker has been developed. It allows for the animation of the hand avatar in the virtual reality and the implementation of the force rendering algorithm: the position of the fingertips is measured by the hand tracker designed and optimized for Kinect, and the rendering algorithm computes the contact forces for wearable haptic display. Preliminary experiments with qualitative results show the effectiveness of the idea of combining Kinect and wearable haptics

Machine Learning in Robot Assisted Upper Limb Rehabilitation: A Focused Review

Robot-assisted rehabilitation, which can provide repetitive, intensive and high-precision physics training, has a positive influence on motor function recovery of stroke patients. Current robots need to be more intelligent and more reliable in clinical practice. Machine learning algorithms (MLAs) are able to learn from data and predict future unknown conditions, which is of benefit to improve the effectiveness of robot-assisted rehabilitation. In this paper, we conduct a focused review on machine learning-based methods for robot-assisted upper limb rehabilitation. Firstly, the current status of upper rehabilitation robots is presented. Then, we outline and analyze the designs and applications of MLAs for upper limb movement intention recognition, human-robot interaction control and quantitative assessment of motor function. Meanwhile, we discuss the future directions of MLAs-based robotic rehabilitation. This review article provides a summary of MLAs for robotic upper limb rehabilitation and contributes to the design and development of future advanced intelligent medical devices