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

Design and Development of a Twisted String Exoskeleton Robot for the Upper Limb

High-intensity and task-specific upper-limb treatment of active, highly repetitive movements are the effective approaches for patients with motor disorders. However, with the severe shortage of medical service in the United States and the fact that post-stroke survivors can continue to incur significant financial costs, patients often choose not to return to the hospital or clinic for complete recovery. Therefore, robot-assisted therapy can be considered as an alternative rehabilitation approach because the similar or better results as the patients who receive intensive conventional therapy offered by professional physicians.;The primary objective of this study was to design and fabricate an effective mobile assistive robotic system that can provide stroke patients shoulder and elbow assistance. To reduce the size of actuators and to minimize the weight that needs to be carried by users, two sets of dual twisted-string actuators, each with 7 strands (1 neutral and 6 effective) were used to extend/contract the adopted strings to drive the rotational movements of shoulder and elbow joints through a Bowden cable mechanism. Furthermore, movements of non-disabled people were captured as templates of training trajectories to provide effective rehabilitation.;The specific aims of this study included the development of a two-degree-of-freedom prototype for the elbow and shoulder joints, an adaptive robust control algorithm with cross-coupling dynamics that can compensate for both nonlinear factors of the system and asynchronization between individual actuators as well as an approach for extracting the reference trajectories for the assistive robotic from non-disabled people based on Microsoft Kinect sensor and Dynamic time warping algorithm. Finally, the data acquisition and control system of the robot was implemented by Intel Galileo and XILINX FPGA embedded system

Low obstacles avoidance for lower limb exoskeletons

Gli esoscheletri motorizzati per gli arti inferiori (LLEs) sono robot indossabili che permettono a soggetti con disabilità degli arti inferiori di camminare indipendentemente, e persino migliorare le prestazioni degli arti inferiori nel caso di soggetti sani. Nonostante i recenti sviluppi, l'uso di questa promettente tecnologia è relegato agli ambiti clinici e di ricerca; il suo utilizzo come strumento per camminare in modo indipendente in ambienti non controllati è ancora mancante. Il motivo principale di questa limitazione è dovuto alla mancanza di adattabilità degli LLE ai diversi ambienti che possono essere incontrati durante il cammino: la maggioranza degli LLE sfrutta traiettorie predefinite degli arti inferiori senza valutare l'ambiente circostante. Questo implica che ogni tipo di controllo addizionale è a carico dell'utente, e risulta in un sovraccarico fisico e cognitivo da parte di quest'ultimo. Questa tesi si pone l'obbiettivo di superare le limitazioni sopracitate, proponendo un approccio innovativo per aumentare l'autonomia degli LLE. In particolare, il metodo proposto ha lo scopo di stimare la traiettoria degli arti inferiori ottimale, così da poter superare in modo autonomo gli ostacoli bassi che potrebbero essere incontrati lungo il cammino. Tramite l'uso di una stereo camera unita ad un algoritmo di Computer Vision, l'ambiente viene percepito in modo da identificare il pavimento e gli ostacoli che potrebbero influenzare il cammino con l'obbiettivo di selezionare il punto d'appoggio ottimale per il piede. Successivamente, un algoritmo iterativo per la generazione della traiettoria del piede senza collisioni (CFFTG) permette di ottenere i dati necessari a calcolare la cinematica inversa dell'esoscheletro, ed infine gli angoli ai giunti ottenuti da quest'ultima vengono forniti ai controllori dei motori per effettuare il movimento desiderato. Test sperimentali in simulazione (basati su dati reali) sono stati eseguiti per valutare il comportamento dell'algoritmo di Computer Vision e del CFFTG, mostrando ottimi risultati in diversi scenari. Inoltre, le assunzioni su cui si basa la soluzione proposta permettono la sua compatibilità con la maggioranza degli esoscheletri commerciali e di ricerca attualmente disponibili. Credo che pensare agli esoscheletri come degli agenti semi autonomi, piuttosto che come dei dispositivi controllati unicamente dall'utente, rappresenti non solo un percorso che porterà alla simbiosi tra uomo ed esoscheletro, ma anche all'uso di questa tecnologia nella vita di tutti i giorni.Powered lower limb exoskeletons (LLEs) are innovative wearable robots that allow independent walking in people with severe gait impairments, or even to augment lower limb capabilities of able-bodied users. Despite the recent advancements, the use of this promising technology is still restricted to controlled research/clinical settings; uptake in real-life conditions as a device to promote user independence is still lacking. The main reason behind this limitation can be traced back to the lack adaptability of LLEs to the different walking conditions that may be encountered in real world settings: the majority of LLEs relies on predefined gait trajectories and is generally unaware of the environment in which gait occurs. This means that the control burden is entirely on the user, resulting in an increased physical and cognitive workload. This thesis aims at overcoming the aforementioned limitations by proposing a novel approach to enhance the autonomy of the LLEs. In particular, the proposed method has the purpose of estimating the optimal gait trajectory of the exoskeleton in order to autonomously avoid low obstacles on the ground. By using a depth camera coupled with Computer Vision software module, the environment is sensed to detect the ground plane and obstacles that might interfere with the forward motion, in order to predict the following foothold. Then, an iterative-based collision-free foot trajectory generator (CFFTG) algorithm is proposed to calculate the optimal foot motion and the joints’ angles to be sent to the exoskeleton low-level controllers. Experimental tests have been carried out in simulation to evaluate both the CV module and the CFFTG based on real data, showing successful performance in different scenarios. In addition, the assumptions that have been considered in this work make the proposed approach compatible with the majority of exoskeletons in research and on the market. I believe that re-thinking exoskeletons as semi-autonomous agents will represent not only the cornerstone to promote a more symbiotic human-exoskeleton interaction but may also pave the way for the use of this technology in the everyday life

A New 4-DOF Robot for Rehabilitation of Knee and Ankle-Foot Complex: Simulation and Experiment

Stationary robotic trainers are lower limb rehab robots which often incorporate an exoskeleton attached to a stationary base. The issue observed in the stationery trainers for simultaneous knee and ankle-foot complex joints is that they restrict the natural motion of ankle-foot in the rehab trainings due to the insufficient Degrees of Freedom (DOFs) of these trainers. A new stationary knee-ankle-foot rehab robot with all necessary DOFs is developed here. A typical rehab training is first implemented in simulation, and then tested on a healthy subject. Results show that the proposed system functions naturally and meets the requirements of the desired rehab training.Comment: 23 pages, 14 figure

Physical Diagnosis and Rehabilitation Technologies

The book focuses on the diagnosis, evaluation, and assistance of gait disorders; all the papers have been contributed by research groups related to assistive robotics, instrumentations, and augmentative devices

Physical human-robot collaboration: Robotic systems, learning methods, collaborative strategies, sensors, and actuators

This article presents a state-of-the-art survey on the robotic systems, sensors, actuators, and collaborative strategies for physical human-robot collaboration (pHRC). This article starts with an overview of some robotic systems with cutting-edge technologies (sensors and actuators) suitable for pHRC operations and the intelligent assist devices employed in pHRC. Sensors being among the essential components to establish communication between a human and a robotic system are surveyed. The sensor supplies the signal needed to drive the robotic actuators. The survey reveals that the design of new generation collaborative robots and other intelligent robotic systems has paved the way for sophisticated learning techniques and control algorithms to be deployed in pHRC. Furthermore, it revealed the relevant components needed to be considered for effective pHRC to be accomplished. Finally, a discussion of the major advances is made, some research directions, and future challenges are presented

Biosignal‐based human–machine interfaces for assistance and rehabilitation : a survey

As a definition, Human–Machine Interface (HMI) enables a person to interact with a device. Starting from elementary equipment, the recent development of novel techniques and unobtrusive devices for biosignals monitoring paved the way for a new class of HMIs, which take such biosignals as inputs to control various applications. The current survey aims to review the large literature of the last two decades regarding biosignal‐based HMIs for assistance and rehabilitation to outline state‐of‐the‐art and identify emerging technologies and potential future research trends. PubMed and other databases were surveyed by using specific keywords. The found studies were further screened in three levels (title, abstract, full‐text), and eventually, 144 journal papers and 37 conference papers were included. Four macrocategories were considered to classify the different biosignals used for HMI control: biopotential, muscle mechanical motion, body motion, and their combinations (hybrid systems). The HMIs were also classified according to their target application by considering six categories: prosthetic control, robotic control, virtual reality control, gesture recognition, communication, and smart environment control. An ever‐growing number of publications has been observed over the last years. Most of the studies (about 67%) pertain to the assistive field, while 20% relate to rehabilitation and 13% to assistance and rehabilitation. A moderate increase can be observed in studies focusing on robotic control, prosthetic control, and gesture recognition in the last decade. In contrast, studies on the other targets experienced only a small increase. Biopotentials are no longer the leading control signals, and the use of muscle mechanical motion signals has experienced a considerable rise, especially in prosthetic control. Hybrid technologies are promising, as they could lead to higher performances. However, they also increase HMIs’ complex-ity, so their usefulness should be carefully evaluated for the specific application