Field Of Rehabilitation Robotics Research Articles

Research of intent recognition in rehabilitation robots: a systematic review

Purpose Rehabilitation robots with intent recognition are helping people with dysfunction to enjoy better lives. Many rehabilitation robots with intent recognition have been developed by academic institutions and commercial companies. However, there is no systematic summary about the application of intent recognition in the field of rehabilitation robots. Therefore, the purpose of this paper is to summarize the application of intent recognition in rehabilitation robots, analyze the current status of their research, and provide cutting-edge research directions for colleagues. Materials and Methods Literature searches were conducted on Web of Science, IEEE Xplore, ScienceDirect, SpringerLink, and Medline. Search terms included “rehabilitation robot”, “intent recognition”, “exoskeleton”, “prosthesis”, “surface electromyography (sEMG)” and “electroencephalogram (EEG)”. References listed in relevant literature were further screened according to inclusion and exclusion criteria. Results In this field, most studies have recognized movement intent by kinematic, sEMG, and EEG signals. However, in practical studies, the development of intent recognition in rehabilitation robots is limited by the hysteresis of kinematic signals and the weak anti-interference ability of sEMG and EEG signals. Conclusions Intent recognition has achieved a lot in the field of rehabilitation robotics but the key factors limiting its development are still timeliness and accuracy. In the future, intent recognition strategy with multi-sensor information fusion may be a good solution.

Research on control method of upper limb exoskeleton based on mixed perception model

AbstractAs one of the research hotspots in the field of rehabilitation robotics, the upper limb exoskeleton robot has been widely used in the field of rehabilitation. However, the existing methods cannot comprehensively and accurately reflect the motion state of patients, which may lead to overtraining and secondary injury of patients in the process of rehabilitation training. In this paper, an upper limb exoskeleton control method based on mixed perception model of motion intention and intensity is proposed, which is based on the 6 degree-of-freedom upper limb rehabilitation exoskeleton in the laboratory. First, the kinematic information and heart rate information in the rehabilitation process of patients are collected, corresponding to patients’ motion intention and motion intensity, and fused to obtain the mixed perception vector. Second, the motion perception model based on long short-term memory neural network is established to realize the prediction of upper limb motion trajectory of patients and compared with back-propagation neural network to prove its effectiveness. Finally, the control system is built, and both offline and online test of the control method proposed are implemented. The experimental results show that the method can achieve comprehensive motion state perception of patients, realize real-time and accurate prediction trajectory according to human motion intention and intensity. The average prediction accuracy is 95.3%, and predicted joint angle error is less than 5 degrees. Therefore, the control method based on mixed perception model has good robustness and universality, which provides a new method for the active control of upper limb exoskeleton.

EMG-Driven Machine Learning Control of a Soft Glove for Grasping Assistance and Rehabilitation

In the field of rehabilitation robotics, transparent, precise and intuitive control of hand exoskeletons still represents a substantial challenge. In particular, the use of compliant systems often leads to a trade-off between lightness and material flexibility, and control precision. In this letter, we present a compliant, actuated glove with a control scheme to detectthe user’s motion intent, which is estimated by a machine learning algorithm based on muscle activity. Six healthy study participants used the glove in three assistance conditions during a force reaching task. The results suggest that active assistance from the glove can aid the user, reducing the muscular activity needed to attain a medium-high grasp force, and that closed-loop control of a compliant assistive glove can successfully be implemented by means of a machine learning algorithm.

Using proposed optimization algorithm for solving inverse kinematics of human upper limb applying in rehabilitation robotic

The requirement to solve the problem of Inverse Kinetics (IK) plays a very important role in the robotics field in general, and especially in the field of rehabilitation robots, in particular. If the solutions of this problem are not suitable, it can cause undesirable damage to the patient when exercising. Normally, the problem of Inverse Kinematics in the robotics field, as well as the natural field, especially for redundant driven systems, often requires the application of a lot of techniques. The redundancy in Degree of Freedom (DoF), the nonlinearity of the system leads to solve inverse kinematics problem more challenge. In this study, we proposed to apply the self-adaptive control parameters in Differential Evolution with search space improvement (Pro-ISADE) to solve the problem for the human upper limb, which is a very typical redundancy model in nature. First of all, the angles of the joints were measured by a proposed Exoskeleton type Human Motion Capture System (E-HMCS) when the wearer performs some Activities of Daily Living (ADL) and athletic activities. The values of these measured angles joints then were put into the forward kinematics model to find the end effector trajectories. After having these orbits, they were re-fed into the proposed Pro-ISADE algorithm mentioned above to process the IK problem and obtain the predicted joints angular values. The experimental results showed that the predicted joints’ values closely follow the measured joints’ values. That demonstrates the ability to apply the Pro-ISADE algorithm to solve the problem of Inverse Kinetics of the human upper limb as well as the upper limb rehabilitation robot arm.

Bibliometric analysis on international cooperation of rehabilitation robots in China from 2000 to 2019

Rapid development is undergoing in the field of rehabilitation robots, and more countries (regions) are participating in international cooperation and becoming academic contributors. Here in this study, the bibliometric method is used to determine the dynamics and developments of international cooperation in China. The publication data are indexed in Web of Science with search term of rehabilitation robot from 2000 to 2019. Compared with other countries (regions), publication with international co-authors and institutes participating in international cooperation are studied by assessment of indicators such as the cooperation degree, cooperation frequency, and the frequency of citations. The results show that in the past two decades, international scientific cooperation has shown a positive tendency in China, and participating in international collaboration could improve China's impact on the global rehabilitation robot. The United States, England and Japan are the top three countries in number of cooperation with China. Our findings provide valuable information for researchers to better understand China's international scientific collaboration in rehabilitation robot.

Online Natural Myocontrol of Combined Hand and Wrist Actions Using Tactile Myography and the Biomechanics of Grasping.

Objective: Despite numerous recent advances in the field of rehabilitation robotics, simultaneous, and proportional control of hand and/or wrist prostheses is still unsolved. In this work we concentrate on myocontrol of combined actions, for instance power grasping while rotating the wrist, by only using training data gathered from single actions. This is highly desirable since gathering data for all possible combined actions would be unfeasibly long and demanding for the amputee.Approach: We first investigated physiologically feasible limits for muscle activation during combined actions. Using these limits we involved 12 intact participants and one amputee in a Target Achievement Control test, showing that tactile myography, i.e., high-density force myography, solves the problem of combined actions to a remarkable extent using simple linear regression. Since real-time usage of many sensors can be computationally demanding, we compare this approach with another one using a reduced feature set. These reduced features are obtained using a fast, spatial first-order approximation of the sensor values.Main results: By using the training data of single actions only, i.e., power grasp or wrist movements, subjects achieved an average success rate of 70.0% in the target achievement test using ridge regression. When combining wrist actions, e.g., pronating and flexing the wrist simultaneously, similar results were obtained with an average of 68.1%. If a power grasp is added to the pool of actions, combined actions are much more difficult to achieve (36.1%).Significance: To the best of our knowledge, for the first time, the effectiveness of tactile myography on single and combined actions is evaluated in a target achievement test. The present study includes 3 DoFs control instead of the two generally used in the literature. Additionally, we define a set of physiologically plausible muscle activation limits valid for most experiments of this kind.

Soft Rehabilitation and Nursing-Care Robots: A Review and Future Outlook

Rehabilitation and nursing-care robots have become one of the prevalent methods for assistant treatment of motor disorder patients in the field of medical rehabilitation. Traditional rehabilitation robots are mostly made of rigid materials, which significantly limits their application for medical rehabilitation and nursing-care. Soft robots show great potential in the field of rehabilitation robots because of their inherent compliance and safety when they interact with humans. In this paper, we conduct a systematic summary and discussion on the soft rehabilitation and nursing-care robots. This study reviews typical mechanical structures, modeling methods, and control strategies of soft rehabilitation and nursing-care robots in recent years. We classify soft rehabilitation and nursing-care robots into two categories according to their actuation technology, one is based on tendon-driven actuation and the other is based on soft intelligent material actuation. Finally, we analyze and discuss the future directions and work about soft rehabilitation and nursing-care robots, which can provide useful guidance and help on the development of advanced soft rehabilitation and nursing-care robots.

A Semi-passive Planar Manipulandum for Upper-Extremity Rehabilitation.

Robotic rehabilitation is a promising approach to treat individuals with neurological or orthopedic disorders. However, despite significant advancements in the field of rehabilitation robotics, this technology has found limited traction in clinical practice. A key reason for this issue is that most robots are expensive, bulky, and not scalable for in-home rehabilitation. Here, we introduce a semi-passive rehabilitation robot (SepaRRo) that uses controllable passive actuators (i.e., brakes) to provide controllable resistances at the end-effector over a large workspace in a manner that is cost-effective and safe for in-home use. We also validated the device through theoretical analyses, hardware experiments, and human subject experiments. We found that by including kinematic redundancies in the robot's linkages, the device was able to provide controllable resistances to purely resist the movement of the end-effector, or to gently steer (i.e., perturb) its motion away from the intended path. When testing these capabilities on human subjects, we found that many of the upper-extremity muscles could be selectively targeted based on the forcefield prescribed to the user. These results indicate that SepaRRo could serve as a low-cost therapeutic tool for upper-extremity rehabilitation; however, further testing is required to evaluate its therapeutic benefits in patient population.

Low-Profile Two-Degree-of-Freedom Wrist Exoskeleton Device Using Multiple Spring Blades

Robotically assisted rehabilitation therapy, which is therapy performed using a robotic device that guides or assists motion and in some cases triggered by a biological signal (such as a myoelectric signal or brain signal) is effective in recovering motor function following impairment. In the field of rehabilitation robots and human support robot, exoskeleton robots have been widely studied both for upper and lower limbs. Applying the exoskeleton to a wrist joint remains challenging because the wrist has two degrees of freedom in a structure smaller than the structures of other upper and lower limb joints and the center of rotation moves according to motion owing to the complex anatomical structure. To tackle this problem, we developed a wrist exoskeleton mechanism that consists of two elastic elements that largely deform during motion in transmitting forces from two linear actuators implemented on the user's forearm and in transforming the forces to wrist flexion/extension and adduction/abduction. The advantages of the presented device are the device's compactness, low weight, and inherent flexibility due to the elastic structure. The present letter presents an overview of the newly developed wrist exoskeleton mechanism, prototype implementation, and preliminary mechanical evaluations. The technical verification of the exoskeleton revealed the feasibility of generating forces that can generate wrist flexion/extension and adduction/abduction movements.

Design Aspects of a New Device for Ankle Rehabilitation

The ankle joint injuries are very common and their recuperation to fully operational capabilities involves rehabilitation. The existent ankle rehabilitation equipment is simple (like elastic bands, foam rollers) and they allow only simple rehabilitation exercises, which cannot be use safe without the aid of a therapist [1]. Actuated devices are advantageous because they allow many types of exercises on same device, and also they accurate measure forces and angular motions. Thus, the field of rehabilitation robotics is constantly evolving, with novel mechanisms that improve the recovery of the ankle joint. The aim of this paper is to propose a new platform, which can realize a large range of ankle related foot movements. This device can perform plantar flexion/dorsiflexion movements as well as the inversion/eversion movements. A 3D design is presented, as well as input angle variation function of output angle.

On Integration of Additive Manufacturing During the Design and Development of a Rehabilitation Robot: A Case Study

The field of rehabilitation robotics has emerged to address the growing desire to improve therapy modalities after neurological disorders, such as a stroke. For rehabilitation robots to be successful as clinical devices, a number of mechanical design challenges must be addressed, including ergonomic interactions, weight and size minimization, and cost–time optimization. We present additive manufacturing (AM) as a compelling solution to these challenges by demonstrating how the integration of AM into the development process of a hand exoskeleton leads to critical design improvements and substantially reduces prototyping cost and time.

Design and Characterization of a Small-Scale Magnetorheological Damper for Tremor Suppression

This paper explores the design methodology and effectiveness of small-scale magnetorheological dampers (MRDs) in applications that require variable damping. Previously, applications of MRD have been chiefly limited to vehicle shock absorbers and seismic vibration attenuators. There has been recent biomedical interest in active-damping technology, however, particularly in the field of rehabilitation robotics. The topic at hand is the feasibility of developing MRDs that would be functionally and cosmetically adequate for actuation of an upper limb tremor suppression orthosis. A Bingham plastic model is used to determine MRD's functional characteristics, and experimental data are presented to validate the mathematical model. The feasibility of applying the developed small-scale MRDs to attenuation of tremorous motion is explored.

New Horizons for Robot-Assisted Therapy in Pediatrics

The field of rehabilitation robotics has grown substantially during the past 15 yrs. Studies of upper limb robot-assisted therapy for adults with moderate to severe hemiparesis after stroke have shown significant gains compared with usual care in isolated control, coordination, and strength in the paretic arm (J Rehabil Res Dev 2006;43:171-84; Top Stroke Rehabil 2007;14:22-44; Neurorehabil Neural Repair 2008;22:111-21). While attempts to increase the understanding of the key active ingredients of these interventions continue, researchers have recently extended their focus to children with neurologically based movement disorders arising from cerebral palsy and acquired brain injury or stroke. This study's aim was to provide a narrative review that highlights recent pediatric studies of robot-assisted therapies for the upper and lower limbs. Potential benefits will be discussed, as well as challenges and needs for future development.

Localization and control of a rehabilitation mobile robot by close human-machine cooperation.

In the field of rehabilitation robotics, a mobile personal robot represents an attractive solution, especially in economic terms in comparison with a desktop workstation. A manipulator arm mounted on a mobile robot can facilitate the restoration of the disabled user's manipulative function. In order both to encourage the person to participate in the task at hand and to be cost effective, close human-machine cooperation is essential. The person controls the robot via a remote station and develops strategies to successfully carry out a mission. The main problems encountered by the person during the execution of a mission are electing to change modes, and the mode transition itself. We have examined two aspects of this cooperation: 1) information exchange between human and machine for decision-making and 2) giving to operators complementary and redundant modes to command the system. An experiment has been conducted to study these two aspects. This paper focuses on the control of robot movements in an indoor environment and especially on localization parameters, human-like robot behavior, and the value of proposing complementary control modes to the operator.

Evaluation of a robotic workstation for the disabled

Experience with potential users is vital at all stages of the design of equipment for the disabled, not least in the field of rehabilitation robotics. The development of a robotic workstation for the disabled has progressed, over a period of 6 years, from the use of a cheap educational arm, to a specially engineered robot arm and workstation. The design and specification has been refined through constant evaluation by disabled users. Trials at a spinal injuries unit have given approval to the design and appearance of the latest robot arm and workstation, and have led to modifications to the user interface and software. Further trials have taken place in a user's home to investigate in greater depth the usefulness of a robotic workstation in a practical situation. The results of these trials are presented. It is proposed to refine the design of the arm for low-volume production, easy maintenance in the field and improved appearance.