Passive Rehabilitation Research Articles

Design and Control of Two Degrees of Freedom Robot for a Passive Rehabilitation

Design and Control of Two Degrees of Freedom Robot for a Passive Rehabilitation

Design and Control of a Novel 6-DOF Desktop Upper Limb Rehabilitation Robot

Abstract This paper presents the design, analysis, and development of a Novel six degrees of freedom (6-DOF) desktop upper limb rehabilitation robot. The upper limb rehabilitation robot is mainly composed of the Omnidirectional mobile platform, armrest, and 3-DOF wrist rehabilitation mechanism. The forward and inverse kinematics and Jacobian matrix of the upper limb rehabilitation robot are derived based on the kinematics of a rigid body, and its working space is analyzed based on arm kinematics as well. The forward and inverse kinematics of the arm are derived based on the D-H method. A new control strategy and control algorithm were developed based on the hardware structure of the robot system and arm model, and the control strategy and control algorithm are used to carry out the simulated rehabilitation experiment on a single joint of the arm and the simulated rehabilitation experiment on multiple joint linkages in the arm. The experimental results show that the maximum error in the simulated rehabilitation experiment on a single joint of the arm is 6.123 deg, and the maximum error in the simulated rehabilitation experiment of multiple joint linkages in the arm is 5.323 deg. Therefore, the control strategy and control algorithm can complete the corresponding rehabilitation training. This 6-DOF desktop upper limb rehabilitation robot can provide passive rehabilitation training for patients in the early stages of paralysis.

Research and experiment on active training of lower limb based on five-bar mechanism of man-machine integration system

AbstractIn view of the fact that the current research on active and passive rehabilitation training of lower limbs is mainly based on the analysis of exoskeleton prototype and the lack of analysis of the actual movement law of limbs, the human-machine coupling dynamic characteristics for active rehabilitation training of lower limbs are studied. In this paper, the forward and inverse kinematics are solved on the basis of innovatively integrating the lower limb and rehabilitation prototype into a human-machine integration system and equivalent to a five-bar mechanism. According to the constraint relationship of hip joint, knee joint and ankle joint, the Lagrange dynamic equation and simulation model of five-bar mechanism under the constraint of human physiological joint motion are constructed, and the simulation problem of closed-loop five-bar mechanism is solved. The joint angle experimental system was built to carry out rehabilitation training experiments to analyze the relationship between lower limb error and height, weight and BMI, and then, a personalized training planning method suitable for people with different lower limb sizes was proposed. The reliability of the method is proved by experiments. Therefore, we can obtain the law of limb movement on the basis of traditional rehabilitation training, appropriately reduce the training speed or reduce the man-machine position distance and reduce the training speed or increase the man-machine distance to reduce the error to obtain the range of motion angle closer to the theory of hip joint and knee joint respectively, so as to achieve better rehabilitation.

Structural design and research of a novel lower limb rehabilitation robot for human–robot coupling

A bedside rehabilitation robot is developed to address the challenge of motor rehabilitation for patients with lower limb paralysis. Firstly, based on the principles of physical rehabilitation, a two-link planar robot model is used to simulate both the robot and human lower limbs, and the coupling characteristics between the human and robot are thoroughly analyzed. Then, the lower limb rehabilitation robot, fitted with an end-effector and ankle wearable feature, is designed according to the structural parameters. To enhance patient safety during rehabilitation, the device incorporates a freely rotating leg support mechanism that reduces the load on the ankle due to gravitational forces, and a two-stage series elastic mechanism is integrated below the foot support to provide a passive compliant output of robot power, allowing for more natural movement and reducing the risk of injury. Secondly, dynamic modeling is used to determine the dynamic parameters of the robot by conducting simulation calculations based on the inertia parameters of the human body and the robot model design parameters. Finally, an experimental platform is established using the structural and dynamic parameters, and the robot’s reliability is validated through experimentation. Results indicate that the robot can accurately complete passive rehabilitation training tasks, and the dynamic parameters meet the expected requirements.

Current clinical opinion on surgical approaches and rehabilitation of hand flexor tendon injury-a questionnaire study.

The management of flexor tendon injury has seen many iterations over the years, but more substantial innovations in practice have been sadly lacking. The aim of this study was to investigate the current practice of flexor tendon injury management, and variation in practice from the previous reports, most troublesome complications, and whether there was a clinical interest in potential innovative tendon repair technologies. An online survey was distributed via the British Society for Surgery of the Hand (BSSH) and a total of 132 responses were collected anonymously. Results showed that although most surgeons followed the current medical recommendation based on the literature, a significant number of surgeons still employed more conventional treatments in clinic, such as general anesthesia, ineffective tendon retrieval techniques, and passive rehabilitation. Complications including adhesion formation and re-rupture remained persistent. The interest in new approaches such as use of minimally invasive instruments, biodegradable materials and additive manufactured devices was not strong, however the surgeons were potentially open to more effective and economic solutions.

Design and Analysis of VARONE a Novel Passive Upper-Limb Exercising Device

Robots have been widely investigated for active and passive rehabilitation therapy of patients with upper limb disabilities. Nevertheless, the rehabilitation assessment process is often ignored or just qualitatively performed by the physiotherapist implementing chart-based ordinal scales or observation-based measures, which tend to rely on professional experience and lack quantitative analysis. In order to objectively quantify the upper limb rehabilitation progress, this paper presents a noVel pAssive wRist motiOn assessmeNt dEvice (VARONE) having three degrees of freedom (DoFs) based on the gimbal mechanical design. VARONE implements a mechanism of three revolute passive joints with controllable passive resistance. An inertial measurement unit (IMU) sensor is used to quantify the wrist orientation and position, and an encoder module is implemented to obtain the arm positions. The proposed VARONE device can also be used in combination with the previously designed two-DoFs device NURSE (cassiNo-qUeretaro uppeR limb aSsistive dEvice) to perform multiple concurrent assessments and rehabilitation tasks. Analyses and experimental tests have been carried out to demonstrate the engineering feasibility of the intended applications of VARONE. The maximum value registered for the IMU sensor is 36.8 degrees, the minimum value registered is −32.3 degrees, and the torque range registered is around −80 and 80 Nmm. The implemented models include kinematics, statics (F.E.M.), and dynamics. Thirty healthy patients participated in an experimental validation. The experimental tests were developed with different goal-defined exercising paths that the participant had to follow.

Adaptive control for shape memory alloy actuated systems with applications to human-robot interaction.

Shape memory alloy (SMA) actuators are attractive options for robotic applications due to their salient features. So far, achieving precise control of SMA actuators and applying them to human-robot interaction scenarios remains a challenge. This paper proposes a novel approach to deal with the control problem of a SMA actuator. Departing from conventional mechanism models, we attempt to describe this nonlinear plant using a gray-box model, in which only the input current and the output displacement are measured. The control scheme consists of the model parameters updating and the control law calculation. The adaptation algorithm is founded on the multi-innovation concept and incorporates a dead-zone weighted factor, aiming to concurrently reduce computational complexities and enhance robustness properties. The control law is based on a PI controller, the gains of which are designed by the pole assignment technique. Theoretical analysis proves that the closed-loop performance can be ensured under mild conditions. The experiments are first conducted through the Beckhoff controller. The comparative results suggest that the proposed adaptive PI control strategy exhibits broad applicability, particularly under load variations. Subsequently, the SMA actuator is designed and incorporated into the hand rehabilitation robot. System position tracking experiments and passive rehabilitation training experiments for various gestures are then conducted. The experimental outcomes demonstrate that the hand rehabilitation robot, utilizing the SMA actuator, achieves higher position tracking accuracy and a more stable system under the adaptive control strategy proposed in this paper. Simultaneously, it successfully accommodates hand rehabilitation movements for multiple gestures. The adaptive controller proposed in this paper takes into account both the computational complexity of the model and the accuracy of the control results, Experimental results not only demonstrate the practicality and reliability of the controller but also attest to its potential application in human-machine interaction within the field of neural rehabilitation.

Prescribed performance sliding mode control for the PAMs elbow exoskeleton in the tracking trajectory task

PurposeThis study discusses the tracking trajectory issue of the exoskeleton under the bounded disturbance and designs an useful tracking trajectory control method to solve it. By using the proposed control method, the tracking error can be successfully convergence to the assigned boundary. Meanwhile, the chattering effect caused by the actuators is already reduced, and the tracking performance of the pneumatic artificial muscles (PAMs) elbow exoskeleton is improved effectively.Design/methodology/approachA prescribed performance sliding mode control method was developed in this study to fulfill the joint position tracking trajectory task on the elbow exoskeleton driven by two PAMs. In terms of the control structure, a dynamic model was built by conforming to the adaptive law to compensate for the time variety and uncertainty exhibited by the system. Subsequently, a super-twisting algorithm-based second-order sliding mode control method was subjected to the exoskeleton under the boundedness of external disturbance. Moreover, the prescribed performance control method exhibits a smooth prescribed function with an error transformation function to ensure the tracking error can be finally convergent to the pre-designed requirement.FindingsFrom the theoretical perspective, the stability of the control method was verified through Lyapunov synthesis. On that basis, the tracking performance of the proposed control method was confirmed through the simulation and the manikin model experiment.Originality/valueAs revealed by the results of this study, the proposed control method sufficiently applies to the PAMs elbow exoskeleton for tracking trajectory, which means it has potential application in the actual robot-assisted passive rehabilitation tasks.

Assist-as-needed control with a soft robotic glove based on human-object contact estimation

Assist-as-needed control with a soft robotic hand glove for active rehabilitation is studied in this work. There are two resources of the grasping force, the robotic glove and the subject. Compared with traditional passive rehabilitation where the grasping force is merely provided by a robotic hand rehabilitation device (such as hand exoskeleton, robotic glove), assist-as-needed control accounts for the user contribute to performing grasping tasks collaboratively. In this control method, the human muscle strength for grasping is estimated through the myoelectrical signals of the human forearm collected by the MYO armband. A neural network is used for the recognition of human-object contact estimation. The assist-as-needed control is finally implemented to assist humans in grasping tasks. Experiment results on a soft robotic glove show the effectiveness of the proposed assistive control method.

Customized Trajectory Optimization and Compliant Tracking Control for Passive Upper Limb Rehabilitation.

Passive rehabilitation training in the early poststroke period can promote the reshaping of the nervous system. The trajectory should integrate the physicians' experience and the patient's characteristics. And the training should have high accuracy on the premise of safety. Therefore, trajectory customization, optimization, and tracking control algorithms are conducted based on a new upper limb rehabilitation robot. First, joint friction and initial load were identified and compensated. The admittance algorithm was used to realize the trajectory customization. Second, the improved butterfly optimization algorithm (BOA) was used to optimize the nonuniform rational B-spline fitting curve (NURBS). Then, a variable gain control strategy is designed, which enables the robot to track the trajectory well with small human-robot interaction (HRI) forces and to comply with a large HRI force to ensure safety. Regarding the return motion, an error subdivision method is designed to slow the return movement. The results showed that the customization force is less than 6 N. The trajectory tracking error is within 12 mm without a large HRI force. The control gain starts to decrease in 0.5 s periods while there is a large HRI force, thereby improving safety. With the decrease in HRI force, the real position can return to the desired trajectory slowly, which makes the patient feel comfortable.

Imitation Learning-Based System for the Execution of Self-Paced Robotic-Assisted Passive Rehabilitation Exercises

The development of robotic-assisted rehabilitation exercises involving physical human-robot interaction requires extreme care since an injured limb may be in physical contact with the robot, so compliant behavior is imperative for these tasks. Typical approaches involve force control schemes like admittance controllers that allow humans to adapt the motion. However, when the patient's limb has limited mobility or is potentially injured, unintentional forces may occur during the robot's trajectory that could be incompatible with these controllers. This paper addresses a new way of generating compliant trajectories for passive rehabilitation exercises, considering that previous positions of the trajectory are attainable for the patient, so reversing the trajectory is a safe operation. Since there is no clear way to optimize such a goal due to the physiological variability among patients, the condition of reversal is based on imitation learning by taking the analogous healthy limb of the patient as a reference and encoding the forces using Gaussian Mixture Regression, and reversibility is accomplished by means of Reversible Dynamic Movement Primitives. The system allows for self-paced rehabilitation exercises by back-and-forth movements along the trajectory according to the patient's reaction, and it has been successfully applied to a 4-DOF parallel robot for lower-limb rehabilitation.

Complex System Based Automation Technology for Rehabilitation System Research

With the aging of the population in China in recent years, the number of stroke patients is increasing day by day. The sequelae of stroke-induced foot drop are expected to regain some mobility after timely rehabilitation, but if patients do not receive early intervention, they may miss the best rehabilitation period and lose the ability to walk and stand completely. The traditional means of rehabilitation treatment is manual rehabilitation by rehabilitation physicians, but with the increase in the number of patients with movement disorders, the number of rehabilitation physicians has become significantly insufficient. The use of rehabilitation robots to provide adjunctive therapy to patients has become a common and effective means of rehabilitation worldwide. The early rehabilitation robots could only drive the patient to do passive rehabilitation and could not reflect the patient’s true motor intentions. Since EMG signals on the surface of the human body can advance the onset of human movement, they can be used to identify the intention of human movement. This paper validates and explores the experiment based on the underlying data.

PREVENÇÃO E REABILITAÇÃO DE ENTORSE DE TORNOZELO NO TREINAMENTO DE FUTEBOL

ABSTRACT Introduction In soccer training, many impacts in running and defense make ankle sprain a very common sports injury; therefore, prevention and rehabilitation management of ankle sprain is particularly important. Objective Explore the strategy of preventing and rehabilitating ankle sprain in soccer training. Methods 10 athletes with ankle sprain were selected and randomly divided into the experimental and control group. Both groups received rehabilitation training, the control group received only manual therapy, and the experimental group received active and passive rehabilitation management. The indices relevant to ankle rehabilitation were analyzed daily: active extension and flexion angle, in addition to the degree of joint edema. Results By the third day, the experimental group’s recovery rate was significantly higher. By the end of the seventh day, the active plantar flexion angle in the control group was 28.0133, while in the experimental group, it was 32.0512. As for the degree of joint swelling on day 5, the experimental group was 2.2059 and 1.0057 in the control group. The control group only achieved this level of recovery in the experimental group on the seventh day. Conclusion Using comparative analysis, the rehabilitation strategy associated with the active and passive techniques proposed in this article showed a better performance than the traditional protocol. Studies are suggested popularizing rehabilitation combined with active training with passive traction. Level of evidence II; Therapeutic studies - investigation of treatment results.

Nature-Inspired Intelligent Synthesis of a Spherical Mechanism for Passive Ankle Rehabilitation Using Differential Evolution

The ankle rehabilitation in certain injuries requires passive movements to aid in the prompt recovery of ankle movement. In the last years, parallel ankle rehabilitation robots with multiple degrees of freedom have been the most studied for providing such movements in a controlled way. Nevertheless, the high cost does not make it viable for home healthcare. Then, this paper presents an optimization approach where a spherical mechanism of one-degree-of-freedom is proposed as a low-cost ankle rehabilitation device to provide the passive rehabilitation exercise for plantar flexion/dorsiflexion and adduction/abduction ankle movements. The approach is formulated as a mono-objective constraint optimization problem where the relative motion angle of the mechanism, the Grashof criterion, the force transmission, and the rehabilitation routine are included. The link lengths of the mechanism parameterized in Cartesian coordinates are found by the two most representative differential evolution variants. The statistical analysis of optimizers indicates that the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$DE/rand/1/bin$ </tex-math></inline-formula> finds, on average, more promising solutions through algorithm executions than the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$DE/best/1/bin$ </tex-math></inline-formula> . The numerical simulation results and the motion simulation of the CAD model illustrate the obtained ankle rehabilitation mechanism, indicating that the percentage error between the desired rehabilitation path and the curve generated by the coupler point of the mechanism is in the interval <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$[{0.036,0.437}]\%$ </tex-math></inline-formula> . Manufacturing the ankle rehabilitation mechanism with a 3D printer validates the optimization approach and verifies the resulting mechanism.

An End-Effector Type Therapeutic Robot for Home-Based Upper Limb Rehabilitation

<h3>Research Objectives</h3> This research proposes a telerehabilitation framework with a developed desktop-mounted rehabilitation robot (DMRbot) and PTC's Industrial Internet of Things (IIoT) platform to remotely provide home-based passive rehabilitation therapies to individuals with upper limb dysfunctions. <h3>Design</h3> Experimental study. <h3>Setting</h3> In the BioRobotics Lab. <h3>Participants</h3> An experiment provided a passive mode of telerehabilitation to two healthy male human subjects (age: 26-30 years, weights: 70–80 kg, and height: 1.6–1.7 m). <h3>Interventions</h3> While providing robot-aided therapy, rehab robot data (for example, joint angle, torque) and therapists' joystick commands are transported by ThingWorx, which are then processed to get information such as achievement of cures. Participants were seated on a chair, wearing gripper gloves attached to the rehab robot's end-effector. The therapist leveraged the digital twin structure, facilitated by Vuforia studio, to visualize the physical robot motions happening in the remote place. <h3>Main Outcome Measures</h3> We evaluated the device and the ability of the therapist to provide telerehabilitation, meaning how well the patient hand followed the trajectory directed by the therapist remotely. An additional measure was the latency, the time difference between sending joint angle parameters, and the movement of physical joints of the network. <h3>Results</h3> The proposed end-effector type therapeutic robot for home-based upper limb rehabilitation resulted in 100% trajectory movement of the patient's hand, with a network latency of approximately 0.15 seconds. <h3>Conclusions</h3> Therefore, the proposed framework is inclined to make therapies more approachable to remote areas with convenience and affordability. <h3>Author(s) Disclosures</h3> The authors have no conflicts of interest to declare.

An Integrated Programmable CPG With Bounded Output

Cyclic motions are fundamental patterns in robotic applications including industrial manipulation and legged robot locomotion. This paper proposes an approach for the online modulation of cyclic motions in robotic applications. For this purpose, we present an integrated programmable Central Pattern Generator (CPG) for the online generation of the reference joint trajectory of a robotic system out of a library of desired periodic motions. The reference trajectory is then followed by the lower-level controller of the robot. The proposed CPG generates a smooth reference joint trajectory convergence to the desired one while preserving the position and velocity joint limits of the robot. The integrated programmable CPG consists of one novel bounded output programmable oscillator. We design the programmable oscillator for encoding the desired multidimensional periodic trajectory as a stable limit cycle. We also use the state transformation method to ensure that the oscillator's output and its first-time derivative preserve the joint position and velocity limits of the robot. With the help of Lyapunov-based arguments, We prove that the proposed CPG provides the global stability and convergence of the desired trajectory. The effectiveness of the proposed integrated CPG for trajectory generation is shown in a passive rehabilitation scenario on the Kuka iiwa robot arm, and also in a walking simulation on a seven-link bipedal robot.

Flatness tracking control scheme of rehabilitation exoskeleton robot with dynamic uncertainties

Artificial limbs are new robotic devices created to help stroke victims in the rehabilitation process. In this article, we focus our work on applying passive, active or assistive control strategies to provide a physical assistance and rehabilitation by a 7-degree-of-freedom exoskeleton robot with nonlinear uncertain dynamics and unknown bounded external disturbances due to the robot user’s physiological characteristics. The flatness controller combined with time-delay estimation is designed for the 7-degree-of-freedom exoskeleton robot called ETS-MARSE (Ecole de Technologie Supérieure—Motion Assistive Robotic-exoskeleton for Superior Extremity) in order to ensure a passive rehabilitation exercises with a high level of tracking accuracy and robustness against the uncertainty constraints. The stability analysis of such systems is proven using the Lyapunov–Krasovskii functional theory. This approach is illustrated by experimental results with healthy human to highlight the efficiency of the suggested controller scheme.

A novel end-effector upper limb rehabilitation robot: Kinematics modeling based on dual quaternion and low-speed spiral motion tracking control

For patients with upper limb dysfunction after stroke, robot-assisted rehabilitation training plays an important role in functional recovery. The existing upper limb rehabilitation robots have some problems, such as complex mechanisms, insufficient compliance, and can only realize the rehabilitation training of shoulder and elbow joints in the horizontal plane. This research proposes a novel end-effector upper limb rehabilitation robot with three degrees of freedom. Two horizontal rotation freedoms are driven by motors and one vertical translation freedom is driven by a pneumatic cylinder. So it can realize the spatial rehabilitation training of shoulder and elbow joints. The rotation and translation transformation of the robot can be represented by a dual quaternion, which is concise in form and clear in the physical meaning. Therefore, this article adopts dual quaternions to complete the robot’s kinematics modeling, inverse kinematics calculation, and terminal spiral motion trajectory planning. To improve the low-speed moving performance of the spiral motion, a sliding mode control strategy plus feedforward compensation is employed to control the displacement of the cylinder. Experiments show that the robot can realize proximal joints training and has good position tracking accuracy (tracking error is within 2 mm) with smoothness under the proposed control strategy, which can guarantee the accuracy and comfort of passive rehabilitation training, contributing to restoring the function of the impairment upper limbs.

Research on Rehabilitation Training Strategies Using Multimodal Virtual Scene Stimulation.

It is difficult for stroke patients with flaccid paralysis to receive passive rehabilitation training. Therefore, virtual rehabilitation technology that integrates the motor imagery brain-computer interface and virtual reality technology has been applied to the field of stroke rehabilitation and has evolved into a physical rehabilitation training method. This virtual rehabilitation technology can enhance the initiative and adaptability of patient rehabilitation. To maximize the deep activation of the subjects motor nerves and accelerate the remodeling mechanism of motor nerve function, this study designed a brain-computer interface rehabilitation training strategy using different virtual scenes, including static scenes, dynamic scenes, and VR scenes. Including static scenes, dynamic scenes, and VR scenes. We compared and analyzed the degree of neural activation and the recognition rate of motor imagery in stroke patients after motor imagery training using stimulation of different virtual scenes, The results show that under the three scenarios, The order of degree of neural activation and the recognition rate of motor imagery from high to low is: VR scenes, dynamic scenes, static scenes. This paper provided the research basis for a virtual rehabilitation strategy that could integrate the motor imagery brain-computer interface and virtual reality technology.

Multimodal Neural Response and Effect Assessment During a BCI-Based Neurofeedback Training After Stroke.

Stroke caused by cerebral infarction or hemorrhage can lead to motor dysfunction. The recovery of motor function is vital for patients with stroke in daily activities. Traditional rehabilitation of stroke generally depends on physical practice under passive affected limbs movement. Motor imagery-based brain computer interface (MI-BCI) combined with functional electrical stimulation (FES) is a potential active neural rehabilitation technology for patients with stroke recently, which complements traditional passive rehabilitation methods. As the predecessor of BCI technology, neurofeedback training (NFT) is a psychological process that feeds back neural activities online to users for self-regulation. In this work, BCI-based NFT were proposed to promote the active repair and reconstruction of the whole nerve conduction pathway and motor function. We designed and implemented a multimodal, training type motor NFT system (BCI-NFT-FES) by integrating the visual, auditory, and tactile multisensory pathway feedback mode and using the joint detection of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). The results indicated that after 4 weeks of training, the clinical scale score, event-related desynchronization (ERD) of EEG patterns, and cerebral oxygen response of patients with stroke were enhanced obviously. This study preliminarily verified the clinical effectiveness of the long-term NFT system and the prospect of motor function rehabilitation.