Upper-limb Rehabilitation Robot Research Articles

Event-triggered adaptive control for upper-limb robot-assisted passive rehabilitation exercises with input delay

In this article, an adaptive tracking control strategy is designed for uncertain electrically driven end-effector type upper-limb rehabilitation robots subject to an input delay and a limited bandwidth channel. This control scheme is implemented to perform upper-limb passive rehabilitation training for different subjects. Primarily, dynamic analysis of the rehabilitation robot is carried out using the Euler–Lagrange principle, which incorporates motor dynamics to allow the voltage-based control commands as desirable in practical implementations. Thereafter, an adaptive backstepping control law with input delay compensation is designed to estimate the unknown dynamical parameters of the rehabilitation robot during the training sessions. Furthermore, a Lyapunov-based triggering mechanism is developed to deal with the limited bandwidth challenge and reduce the transmissions over the network. The experimental validation is conducted for different scenarios, and a comparison study is carried out with two time-triggered control schemes to investigate the potential of the proposed approach. From the experimental runs and the comparative analysis, the proposed control scheme is found to achieve a promising tracking performance with input delay compensation. Moreover, a significant saving in the network resources is attained during the passive rehabilitation training of the subjects.

Investigation of 2DOF PID Controller for Physio-Therapeutic Application for Elbow Rehabilitation

The aim of this work is to evaluate the output of a two-degree of freedom (DOF) proportional integral derivative (PID) controller for controlling elbow flexion and extension on an upper limb rehabilitation robot of an existing model. Since the usage of upper limb rehabilitation is increasing dramatically because of human impairment, 2DOF has been proposed in this work as a suitable controller. The 2DOF PID controller offers set-point-weight features and, hence, is fast in removing disturbance from the system and ensuring system stability. Importantly, as the system parameters are unknown in this work, the black-box model approach has been taken into consideration, using the MATLAB System identification toolbox to estimate a model. The best-fitted estimated model is then coupled with the proposed controller in the MATLAB/Simulink environment that, upon successful simulation works, leads, finally, to the hardware implementation. Three different amplitudes of sinusoidal current signals, such as 0.3 amps, 0.2 amps, and 0.1 amps, are applied for hardware measurements. Considering patients’ physical conditions. In this work, the 2DOF controller offers a fast transient response, settling time, negligible tracking error and 0% overshoot and undershoot.

Upper-Limb Muscle Synergy Features in Human-Robot Interaction with Circle-Drawing Movements.

The upper-limb rehabilitation robots can be developed as an efficient tool for motor function assessments. Circle-drawing has been used as a specific task for robot-based motor function measurement. The upper-limb movement-related kinematic and kinetic parameters measured by motion and force sensors embedded in the rehabilitation robots have been widely studied. However, the muscle synergies characterized by multiple surface electromyographic (sEMG) signals in upper limbs during human-robot interaction (HRI) with circle-drawing movements are rarely investigated. In this research, the robot-assisted and constrained circle-drawing movements for upper limb were used to increase the consistency of muscle synergy features. Both clockwise and counterclockwise circle-drawing tasks were implemented by all healthy subjects using right hands. The sEMG signals were recorded from six muscles in upper limb, and nonnegative matrix factorization (NMF) analysis was utilized to obtain muscle synergy information. Both synergy pattern and activation coefficient were calculated to represent the spatial and temporal features of muscle synergies, respectively. The results obtained from the experimental study confirmed that high structural similarity of muscle synergies was found among the subjects during HRI with circle-drawing movement by healthy subjects, which indicates healthy people may share a common underlying muscle control mechanism during constrained upper-limb circle-drawing movement. This study indicates the muscle synergy analysis during the HRI with constrained circle-drawing movement could be considered as a task for upper-limb motor function assessment.

Impedance learning control for physical human-robot cooperative interaction

In this paper, three challenges often encountered when upper limb rehabilitation robots are integrated with impaired people are addressed. Firstly, estimation of Desired Intended Motion (DIM) of the robot’s wearer is achieved. Secondly, robust adaptive impedance control based on the Modified Function Approximation Technique (MFAT) is designed. Lastly, a new Integral Nonsingular Terminal Sliding Mode Control (INTSMC) is suggested. In particular, the integration of INTSMC enriches the system by ensuring continuous performance tracking of system’s trajectories, high robustness, fast transient response, finite-time convergence, and chattering reduction. Besides, the MFAT strategy approximates the dynamic model without collecting any prior knowledge of the lower and upper bounds of the dynamic model’s individual uncertainties. Furthermore, leveraging Radial Basis Function Neural Network (RBFNN) to link estimated DIM to the adaptive impedance control allows the upper limb robot to easily track the target impedance model. Finally, in efforts to validate the scheme in real-time, controlled experimental cases are conducted using the exoskeleton robot.

Quantitative Assessment of Motor Function by an End-Effector Upper Limb Rehabilitation Robot Based on Admittance Control

Various rehabilitation robots have been developed to assist the movement training of the upper limbs of stroke patients, among which some have been used to evaluate the motor recovery. However, how to understand the recovery of motor function from the quantitative assessment following robot-assisted rehabilitation training is still not clear. The objective of this study is to propose a quantitative assessment method of motor function based on the force and trajectory characteristics during robotic training to reflect motor functional recovery. To assist stroke patients who are not able to move voluntarily, an assistive training mode was developed for the robot-assisted rehabilitation system based on admittance control. Then, to validate the relationship between characteristic information and functional recovery, a clinical experiment was conducted, in which nine stroke patients and nine healthy subjects were recruited. The results showed a significant difference in movement range and movement smoothness during trajectory tracking tasks between stroke patients and healthy subjects. The two parameters above have a correlation with the Fugl-Meyer Assessment for Upper Extremity (FMU) of the involved patients. The multiple linear regression analysis showed FMU was positively correlated with parameters (R2=0.91,p<0.005). This finding indicated that the above-mentioned method can achieve quantitative assessment of motor function for stroke patients during robot-assisted rehabilitation training, which can contribute to promoting rehabilitation robots in clinical practice.

Design and Development of an Upper Limb Rehabilitative Robot with Dual Functionality.

The design of an upper limb rehabilitation robot for post-stroke patients is considered a benchmark problem regarding improving functionality and ensuring better human–robot interaction (HRI). Existing upper limb robots perform either joint-based exercises (exoskeleton-type functionality) or end-point exercises (end-effector-type functionality). Patients may need both kinds of exercises, depending on the type, level, and degree of impairments. This work focused on designing and developing a seven-degrees-of-freedom (DoFs) upper-limb rehabilitation exoskeleton called ‘u-Rob’ that functions as both exoskeleton and end-effector types device. Furthermore, HRI can be improved by monitoring the interaction forces between the robot and the wearer. Existing upper limb robots lack the ability to monitor interaction forces during passive rehabilitation exercises; measuring upper arm forces is also absent in the existing devices. This research work aimed to develop an innovative sensorized upper arm cuff to measure the wearer’s interaction forces in the upper arm. A PID control technique was implemented for both joint-based and end-point exercises. The experimental results validated both types of functionality of the developed robot.

Robust control of a cable-driven rehabilitation robot for lower and upper limbs

In this research, a redundant cable-driven robust rehabilitation robot has been proposed for helping and automating the proper function of the patient’s lower and upper limbs in the presence of uncertainties, disturbances, noise, and time delay using a new control algorithm to derive the best tracking with the least deviations. A new joint limit avoidance path-planning method is exerted while maintaining the bounds of upper and lower angles. Also, a new robust motion controller, namely computed-torque-like controller with a variable-structure compensator was applied to the system and compared with computed-torque controller outputs. Thus, showing the efficiency of the mentioned control algorithm in the presence of uncertainties, disturbances, noise, and time delay and its superior performance and robustness in spatial motions are the goals of this paper as well as taking advantage of a new path-planning approach.Firstly, the kinematic formulation of the cables is obtained. Then, a joint limit avoidance theory is used to apply upper and lower bounds for the joint angles. In the next step, Lagrangian dynamic equations for the 3D motions are derived. Subsequently, the positive and unilateral tension conditions in cable-driven systems are applied using null-space solutions. To have precise tracking and robustness with the existence of uncertainties, disturbances, noise, and time delay, a computed-torque control and robust computed-torque-like controller with a variable-structure compensator are utilized for the system. Stability analyses of the controllers are presented and the obtained results are compared for tracking a spatial reference trajectory.Ultimately, this controller witnessed an improvement in the lower limb with the existence of uncertainties and disturbances in terms of the robustness of the given method about 19.5 percent, and in cable forces about 17.1 percent. Improvements for the tracking errors and the control inputs were 10.8 and 7.3 percent in the presence of noise, and 7.3 and 8.6 percent in the presence of the time delay respectively. Similar results were obtained for the upper limb with 21 percent improvement in control inputs and 21.1 percent improvement in tracking performance respectively.

Evaluation of an upper limb robotic rehabilitation program on motor functions, quality of life, cognition, and emotional status in patients with stroke: a randomized controlled study.

This study aims to find out whether including robotic therapy in addition to a conventional rehabilitation program affects the quality of life, motor function, cognition, and emotional status of hemiplegic patients. Thirty-seven stroke patients recruited between April 2016 and April 2019 were included in the study. The patients were randomized into 2 groups (Robotic rehabilitation group-RR n:17, Control group n:20), RR was arranged to be 30-45min, 5days per week for 4weeks. All patients were assessed at the beginning of therapy and the end of 4th week with Brunnstrom stages of motor recovery, Fugl-Meyer Assessment (FMA), handgrip strength, Purdue peg test, Minnesota manual dexterity test, Modified Ashworth Scale (MAS), Functional Independence Measure (FIM), Stroke Specific Quality of Life Scale (SS-QOL), Nottingham Extended Activities of Daily Living (NEADL) Scale, Montreal Cognitive Assessment (MoCA) and Center for Epidemiological Studies Depression Scale (CES- D). Improvements in motor function scores, spasticity, general functioning, activities of daily living, cognitive assessment were better in the robotic group when compared to the control group but this difference was not statistically significant (p > 0.05). Improvement in the CES-D in the RR-group was better in comparison to the control group (p = 0.018). Improvements in motor functions were observed after the treatment in both groups. Although RR group improved better in numbers, none of the outcomes except the CES-D scale were significant. Robotic rehabilitation provides a favorable alternative bringing slight benefits, and also is advantageous in terms of work power and psychological recovery, making its addition to conventional neurological rehabilitation effective and useful in patient management after stroke. ClinicalTrials.gov Identifier: NCT04393480.

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.

Mechatronic Design of a Robot for Upper Limb Rehabilitation at Home

This paper addresses the design of a novel bionic robotic device for upper limb rehabilitation tasks at home. The main goal of the design process has been to obtain a rehabilitation device, which can be easily portable and can be managed remotely by a professional therapist. This allows to treat people also in regions that are not easily reachable with a significant cost reduction. Other potential benefits can be envisaged, for instance, in the possibility to keep social distancing while allowing rehabilitation treatments even during a pandemic spread. Specific attention has been devoted to design the main mechatronic components by developing specific kinematics and dynamics models. The design process includes the implementation of a specific control hardware and software. Preliminary experimental tests are reported to show the effectiveness and feasibility of the proposed design solution.

Effect of Upper Limb Rehabilitation Robot Therapy on Functional Recovery in Children With Upper Limb Movement Disorder: A Meta-analysis and Systematic Review

Effect of Upper Limb Rehabilitation Robot Therapy on Functional Recovery in Children With Upper Limb Movement Disorder: A Meta-analysis and Systematic Review

Task-Based Design Approach: Development of a Planar Cable-Driven Parallel Robot for Upper Limb Rehabilitation

This paper deals with the optimal design of a planar cable-driven parallel robot (CDPR), with three degrees of freedom, intended for assisting the patient’s affected upper limb along a prescribed movement. A Qualisys motion capture system was used to record the prescribed task performed by a healthy subject. For each pose taken by the center of mass of the end-effector, the cable tensions, the elastic stiffness and the dexterity were optimized while satisfying a set of constraints. First, a multiobjective formulation of the optimization problem was adopted. Since selecting a single solution among the multiple ones given by the Pareto front presents an issue, a mono-objective formulation was chosen, where the objective function was defined as a weighted sum of the chosen criteria. The appropriate values of the weighted coefficients were studied with the aim of identifying their influence on the optimization process and, thus, a judicious choice was made. A prototype of the optimal design of the CDPR was developed and validated experimentally on the prescribed workspace using the position control approach for the motors. The tests showed promising reliability of the proposed design for the task.

Design and evaluation of a novel upper limb rehabilitation robot with space training based on an end effector

Abstract. The target of this paper is to design a lightweight upper limb rehabilitation robot with space training based on end-effector configuration and to evaluate the performance of the proposed mechanism. In order to implement this purpose, an equivalent mechanism to the human being upper limb is proposed before the design. Then, a 4 degrees of freedom (DOF) end-effector-based upper limb rehabilitation robot configuration is designed to help stroke patients perform space rehabilitation training of the shoulder flexion/extension and adduction/abduction and elbow flexion/extension. Thereafter, its kinematical model is established together with the proposed equivalent upper limb mechanism. The Monte Carlo method is employed to establish their workspace. The results show that the overlap of the workspace between the proposed mechanism and the equivalent mechanism is 96.61 %. In addition, this paper also constructs a human–machine closed-chain mechanism to analyze the flexibility of the mechanism. According to the relative manipulability and manipulability ellipsoid, the highly flexible area of the mechanism accounts for 67.6 %, and the mechanism is far away from the singularity on the drinking trajectory. In the end, the single-joint training experiments and a drinking water training trajectory planning experiment are developed and the prototype is manufactured to verify it.

Design and Implementation of BCI-based Intelligent Upper Limb Rehabilitation Robot System

The present study aimed to use the proposed system to measure and analyze brain waves of users to allow intelligent upper limb rehabilitation and to optimize the system using a genetic algorithm. The study used EPOC Neuroheadset for Emotiv with EEG electrodes attached as a non-invasive method for measuring brain waves. The brain waves were measured according to the EEG 10-20 standard electrode layout, which allows measurement of signals from each spot where electrodes are attached based on EEG characteristics. The measured data were added in a database. In the intelligent neuro-fuzzy model, wave transform was used for extracting brain wave characteristics according to user intentions and to eliminate noise from the signals in an effort to increase reliability. Moreover, to construct the option rules of the neuro-fuzzy system, FCM technique and optimal cluster evaluation method were used. Furthermore, the asymmetric Gaussian membership function was used to improve performance, whereas SD and WF divided into left and right sides were used to express the chromosomes. Optimal EEG electrode locations were found, and comparative analysis was performed on the differences based on membership function, number of clusters, and number of learning generations, learning algorithm, and wavelet settings. The performance evaluation results showed that the optimal EEG electrode locations were F7, F8, FC5, and FC6, whereas the accuracy of learning and test data of user-intention recognition was found to be 94.2% and 92.3%, respectively, which suggests that the proposed system can be used to recognize user intention for specific behavior. The system proposed in the present study can allow continued rehabilitation exercise in everyday living according to user intentions, which is expected to help improve the user's willingness to participate in rehabilitation and his or her quality of life.

Serotonin Levels and Cognitive Recovery in Patients with Subacute Stroke after Rehabilitation Treatment.

Post-stroke depression and cognitive impairment are common conditions affecting patients after stroke. Serotonin is a neurotransmitter involved in modulating, among others, mood, cognition, learning, and memory. Sub-optimal serotonin activity may be in part responsible for cognitive deficits seen in depression. In this pilot study serotonin levels were evaluated in 29 patients with sub-acute stroke before and after a rehabilitation treatment (consisting of a program of upper limb robotic rehabilitation in addition to conventional physical therapy treatment). We employed the Back Depression Inventory scale to evaluate symptoms of depression, and specific tools to evaluate cognitive functions. We found a significant reduction of the serotonin levels after rehabilitation in the whole group (T0: 85.9 ± 92.4 ng/mL; T1: 61.9 ± 58.4 ng/mL; p = 0.0018), as well as in the subgroup of patients untreated with Selective Serotonin Reuptake Inhibitors (SRRI), (mean serotonin at T0: 154.0 ± 102.3 ng/mL; mean serotonin at T1: 92.9. ± 68.7 ng/mL at T1; p = 0.005). We also found a correlation with cognitive assessment: in particular, the change from baseline of the serotonin (ΔSerotonin) was correlated with the changes from baseline of the Rey’s Figure (ΔROCF) (r = 0.535; p < 0.05), the Tower of London (ΔToL) (subscore point: r = 0.621; p < 0.005; subscore time: r = −0.619; p < 0.005) meaning that a serotonin levels decrease is associated with a worsening of cognitive functions. Considering patients treated and untreated with SSRIs separately, in patients treated with SSRIs (n = 16) we found only a positive correlation between ∆Serotonin and ∆ToL (subscore point: r= 0.587; p = 0.045), whereas in patients untreated with SSRIs (n = 13) we found a positive correlations between ΔSerotonin and ΔROCF (r = 0.700; p = 0.036), ∆Stroop (subscore time: r = 0.750; p = 0.020) and ∆Tol (subscore point: r = 0.740; p = 0.023) and a negative correlation between ΔSerotonin and ∆Tol (subscore time: r= −0.833; p = 0.005). These results suggest that variation of serotonin levels should be monitored in patients during a rehabilitation program, not only for their relationship with depression symptoms, but also for the correlation with cognitive performance.

Influence of Cognitive Impairment on the Recovery of Subjects with Subacute Stroke Undergoing Upper Limb Robotic Rehabilitation.

Cognitive decline is often present in stroke survivors, with a significant impact on motor recovery. However, how specific cognitive domains could impact motor recovery after robotic rehabilitation in patients with stroke is still not well understood. In this study, we analyzed the relationship between cognitive impairment and the outcome of a robot-mediated upper limb rehabilitation intervention in a sample of 51 subacute stroke patients. Participants were enrolled and treated with a set of robotic and sensor-based devices. Before the intervention, patients underwent a cognitive assessment by means of the Oxford Cognitive Screen. To assess the effect of the 30-session rehabilitation intervention, patients were assessed twice with the following outcome measures: the Fugl-Meyer Assessment for Upper Extremity (FMA-UE), to evaluate motor function; the Upper limb Motricity Index (MI), to evaluate upper limb muscle strength; the Modified Barthel Index (mBI), to evaluate activities of daily living and mobility. We found that deficits in spatial attention and executive functions impacted the mBI improvement, while language, number processing, and spatial attention deficits reduced the gains in the FMA-UE. These results suggest the importance to evaluate the cognitive functions using an adequate tool in patients with stroke undergoing a robotic rehabilitation intervention.

Design and control of a cable-driven rehabilitation robot for upper and lower limbs

AbstractThe design and control of a cable-driven rehabilitation robot, which can be configured easily for exercising different articulations such as elbows, shoulders, hips, knees and ankles without requiring any orthosis, are introduced. The passive, active-assisted and active-resisted exercises were designed and implemented using impedance control. The controller could switch between exercises according to the force feedback. The effectiveness of the proposed controller was demonstrated by experimental studies. The robot was tested first with a dummy extremity and then with a healthy subject mimicking various types of patients during the tests. Experimental results showed that satisfactory closed-loop performances were achieved.

DEVELOPMENT AND ANALYSIS OF A BILATERAL END-EFFECTER UPPER LIMB REHABILITATION ROBOT

Studies have shown that rehabilitation training with the unaffected side guiding affected side is more consistent with the natural movement pattern of human upper limb compared with unilateral rehabilitation training, which is conducive to improve rehabilitation effect of the affected limb motor function. In this paper, a bilateral end-effector upper limb rehabilitation robot (BEULRR) based on two modern commercial manipulators is developed first, then the kinematics, reachability, and dexterity analysis of BEULRR are performed, respectively. Finally, a bilateral symmetric training protocol with the unaffected side guiding the affected side is proposed and evaluated through healthy human subject experiment testing based on BEULRR. The simulation results show that the developed BEULRR could perform spatial rehabilitation training and its rehabilitation training workspace can fully cover the physiological workspace of human upper limb. The preliminary experiment results from the healthy human subject show that the BEULRR system could provide reliable bilateral symmetric training protocol. These simulation and experiment results demonstrated that the developed BEULRR system could be used in bilateral rehabilitation training application, and also show that the BEULRR system has the potential to be applied to clinical rehabilitation training in the further step. In the close future, the proposed BEULRR and bilateral symmetric training protocol are planned to be applied in elderly volunteers and patients with upper limb motor dysfunction for further evaluating.

Effects of passive and active training modes of upper-limb rehabilitation robot on cortical activation: a functional near-infrared spectroscopy study.

The purpose of this study is to investigate the cortical activation during passive and active training modes under different speeds of upper extremity rehabilitation robots. Twelve healthy subjects completed the active and passive training modes at various speeds (0.12, 0.18, and 0.24 m/s) for the right upper limb. The functional near-infrared spectroscopy (fNIRS) was used to measure the neural activities of the sensorimotor cortex (SMC), premotor cortex (PMC), supplementary motor area (SMA), and prefrontal cortex (PFC). Both the active and passive training modes can activate SMC, PMC, SMA, and PFC. The activation level of active training is higher than that of passive training. At the speed of 0.12 m/s, there is no significant difference in the intensity of the two modes. However, at the speed of 0.24 m/s, there are significant differences between the two modes in activation levels of each region of interest (ROI) (P < 0.05) (SMC: F = 8.90, P = 0.003; PMC: F = 8.26, P = 0.005; SMA: F = 5.53, P = 0.023; PFC: F = 9.160, P = 0.003). This study mainly studied on the neural mechanisms of active and passive training modes at different speeds based on the end-effector upper-limb rehabilitation robot. Slow, active training better facilitated the cortical activation associated with cognition and motor control.See Video Abstract, http://links.lww.com/WNR/A621.

Configuration Design of an Upper Limb Rehabilitation Robot with a Generalized Shoulder Joint

For stroke patients with upper limb motor dysfunction, rehabilitation training with the help of rehabilitation robots is a social development trend. Existing upper limb rehabilitation robots have difficulty fully fitting the complex motion of the human shoulder joint and have poor human–robot compatibility. In this paper, based on the anatomical structure of the human upper limb, an equivalent mechanism model of the human upper limb is established. The configuration synthesis of the upper limb rehabilitation mechanism was carried out, a variety of shoulder joint man–machine closed-chain Θs and shoulder elbow human–machine closed-chain Θse configuration combinations were synthesized, and the configuration model with compatibility and reduced moment conduction attenuation was selected from them. Two configurations, 2Pa1P3Ra and 5Ra1P, are proposed for the generalized shoulder joint mechanism of the robot. The closed-chain kinematic models of the two configurations are established, and the velocity Jacobian matrix is obtained. Motion performance analysis, condition reciprocal analysis and operability ellipsoid analysis of different configuration design schemes were carried out in different operation planes. The results show that in the normal upper limb posture of the human body, the 5Ra1P configuration of the shoulder joint has better kinematic performance. Finally, on this basis, an upper limb rehabilitation robot prototype with good human–computer compatibility is developed, and its moving space was verified.