Development of a Wearable Upper Limb Rehabilitation Robot Based on Reinforced Soft Pneumatic Actuators

Dyskinesia of the upper limbs caused by stroke,sports injury,or trafc accidents limits the ability to perform the activities of daily living.Besides the necessary medical treatment,correct and scientifc rehabilitation training for the injured joint is an important auxiliary means during the treatment of the efected upper limb.Conventional upperlimb rehabilitation robots have some disadvantages,such as a complex structure,poor compliance,high cost,and poor portability.In this study,a novel soft wearable upper limb rehabilitation robot(SWULRR)with reinforced soft pneumatic actuators(RSPAs)that can withstand high pressure and featuring excellent loading characteristics was developed.Driven by RSPAs,this portable SWULRR can perform rehabilitation training of the wrist and elbow joints.In this study,the kinematics of an SWULRR were analyzed,and the force and motion characteristics of RSPA were studied experimentally.The results provide a reference for the development and application of wearable upper limb rehabilitation robots.An experimental study on the rotation angle of the wrist and the pressure of the RSPA was conducted to test the efect of the rehabilitation training and verify the rationality of the theoretical model.The process of wrist rehabilitation training was tested and evaluated,indicating that SWULRR with RSPAs will enhance the fexibility,comfort,and safety of rehabilitation training.This work is expected to promote the development of wearable upper-limb rehabilitation robots based on modular reinforced soft pneumatic actuators.

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.

Adaptive neural tracking control for upper limb rehabilitation robot with output constraints

The authors investigate the trajectory tracking control problem of an upper limb reha-bilitation robot system with unknown dynamics.To address the system's uncertainties and improve the tracking accuracy of the rehabilitation robot,an adaptive neural full-state feedback control is proposed.The neural network is utilised to approximate the dy-namics that are not fully modelled and adapt to the interaction between the upper limb rehabilitation robot and the patient.By incorporating a high-gain observer,unmeasurable state information is integrated into the output feedback control.Taking into consider-ation the issue of joint position constraints during the actual rehabilitation training process,an adaptive neural full-state and output feedback control scheme with output constraint is further designed.From the perspective of safety in human–robot interaction during rehabilitation training,log-type barrier Lyapunov function is introduced in the output constraint controller to ensure that the output remains within the predefined constraint region.The stability of the closed-loop system is proved by Lyapunov stability theory.The effectiveness of the proposed control scheme is validated by applying it to an upper limb rehabilitation robot through simulations.

A new active rehabilitation training mode for upper limbs based on Tai Chi Pushing Hands

Robot-assisted rehabilitation is a crucial approach to restoring motor function in the limb.However,the current training trajectory lacks sufficient theoretical or practical support,and the monotony of single-mode training is a concern.Tai Chi Pushing Hands,a beneficial and effective daily exercise,has been shown to improve balance function,psychological state,and motor function of the upper extremities in patients recovering from stroke.To address these issues,we propose a new active rehabilitation training that incorporates Tai Chi Pushing Hands movements and yin-yang balance principles.The training trajectory and direction are encoded by the velocity field and consist of two processes:yang(push)and yin(return).During yang,the limb actively pushes the robot to move,while during yin,the limb actively follows the robot’s movement.To provide necessary assistance,an admittance controller with self-adaptive parameters is designed.In addition,we introduce two indexes,the‘Intention Angle’(ϖ)and the time ratio(Γ),to evaluate motion perception performance.Our experiment was conducted on a 4-degree-of-freedom upper limb rehabilitation robot platform,and the subjects were separated into a familiar group and an unfamiliar group.The experiment results show that the training could be completed well no matter whether the subject is familiar with Tai Chi Pushing Hands or not.The parameters and the movement of the robot can be adjusted based on the interactive force to adapt to the ability of the subject.

Cable-Driven Parallel Robot Workspace Identification and Optimal Design Based on the Upper Limb Functional Rehabilitation

An assessment of the human motion repeatability for three selected Activities of Daily Living(ADL)is performed in this paper.These exercises were prescribed by an occupational therapist for the upper limb rehabilitation.The movement patterns of five participants,recorded using a Qualisys motion capture system,are compared based on the Analysis of Variance(ANOVA)method.This survey is motivated by the need to find the appropriate task workspace of a 6-degrees of freedom cable-driven parallel robot for upper limb rehabilitation,which is able to reproduce the three selected exercises.This comparison is performed to justify,whether or not,there is enough similarity between the participants’gestures,and so a single reference trajectory can be adopted as the robot-prescribed workspace.Using the results of the comparative study,an optimization process of the sought robot design is carried out,where the structure size and the cable tensions simultaneously minimized.

All-Fabric Bi-directional Actuators for Multi-joint Assistance of Upper Limb

According to clinical studies,upper limb robotic suits are vital to reduce therapist fatigue and accelerate patient rehabilitation.Soft pneumatic actuators have drawn increasing attention for the development of wearable robots due to their low weight,flexibility,and high power-to-weight ratio.However,most of current actuators were designed for the flexion assistance of a specific joint,and that for joint extension requires further investigation.Furthermore,designing an actuator for diverse working scenarios remains a challenge.In this paper,we propose an all-fabric bi-directional actuator to assist the flexion and extension of the elbow,wrist,and fingers.A mathematical model is presented that predicts the deformation and guides the design of the proposed bi-directional actuator.To further validate the applicability and adaptability of the proposed actuator for different joints,we developed a 3-DOF soft robotic suit.Preliminary results show that the robotic suit can assist the motion of the elbow,wrist,and finger of the subject.

Safety Protection Method of Rehabilitation Robot Based on fNIRS and RGB-D Information Fusion

In order to improve the safety protection performance of the rehabilitation robot,an active safety protection method is proposed in the rehabilitation scene.The oxyhemoglobin concentration information and RGB-D information are combined in this method,which aims to realize the comprehensive monitoring of the invasion target,the patient’s brain function movement state,and the joint angle in the rehabilitation scene.The main focus is to study the fusion method of the oxyhemoglobin concentration information and RGB-D information in the rehabilitation scene.Frequency analysis of brain functional connectivity coefficient was used to distinguish the basic motion states.The human skeleton recognition algorithm was used to realize the angle monitoring of the upper limb joint combined with the depth information.Compared with speed and separation monitoring,the protection method of multi-information fusion is safer and more comprehensive for stroke patients.By building the active safety protection platform of the upper limb rehabilitation robot,the performance of the system in different safety states is tested,and the safety protection performance of the method in the upper limb rehabilitation scene is verified.

Impedance learning adaptive super-twisting control of a robotic exoskeleton for physical human-robot interaction

This study addresses two issues about the interaction of the upper limb rehabilitation robot with individuals who have disabilities.The first step is to estimate the human's target position(also known as TPH).The second step is to develop a robust adaptive impedance control mechanism.A novel Non-singular Terminal Sliding Mode Control combined with an adaptive super-twisting controller is being developed to achieve this goal.This combination's purpose is to provide high reliability,continuous performance tracking of the system's trajectories.The proposed adaptive control strategy reduces matched dynamic uncertainty while also lowering chattering,which is the sliding mode's most glaring issue.The proposed TPH is coupled with adaptive impedance control with the use of a Radial Basis Function Neural Network,which allows a robotic exoskeleton to simply track the desired impedance model.To validate the approach in real-time,an exoskeleton robot was deployed in controlled experimental circumstances.A comparison study has been set up to show how the adaptive impedance approach proposed is better than other traditional controllers.