Upper-limb Exoskeleton Research Articles

Design and Analysis of a Novel Shoulder Exoskeleton Based on a Parallel Mechanism

Power-assisted upper-limb exoskeletons are primarily used to improve the handling efficiency and load capacity. However, kinematic mismatch between the kinematics and biological joints is a major problem in most existing exoskeletons, because it reduces the boosting effect and causes pain and long-term joint damage in humans. In this study, a shoulder augmentation exoskeleton was designed based on a parallel mechanism that solves the shoulder dislocation problem using the upper arm as a passive limb. Consequently, the human–machine synergy and wearability of the exoskeleton system were improved without increasing the volume and weight of the system. A parallel mechanism was used as the structural body of the shoulder joint exoskeleton, and its workspace, dexterity, and stiffness were analyzed. Additionally, an ergonomic model was developed using the principle of virtual work, and a case analysis was performed considering the lifting of heavy objects. The results show that the upper arm reduces the driving force requirement in coordinated motion, enhances the load capacity of the system, and achieves excellent assistance.

Structure design and analysis of upper limb wearable passive power-assisted exoskeleton robot

The upper limb exoskeleton robot has been a key research direction at home and abroad in recent years. Still, the existing upper limb exoskeleton robot has poor coupling with the human body, and the power assistance effect could be better. In this paper, the strength of each muscle group of the upper limb when the human body is carrying objects is measured as reflected by the surface EMG signal of the human body, and the human kinematics is analyzed to guide the design of the passive exoskeleton robot of the upper limb. First, the spring tension and compression system model is established for the upper limb of the human body. The model is statically analyzed, the forces and moments on each joint are calculated, and each muscle’s actual output data when carrying objects is estimated. Based on the muscle kinematics model, a passive upper limb exoskeleton robot is designed. The robot is divided into three modules, namely, the arm module, shoulder module, and back module, using ergonomics and modular design ideas. The energy storage module and joint degree of freedom of the exoskeleton are analyzed to ensure that the exoskeleton meets the requirements of ergonomics, and the key components are checked and simulated. The results show that the designed upper limb wearable passive power-assisted exoskeleton robot meets the strength requirements, which verifies the rationality of the structure design.

Research on configuration design and intelligent compliance control of reconfigurable modular flexible upper limb rehabilitation robot

The upper limb exoskeleton rehabilitation robot can realize the partial functional compensation of upper limb and complete the various types of rehabilitation training for each joint of upper limb. However, the existing upper limb exoskeleton rehabilitation robots are lack of flexible reconfigurability, which are difficult to meet the diversified patient objects and rehabilitation needs, and have some problems, such as insufficient motion compliance, poor portability, and wearing comfort. To effectively solve the above problems and improve the effect of upper limb rehabilitation training, this project plans to carry out the following research: Firstly, analyze the structural characteristic and movement mechanism of upper limb, clarify the configuration theory of the modular flexible upper limb exoskeleton rehabilitation robot with reconfigurable, and design and optimize the mechanism form and structural parameters of the reconfigurable modular flexible upper limb exoskeleton rehabilitation robot. Secondly, based on the perspective of rigid–flexible coupling integration of bone–muscle–robot, the integrated equivalent mechanism model is constructed and the integrated dynamics model is established to plan compliance motion and develop intelligent compliance control strategy. Finally, the simulation experimental platform is built for simulation experimental demonstration of upper limb rehabilitation training. The implementation of this study will provide new idea and method for realizing the effect of flexible, compliance, light, and comfortable of upper limb rehabilitation training.

A Trade-Off between Complexity and Interaction Quality for Upper Limb Exoskeleton Interfaces.

Exoskeletons are among the most promising devices dedicated to assisting human movement during reeducation protocols and preventing musculoskeletal disorders at work. However, their potential is currently limited, partially because of a fundamental contradiction impacting their design. Indeed, increasing the interaction quality often requires the inclusion of passive degrees of freedom in the design of human-exoskeleton interfaces, which increases the exoskeleton's inertia and complexity. Thus, its control also becomes more complex, and unwanted interaction efforts can become important. In the present paper, we investigate the influence of two passive rotations in the forearm interface on sagittal plane reaching movements while keeping the arm interface unchanged (i.e., without passive degrees of freedom). Such a proposal represents a possible compromise between conflicting design constraints. The in-depth investigations carried out here in terms of interaction efforts, kinematics, electromyographic signals, and subjective feedback of participants all underscored the benefits of such a design. Therefore, the proposed compromise appears to be suitable for rehabilitation sessions, specific tasks at work, and future investigations into human movement using exoskeletons.

A Wearable Upper Limb Exoskeleton for Intuitive Teleoperation of Anthropomorphic Manipulators

Teleoperation technology combines the strength and accuracy of robots with the perception and cognition abilities of human experts, allowing the robots to work as an avatar of the operator in dangerous environments. The motion compatibility and intuitiveness of the human–machine interface directly affect the quality of teleoperation. However, many motion capture methods require special working environments or need bulky mechanisms. In this research, we proposed a wearable, lightweight, and passive upper limb exoskeleton, which takes intuitiveness and human-machine compatibility as a major concern. The upper limb pose estimation and teleoperation mapping control methods based on the exoskeleton are also discussed. Experimental results showed that by the help of the upper limb exoskeleton, people can achieve most areas of the normal range of motion. The proposed mapping control methods were verified on a 14-DOF anthropomorphic manipulator and showed good performance in teleoperation tasks.

Design methodology of portable upper limb exoskeletons for people with strokes.

OPINION article Front. Neurosci., 16 March 2023Sec. Neural Technology Volume 17 - 2023 | https://doi.org/10.3389/fnins.2023.1128332

Glenohumeral joint trajectory tracking for improving the shoulder compliance of the upper limb rehabilitation robot.

Exoskeletons have become an important tool to help patients with upper extremity motor dysfunction in rehabilitation training and life assistance. In the study of the upper limb exoskeleton, the human glenohumeral joint will produce accompanying movement during the movement of the shoulder joint. This phenomenon causes a positional deviation between the shoulder joint and the exoskeleton, which affects the accuracy of exoskeleton-assisted human movement and the wearing comfort. Spend. Taking the coronal adduction and abduction of the shoulder joint as the research object, the shoulder joint angle and glenohumeral joint bony motion trajectory were fitted by bi-level X-rays, and then the Ultium Motion motion capture system was used to collect the characteristic motion of the shoulder joint surface and establish a model. A back-propagation neural network with shoulder joint motion and shoulder width as input and the coronal position of the glenohumeral joint as output, finally applied the model to the Nimbot exoskeleton upper limb rehabilitation training robot to verify the effectiveness of the algorithm. Real-time prediction of the glenohumeral joint motion trajectory was achieved, and the human-machine coupling compliance during the wearing of the upper limb exoskeleton was improved.

Volitional control of upper-limb exoskeleton empowered by EMG sensors and machine learning computing

Volitional control of upper-limb exoskeleton empowered by EMG sensors and machine learning computing

Design and Verification of Lockable Upper-Limb Exoskeleton Based on Jamming and Engagement Mechanisms

This letter presents a lockable upper-limb exoskeleton to reduce the physical fatigue of laborers/surgeons operating with upper limbs maintaining fixed posture for long time. A novel structure design integrating the jamming and engagement mechanisms that can provide locking of flexion and adduction movements of upper arm without affecting the motion space is proposed. An air-pressure waist bag with a voice control interface is developed, giving good portability and user convenience to the exoskeleton. The system is validated in experiments, indicating a locking torque as large as 6 Nm with 3.5 bar air pressure. Locking and unlocking settling times of the jamming mechanism are 0.09 s and 0.10 s, meaning nearly no delay can be felt by users for the switching. Moreover, surface electromyography (EMG) signal tests demonstrate that the proposed exoskeleton can significantly reduce muscle activation of randomly selected subjects by 25%--73%. Compared with commercially-available passive exoskeletons, proposed system has a lower weight, much larger and adjustable locking torque owing to the specially designed jamming mechanism. The exoskeleton presents good compliance, great flexibility, and hands free human-machine interface, showing good potential for physical fatigue reduction of laborers/surgeons over long-term operations.

Evaluation of a Passive Upper Limb Exoskeleton in Healthcare Workers during a Surgical Instrument Cleaning Task.

(1) Background: Healthcare workers are highly affected by work-related musculoskeletal disorders, particularly in the lower back, neck and shoulders, as their occupational tasks expose them to biomechanical constraints. One solution to prevent these musculoskeletal disorders may be the use of a passive exoskeleton as it aims to reduce muscle solicitation. However, few studies have been carried out directly in this field to assess the impact of the use of a passive upper limb exoskeleton on this population. (2) Methods: Seven healthcare workers, equipped with electromyographic sensors, performed a tool cleaning task with and without a passive upper limb exoskeleton (Hapo MS, Ergosanté Technologie, France). Six muscles of the upper limbs were analysed, i.e., anterior deltoid, biceps brachii, pectoralis major, latissimus dorsi, triceps brachii and longissimus thoracis. A subjective analysis of the usability of the equipment, the perception of effort and discomfort, was also carried out using the System Usability Scale and the Borg scale. (3) Results: The longissimus thoracis was the most used muscle during this task. We observed a significant decrease in the muscular solicitation of the anterior deltoid and latissimus dorsi when wearing the exoskeleton. Other muscles were not significantly impacted by the device. (4) Conclusions: the passive exoskeleton used in this study allowed the reduction in muscular load on the anterior deltoid and latissimus dorsi without negative effects on other muscles. Other field studies with exoskeletons are now necessary, particularly in hospitals, to increase our knowledge and improve the acceptability of this system for the prevention of musculoskeletal disorders.

Single Lead EMG signal to Control an Upper Limb Exoskeleton Using Embedded Machine Learning on Raspberry Pi

Post-stroke can cause partial or complete paralysis of the human limb. Delayed rehabilitation steps in post-stroke patients can cause muscle atrophy and limb stiffness. Post-stroke patients require an upper limb exoskeleton device for the rehabilitation process. Several previous studies used more than one electrode lead to control the exoskeleton. The use of many electrode leads can lead to an increase in complexity in terms of hardware and software. Therefore, this research aims to develop single lead EMG pattern recognition to control an upper limb exoskeleton. The main contribution of this research is that the robotic upper limb exoskeleton device can be controlled using a single lead EMG. EMG signals were tapped at the biceps point with a sampling frequency of 2000 Hz. A Raspberry Pi 3B+ was used to embed the data acquisition, feature extraction, classification and motor control by using multithread algorithm. The exoskeleton arm frame is made using 3D printing technology using a high torque servo motor drive. The control process is carried out by extracting EMG signals using EMG features (mean absolute value, root mean square, variance) further extraction results will be trained on machine learning (decision tree (DT), linear regression (LR), polynomial regression (PR), and random forest (RF)). The results show that machine learning decision tree and random forest produce the highest accuracy compared to other classifiers. The accuracy of DT and RF are of 96.36±0.54% and 95.67±0.76%, respectively. Combining the EMG features, shows that there is no significant difference in accuracy (p-value 0.05). A single lead EMG electrode can control the upper limb exoskeleton robot device well.

Model-free super-twisting terminal sliding mode controller using sliding mode disturbance observer for n-DOF upper-limb rehabilitation exoskeleton with backlash hysteresis

This paper proposes a model-free super-twisting terminal sliding mode controller (MF-STTSMC) for the n-DOF upper-limb rehabilitation exoskeleton in the presence of external disturbance and backlash hysteresis. This ultra-local model-based control scheme consists of a sliding mode disturbance observer (SMDO) and a super-twisting non-singular fast terminal sliding mode controller (ST-NFTSMC). The ultra-local model is used to approximate the origin complex exoskeleton system in a short sliding time window, which avoids the requirement for accurate modelling and decreases the difficulty of controller design. To compensate for the lumped uncertainties, the SMDO is constructed to achieve finite-time observation and zero estimation error. Besides, to realise finite-time convergence of sliding surface and tracking error with less chattering, the ST-NFTSMC is proposed by employing a super-twisting algorithm. Furthermore, the stability of a closed-loop system with MF-STTSMC is ensured by using the Lyapunov theorem. Finally, to validate the proposed strategy, co-simulations of 7-DOF iReHave upper-limb exoskeleton are realised by using SolidWorks, SimMechanics, and Matlab/Simulink. Compared to time-delay estimation-based intelligent proportional-derivative control (TDE-iPD), α-variable adaptive model-free controller (α-AMFC), and inclusive and enhanced time delay controller (IETDC), the higher performances of the proposed MF-STTSMC are demonstrated.

A passive upper-limb exoskeleton reduced muscular loading during augmented reality interactions

The aim of this study was to evaluate a passive upper-limb exoskeleton as an ergonomic control to reduce the musculoskeletal load in the shoulders associated with augmented reality (AR) interactions. In a repeated-measures laboratory study, each of the 20 participants performed a series of AR tasks with and without a commercially-available upper-limb exoskeleton. During the AR tasks, muscle activity (anterior, middle, posterior deltoid, and upper trapezius), shoulder joint postures/moment, and self-reported discomfort were collected. The results showed that the exoskeleton significantly reduced muscle activity in the upper trapezius and deltoid muscle groups and self-reported discomfort. However, the shoulder postures and task performance measures were not affected by the exoskeleton during the AR interactions. Given the significant decrease in muscle activity and discomfort without compromising task performance, a passive exoskeleton can be an effective ergonomic control measure to reduce the risks of developing musculoskeletal discomfort or injuries in the shoulder regions.

AGREE: A Compliant-Controlled Upper-Limb Exoskeleton for Physical Rehabilitation of Neurological Patients

In this work, we introduce the AGREE exoskeleton, a robotic device designed to assist in upper-limb physical rehabilitation for post-stroke survivors. We detail the exoskeleton design at the mechatronic, actuation, and control levels. The AGREE exoskeleton features a lightweight and adaptable mechanical design, which can be used with both the right and left arm, supporting three active degrees-of-freedom at the shoulder and one at the elbow. The device embodies a spring-pulley anti-gravity system to minimize torque requirements and has torque sensors on each joint for safe and smooth interaction with the user. The AGREE control system, which employs a loadcell-based impedance control method, offers various modes of human-robot interaction, such as passive-assisted, active-assisted, and active-resistive exercises. Results from our experimental characterization demonstrate that the exoskeleton is capable of both compliant and rigid behavior, providing a wide range of haptic impedance and transparent behavior to both user-generated and therapist-generated forces. Our findings indicate that the AGREE exoskeleton may be a viable option for safely assisting patients with neurological conditions.

Efficacy of passive upper-limb exoskeletons in reducing musculoskeletal load associated with overhead tasks

Overhead work can pose substantial musculoskeletal stress in many industrial settings. This study aimed to evaluate the efficacy of passive upper-limb exoskeletons in reducing muscular activity and subjective discomfort ratings. In a repeated-measures laboratory experiment, 20 healthy male participants performed 10-min drilling tasks with and without two passive upper-limb exoskeletons (VEX and Airframe). During the tasks, muscle activity in eight muscles (upper limb - upper trapezius, middle deltoid, biceps brachii, triceps brachii; low back - erector spinae; lower limb - rectus femoris, biceps femoris, tibialis anterior) was collected using electromyography as a physical exertion measure. Subjective discomfort rating in six body parts was measured using the Borg's CR-10 scale. The results showed that muscle activity (especially in the upper-limb muscles) was significantly decreased by 29.3–58.1% with both exoskeletons compared to no exoskeleton condition. The subjective discomfort ratings showed limited differences between the conditions. These findings indicate that passive upper-limb exoskeletons may have potential as an effective intervention to reduce muscular loading and physical exertion during overhead work.

Specificity of 3D Printing and AI-Based Optimization of Medical Devices Using the Example of a Group of Exoskeletons

Three-dimensional-printed medical devices are a separate group of medical devices necessary for the development of personalized medicine. The present article discusses a modern and specific group of medical devices and exoskeletons, which aims to present our own experiences in the selection of materials, design, artificial-intelligence optimization, production, and testing of several generations of various upper limb exoskeletons when considering the Medical Devices Regulation (MDR) and the ISO 13485 and ISO 10993 standards. Work is underway to maintain the methodological rigor inherent in medical devices and to develop new business models to achieve cost-effectiveness so that inadequate legislation does not stop the development of this group of technologies (3D scanning, 3D printing, and reverse engineering) in the healthcare system. The gap between research and engineering practice and clinical 3D printing should be bridged as quickly and as carefully as possible. This measure will ensure the transfer of proven solutions into clinical practice. The growing maturity of 3D printing technology will increasingly impact everyday clinical practice, so it is necessary to prepare medical specialists and strategic and organizational changes to realize the correct implementation based on the needs of patients and clinicians.

An Improved Super-Twisting Sliding Mode for Flexible Upper-Limb Exoskeleton

Aiming at the decrease of tracking accuracy caused by nonlinear friction and strong coupling of the flexible upper-limb exoskeleton, an improved super-twisting sliding mode controller (ISTSMC) is proposed. Compared with the conventional super twisted sliding mode controller (STSMC), this method can replace the switching function under the integral term with a nonsmooth term, resulting in a faster response, less vibration when performing trajectory tracking, and reduced steady-state error. The introduction of the nonsmooth term causes the controller to have a stronger anti-interference ability. At the same time, the parameters of the ISTSMC can be adjusted in order to achieve the expected control performance. The effectiveness and feasibility of the proposed control algorithm are verified through experiments.

Position control of electro-hydraulic servo system using active disturbance rejection control for upper-limb exoskeleton

This paper presents a two-degree-of-freedom(2-DOF) upper-limb exoskeleton actuated by electro-hydraulic servo system (EHSS), and position control based on active disturbance rejection control (ADRC) strategy. Proportional integral derivative (PID) controller is widely used in EHSS system because it is model free, and its parameters can be adjusted easily. However, the nonlinear dynamics of EHSS is subject to parameter variations and friction effects during operation. The trajectory tracking performance of this method is limited due to the uncertain model parameter and external disturbance of EHSS in exoskeleton. To actively compensate the total disturbance including the system uncertainty and external disturbance, and ensure the finite time convergence of disturbances, the ADRC controller is developed. The disturbances can be estimated by the extended state observer (ESO) and compensated during each sampling period in the ADRC method. The proposed control strategy not only satisfies the steady-state accuracy demands, but also effectively resists to the system uncertainties and the disturbance. To validate the feasibility of the proposed control strategy, the simulations were carried out. The numerical simulation results clearly indicate the superior performance of proposed ADRC method over the regular PID control approach.

Graded Optimization of Upper Limb Exoskeleton Parts for Grid Operations

Upper limb exoskeleton is gradually used in industrial production because of its flexibility, safety, and ease of wear. To improve the load reduction effect of the upper limb exoskeleton in power grid operation, this paper first establishes an efficiency optimization model considering the number of gears, transmission ratio, and pressure angle of upper limb exoskeleton transmission joint gears. Further, an exoskeleton load reduction model based on the joint optimization of multiple parameters of the upper limb exoskeleton is constructed by combining the muscle force application fatigue evaluation. For the above model, a hybrid simulated annealing-flash connection process algorithm based on Cubic mapping and golden sine is designed for the solution. To address the shortcomings of the standard LAPO, Cubic mapping, simulated annealing algorithm, and golden sine operator are introduced for improvement, producing high-quality initial solutions through the traversal of Cubic chaotic sequences, hybrid simulated annealing algorithm to enhance the global search capability of the algorithm, and further incorporating golden sine operator to strengthen the local search capability of the algorithm. In the simulation section, the designed Improved Lightning Connection Process Algorithm (ILAPO) is compared horizontally with cutting-edge swarm intelligence algorithms such as LAPO, PSO, and HBA to verify the feasibility of the model in this paper in the exoskeleton domain and the efficiency of the designed algorithm.

A Self-Aligning Upper-Limb Exoskeleton Preserving Natural Shoulder Movements: Kinematic Compatibility Analysis.

NESM- γ is an upper-limb exoskeleton to train motor functions of post-stroke patients. Based on the kinesiology of the upper limb, the NESM- γ includes a four degrees-of-freedom (DOF) active kinematic chain for the shoulder and elbow, along with a passive chain for self-aligning robotic joint axes with the glenohumeral (GH) joint's center of rotation. The passive chain accounts for scapulohumeral rhythm and trunk rotations. To assess self-aligning performance, we analyzed the kinematic and electromyographic data of the shoulder in eight healthy subjects performing reaching tasks under three experimental conditions: moving without the exoskeleton (baseline), moving while wearing the exoskeleton with the passive DOFs properly functioning, i.e., unlocked (human-in-the-loop(HIL)-unlocked), and with the passive DOFs locked (HIL-locked). Comparison of baseline and HIL-unlocked conditions showed nearly unchanged anatomical movement patterns, with a root-mean-square error of shoulder angle lower than 5 deg and median deviations of the GH center of rotation below 20 mm. Peak muscle activations showed no significant differences. In contrast, the HIL-locked condition deviated significantly from the baseline, as observed by the trunk and GH trajectory deviations up to 50 mm, accompanied by increased peak muscle activations in the Deltoid and Upper Trapezius muscles. These findings highlight the need for kinematic solutions in shoulder exoskeletons that can accommodate the movements of the entire shoulder complex and trunk to achieve kinematic compatibility.