Rehabilitation Exoskeleton Research Articles

Study and implementation of fluxgate current sensor with wireless connectivity for finger exoskeleton rehabilitation

SummaryA fully integrated fluxgate magnetometer has been developed to monitor motor current in a finger exoskeleton device. The use of a fluxgate sensor can provide more accurate and natural movement of the fingers, as well as reducing the weight and complexity of the exoskeleton design. The sensor we developed incorporates several advanced features that provide enhanced sensitivity and accuracy compared to existing state‐of‐the‐art sensors. These features include a fluxgate frontend readout circuit with chopping stabilization technology, which achieves a gain of 14.3 V/T, a low noise density of 4.5 nT/√Hz, and a wide measurement range of ±1.5 mT. The gain variation of the sensor is only 1.5% at an 850 kHz bandwidth, and it has a wide dynamic current range from 0.005 mA to 100 A. The sensor also features an integrated 2.4 GHz wireless circuit for easy data transmission. The use of a fluxgate sensor in monitoring motor torque in the proximal interphalangeal joint can provide more precise and natural finger movement and reduce the weight and complexity of the exoskeleton design.

Towards meaningful community ambulation in individuals post stroke through use of a smart hip exoskeleton: a preliminary investigation

ABSTRACT Stroke is the leading cause of long-term disability in the United States, leaving survivors with profound mobility challenges that impact independent community ambulation. Evidence shows assistance at the hip during walking may be beneficial for stroke survivors. In this cross-over design study, we examine the impact of a novel hip exoskeleton on both functional and patient reported outcomes measuring speed, fall risk, gait symmetry, energy expenditure and perceived walking ability during both indoors and outdoors in single and serial counting dual task paradigms. Nine ambulatory stroke survivors with hemiplegia were included. No differences were seen between the exoskeleton and baseline conditions for any outcomes. Only the patient reported outcome in which subjects were asked to rate their ability to walk outdoors approached statistical significance (p = 0.051) with greater improvement reported for the exoskeleton condition. When asked to rate several key factors about the exoskeleton, weight and assistance emerged as primary perceived negative factors of the exoskeleton underscoring the need for improvements to the technology in this area. Despite lack of differences across groups, some individuals responded positively to the exoskeleton for several functional outcomes measured, highlighting the need for additional exploration into the use of personalized hip exoskeletons for post-stroke rehabilitation.

Trajectory Learning by Therapists' Demonstrations for an Upper Limb Rehabilitation Exoskeleton

In this work, we propose a method for trajectory implementation based on the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Learning by Demonstrations</i> approach to deal with trajectory planning issues in upper-limb rehabilitation exoskeletons. Currently applied path-planning methods use mathematical trajectories or <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Teach-and-play</i> approaches. The former do not propose human-like movements to patients, which is crucial to induce correct motor relearning. Moreover, they often differ from therapists' expectations of how movements should be executed, reducing the acceptability and use of exoskeletons in hospitals. The latter, using a single filtered trajectory demonstration, better meet therapists' expectations but lack consistency and optimization. In our approach, we employed <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Hidden Markov Models</i> , still never used for rehabilitation robotics, to study a set of demonstrations and we optimized the results to respect physiological muscular activation patterns. Recorded few repetitions of a movement from the interaction of a therapist with an exoskeleton, our machine-learning-based algorithm returns a ready-to-use trajectory representing the therapist's desires. We tested our method on a 4 degrees-of-freedom exoskeleton to record 5 exercises, interacting with 5 therapists. Comparing our trajectories with those obtained with literature methods, we see that our approach produces better kinematic and human-likeness results, and is better according to the global opinion expressed by the therapists.

Analysis of motion characteristics of lower limb exoskeleton robot

To address the issue of motion coordination in lower limb exoskeleton rehabilitation robots, and to meet the basic characteristics of ergonomics and human kinematics, a humanoid design was adopted to design a lower limb exoskeleton rehabilitation robot. The Denavit- Hartenberg (D-H) mathematical model of the lower limb exoskeleton rehabilitation robot was established, and the motion characteristics of each joint were analyzed to obtain the D-H parameters during the motion process. The motion characteristics were analyzed from the perspectives of forward kinematics and inverse kinematics. The variation law of motion parameters during the motion process was obtained, and simulation analysis of the motion characteristics was performed. The results show that the maximum center of mass velocity is 0.45 m/s, which is reached within 0.8 seconds. After that, the velocity decreases, with a range of approximately -0.2 m/s to 0.55 m/s. It can be seen that the displacement and velocity changes of the exoskeleton robot legs are relatively stable, which meets the design requirements.

Development of a novel hybrid securing actuator for a self-securing soft robotic hand exoskeleton.

The development of soft robotic hand exoskeletons for rehabilitation has been well-reported in the literature, whereby the emphasis was placed on the development of soft actuators for flexion and extension. Little attention was focused on developing the glove interface and attachments of actuators to the hand. As these hand exoskeletons are largely developed for personnel with impaired hand function for rehabilitation, it may be tedious to aid the patients in donning and doffing the glove, given that patients usually have stiff fingers exhibiting high muscle tone. To address this issue, a hybrid securing actuator was developed and powered pneumatically to allow for rapid securing and release of a body segment. As a proof of concept, the actuator was further adapted into a self-securing glove mechanism and assembled into a complete self-securing soft robotic hand exoskeleton with the attachment of bidirectional actuators. Our validation tests show that the self-wearing soft robotic hand exoskeleton can easily conform and secure onto the human hand and assist with manipulation tasks.

XoRehab: IoT Enabled Wheelchair based Lower Limb Rehabilitation System.

IoT in healthcare brought a technological revolution in rehabilitation, enabling the patients to get rehabilitation in the comfort of their home, while being supervised remotely by the professionals. IoT enabled rehabilitation ensures a best possible way towards recovery, without inflicting further injuries. It also allows customization of rehabilitation plan based on the patient profile and progress, while helping in defining their personalised milestones. The main contribution of this paper is a novel wheelchair based IoT enabled 'XoRehab", exoskeleton for rehabilitation; a device for lower limb, with a backrest mechanism. This involves development of a well-trained robot based on electromechanical actuation with micro-controller and feedback system, which can replace the physical trainer or physiotherapist. This autonomous device will control speed of flexion and extension on patient's limbs to improve efficiency of the treatment. It also provides repetitive motion of flexion and extension. The edge system design to upload local rehabilitation data and logs to the cloud server is presented. We propose an opensource Elasticsearch Logstash Kibana (ELK) stack for providing the cloud services, which is a scalable solution. The design of the developed prototype has been discussed in detail along with the functional test results.Clinical Relevance- The introduction of well-trained exoskeleton in the rehabilitation process, gives a high level of performance in patient recovery, and it contributes to expeditious restoration of their joints and improvement in muscle and nerve system.

Exoskeleton Arm: The First Step for Treatment of Paralysis Patient

Ongoing research and innovation in this field continue to expand the possibilities and offer new opportunities for enhanced functional independence and quality of life. It's important to note that the specific design, features, and capabilities of the exoskeleton can vary based on the research and development efforts outlined in the paper. The mentioned technologies and mechanisms highlight a promising direction for the advancement of assistive exoskeletons in rehabilitation. Further research and refinement in this field can lead to improved outcomes and increased accessibility for individuals with upper extremity mono paresis. The mechanism for the movement of the hand is a tendon flexion mechanism with servo motor actuators controlled by a microcontroller. Technology is transforming patient rehabilitation and improving the lives of individuals with disabilities. Kinematics design replicates the natural movement of the human arm while considering the limitations of the exoskeleton system. Use biomechanical principles to determine the number and placement of joints, as well as the range of motion required for each joint. The exoskeleton should be lightweight, and streamlined, and allow natural motion without restricting the user.

Gait parameter fitting and adaptive enhancement based on cerebral blood oxygen information.

Accurate recognition of patients' movement intentions and real-time adjustments are crucial in rehabilitation exoskeleton robots. However, some patients are unable to utilize electromyography (EMG) signals for this purpose due to poor or missing signals in their lower limbs. In order to address this issue, we propose a novel method that fits gait parameters using cerebral blood oxygen signals. Two types of walking experiments were conducted to collect brain blood oxygen signals and gait parameters from volunteers. Time domain, frequency domain, and spatial domain features were extracted from brain hemoglobin. The AutoEncoder-Decoder method is used for feature dimension reduction. A regression model based on the long short-term memory (LSTM) model was established to fit the gait parameters and perform incremental learning for new individual data. Cross-validation was performed on the model to enhance individual adaptivity and reduce the need for individual pre-training. The coefficient of determination (R2) for the gait parameter fit was 71.544%, with a mean square error (RMSE) of less than 3.321%. Following adaptive enhancement, the coefficient of R2 increased by 6.985%, while the RMSE decreased by 0.303%. These preliminary results indicate the feasibility of fitting gait parameters using cerebral blood oxygen information. Our research offers a new perspective on assisted locomotion control for patients who lack effective myoelectricity, thereby expanding the clinical application of rehabilitation exoskeleton robots. This work establishes a foundation for promoting the application of Brain-Computer Interface (BCI) technology in the field of sports rehabilitation.

Nonlinear-Observer-Based Neural Fault-Tolerant Control for a Rehabilitation Exoskeleton Joint with Electro-Hydraulic Actuator and Error Constraint

The rehabilitation exoskeleton is an effective piece of equipment for stroke patients and the aged. However, this complex human–robot system incurs many problems, such as modeling uncertainties, unknown human–robot interaction, external disturbance, and actuator fault. This paper addresses the adaptive fault-tolerant tracking control for a lower limb rehabilitation exoskeleton joint driven by an electro-hydraulic actuator (EHA). First, the model of the exoskeleton joint is built by considering the principle of the hydraulic cylinder and the servo valve. Then, a novel disturbance-observer-based neural fault-tolerant control scheme is proposed, where the neural network and disturbance observer are incorporated to reduce the influence of the the nonlinear uncertainties and disturbance. Meanwhile, a barrier Lyapunov function is constructed to ensure the stability of the closed-loop system. Finally, comparative simulations on an exoskeleton joint validate the effect of the proposed control scheme.

Autonomous motion and control of lower limb exoskeleton rehabilitation robot.

Introduction: The lower limb exoskeleton rehabilitation robot should perform gait planning based on the patient's motor intention and training status and provide multimodal and robust control schemes in the control strategy to enhance patient participation. Methods: This paper proposes an adaptive particle swarm optimization admittance control algorithm (APSOAC), which adaptively optimizes the weights and learning factors of the PSO algorithm to avoid the problem of particle swarm falling into local optimal points. The proposed improved adaptive particle swarm algorithm adjusts the stiffness and damping parameters of the admittance control online to reduce the interaction force between the patient and the robot and adaptively plans the patient's desired gait profile. In addition, this study proposes a dual RBF neural network adaptive sliding mode controller (DRNNASMC) to track the gait profile, compensate for frictional forces and external perturbations generated in the human-robot interaction using the RBF network, calculate the required moments for each joint motor based on the lower limb exoskeleton dynamics model, and perform stability analysis based on the Lyapunov theory. Results and discussion: Finally, the efficiency of the APSOAC and DRNNASMC algorithms is demonstrated by active and passive walking experiments with three healthy subjects, respectively.

Fractional multi-loop active disturbance rejection control for a lower knee exoskeleton system

Rehabilitation Exoskeleton is becoming more and more important in physiotherapists’ routine work. To improve the treatment performance, such as reducing the recovery period and/or monitoring and reacting to unpredictable situations, the rehabilitation manipulators need to help the patients in various physical trainings. A special case of the active disturbance rejection control (ADRC) is applied to govern a proper realisation of basic limb rehabilitation trainings. The experimental study is performed on a model of a flexible joint manipulator, whose behaviour resembles a real exoskeleton rehabilitation device (a one-degree-of-freedom, rigid-link, flexible-joint manipulator). The fractional (FADRC) is an unconventional model-independent approach, acknowledged as an effective controller in the existence of total plant uncertainties, and these uncertainties are inclusive of the total disturbances and unknown dynamics of the plant. In this work, three FADRC schemes are used, the first one using a fractional state observer (FSO), or FADRC1, second one using a fractional proportional-derivative controller (FPD), or FADRC2, and the third one a Multi-loop fractional in PD-loop controller and the observer-loop (Feedforward and Feedback), or FADRC3. The simulated Exoskeleton system is subjected to a noise disturbance and the FADRC3 shows the effectiveness to compensate all these effects and satisfies the desired position when compared with FADRC1 and FADRC2. The design and simulation were carried out in MATLAB/Simulink.

Review of adaptive control for stroke lower limb exoskeleton rehabilitation robot based on motion intention recognition.

Stroke is a significant cause of disability worldwide, and stroke survivors often experience severe motor impairments. Lower limb rehabilitation exoskeleton robots provide support and balance for stroke survivors and assist them in performing rehabilitation training tasks, which can effectively improve their quality of life during the later stages of stroke recovery. Lower limb rehabilitation exoskeleton robots have become a hot topic in rehabilitation therapy research. This review introduces traditional rehabilitation assessment methods, explores the possibility of lower limb exoskeleton robots combining sensors and electrophysiological signals to assess stroke survivors' rehabilitation objectively, summarizes standard human-robot coupling models of lower limb rehabilitation exoskeleton robots in recent years, and critically introduces adaptive control models based on motion intent recognition for lower limb exoskeleton robots. This provides new design ideas for the future combination of lower limb rehabilitation exoskeleton robots with rehabilitation assessment, motion assistance, rehabilitation treatment, and adaptive control, making the rehabilitation assessment process more objective and addressing the shortage of rehabilitation therapists to some extent. Finally, the article discusses the current limitations of adaptive control of lower limb rehabilitation exoskeleton robots for stroke survivors and proposes new research directions.

Robotic digital twin as a training platform for rehabilitation health personnel

In the last twenty years, a trend towards the digitization of products and processes has been generated, so the new concept of health 4.0 promotes the use of simulators and digital twins for the training of health personnel, as well as for the personalized planning of patients rehabilitation treatments. This paper presents a virtual training tool for health personnel, which is based on the prototype of a digital twin of an exoskeleton for upper limb rehabilitation. The device was designed in Solidworks® and later its equivalent model was obtained in Matlab/Simulink® software. Through the latter, the functionality of the device is evaluated through the implementation of different therapeutic routines, which help the physiotherapist to plan and evaluate the performance of each patient’s treatment. In this case, the evaluation of the movements of the upper limb are generated through independent and combined movements of the shoulder,elbow and wrist joints and, as a result, graphs of the movements are obtained, , as well as a virtual representation of the digital twin and the values of the torques in each joint. Finally, a digital tool that allows the digital twin prototype to be configured to conditions similar to those of the real exoskeleton for automation and supervision tasks is obtained.

Control technologies of lower limb rehabilitation exoskeleton robots based on surface electromyography: A review

The aging population is accompanied by a decline in human body function, leading to an increasing number of people with lower limb dysfunction, which has become a global public health challenge today. The lower limb rehabilitation exoskeleton robot based on surface electromyography is a current research hotspot. It can help people with lower extremity dysfunction perform better rehabilitation training. This review presents the analysis and processing of surface electromyography, feature extraction and recognition, as well as the control methods for lower limb rehabilitation exoskeleton robots.

A Self-Coordinating Controller with Balance-Guiding Ability for Lower-Limb Rehabilitation Exoskeleton Robot.

The restricted posture and unrestricted compliance brought by the controller during human-exoskeleton interaction (HEI) can cause patients to lose balance or even fall. In this article, a self-coordinated velocity vector (SCVV) double-layer controller with balance-guiding ability was developed for a lower-limb rehabilitation exoskeleton robot (LLRER). In the outer loop, an adaptive trajectory generator that follows the gait cycle was devised to generate a harmonious hip-knee reference trajectory on the non-time-varying (NTV) phase space. In the inner loop, velocity control was adopted. By searching the minimum L2 norm between the reference phase trajectory and the current configuration, the desired velocity vectors in which encouraged and corrected effects can be self-coordinated according to the L2 norm were obtained. In addition, the controller was simulated using an electromechanical coupling model, and relevant experiments were carried out with a self-developed exoskeleton device. Both simulations and experiments validated the effectiveness of the controller.

Pneumatic Bending Soft Actuator Coupling With Revolute Joint With Different Boundary Constraints

This article presents a study on pneumatic bending soft actuator (SA) coupling with revolute joint (RJ) with different boundary constraints (BCs), aimed to discover the bending performance of SA wearing on physical joint of human body as body joint actuators with different installation methods. First, a new pneumatic bidirectional bending SA is designed and fabricated, and its mechanical characteristic is obtained by experimental tests and fitting methods. Then, the mechanical characteristic is applied to the discrete bending model that approximates the continuous bending of the SA, and the kinetostatic analysis based on the principle of virtual work is conducted on the SA-RJ coupling system (SA-RJ CS) with fixing BC (FBC), hinging BC (HBC), and sliding BCs (SBCs). The kinetostatic equations are solved numerically, and thus the bending performance of the SA-RJ CS with different BCs is obtained. Results show the SA-RJ CS with SBCs performs better in bending angle and actuating torque than that with FBC or HBC. Therefore, it is suggested to install the SA of joint actuator on human body by SBCs. This study guides the application of pneumatic bending SA in rehabilitation exoskeleton. At present, we have used the axial SBC in rehabilitation exoskeleton.

Bilateral mode exoskeleton for hand rehabilitation with wireless control using 3D printing technology based on IMU sensor

This research aimed to develop an open-source exoskeleton for hand rehabilitation (EHR) device that can be controlled wirelessly in bilateral mode. This design has the advantage of being light and being controlled easily using WiFi-based wireless communication by non-paretic hands. This open-source EHR composed of two parts, namely the master and slave parts, each of which uses a mini ESP32 microcontroller, IMU sensor, and 3D printing. The mean RMSE obtained for all exoskeleton fingers is 9.04°. Since the EHR design is open source, the researchers can create and develop rehabilitation device for the therapeutic process of patients who are paralyzed or partially paralyzed independently using healthy hand.

Lower Limb Exoskeleton for Rehabilitation with Flexible Joints and Movement Routines Commanded by Electromyography and Baropodometry Sensors.

This paper presents the development of an instrumented exoskeleton with baropodometry, electromyography, and torque sensors. The six degrees of freedom (Dof) exoskeleton has a human intention detection system based on a classifier of electromyographic signals coming from four sensors placed in the muscles of the lower extremity together with baropodometric signals from four resistive load sensors placed at the front and rear parts of both feet. In addition, the exoskeleton is instrumented with four flexible actuators coupled with torque sensors. The main objective of the paper was the development of a lower limb therapy exoskeleton, articulated at hip and knees to allow the performance of three types of motion depending on the detected user's intention: sitting to standing, standing to sitting, and standing to walking. In addition, the paper presents the development of a dynamical model and the implementation of a feedback control in the exoskeleton.

CURER: A Lightweight Cable-Driven Compliant Upper Limb Rehabilitation Exoskeleton Robot

Upper limb exoskeletons show promise for improving functionalities required for stroke patients. Despite recent progress, most of current upper limb rehabilitation devices are still bulky, heavy, and less compliant to be applied. This article presents a cable-driven compliant upper limb rehabilitation exoskeleton robot (CURER) with a lightweight frame and comfortable human–robot interaction. A modular series elastic actuator (SEA) was designed to provide controlled torque for each active robotic joint, and Bowden cables were applied to transfer controlled torque to distal joints. A six-bar double parallelogram mechanism was designed to implement 3 active degrees of freedom (DOFs) of a shoulder. An actuated elbow with 1 DOF and a wrist with a passive DOF were also developed for CURER. The anthropomorphic shoulder, elbow, and wrist joints can minimize misalignment between human upper limbs and the robot. The length of anthropomorphic arm was adjustable for a wide range of users. It can apply up to a 33 N·m torque in shoulder flexion/extension, abduction/adduction, intra/extra rotation, and elbow flexion/extension, with a range of 7.6–8.0 Hz position bandwidth in each actuation. CURER has a large range of motion and can provide accurate torque control for stroke patients’ requirements. Besides, a comprehensive rehabilitation strategy including robot-in-charge mode and human-in-charge mode was developed for different recovery stages. Experiments carried out on CURER actuation units demonstrated good position and impedance control performance. Finally, a virtual reality training system was developed to assist the subjects to accomplish upper limb rehabilitation efficiently.

Optimal sliding mode controller for lower limb rehabilitation exoskeleton in constrained environments

&lt;p&gt;In this article, a lower limb exoskeleton (LLE) under contacting constrained motion has been modelled using augmented Lagrange equations which include Lagrange multiplier and Jacobian vectors. A sliding mode Controller optimized by the grey Wolf optimization algorithm has been used for controlling (LLE) in the case of constrained motion with uncertainties and outside perturbation. The grey wolf optimization algorithm has been used as an optimization algorithm for finding the optimal controllers’ parameters in order to improve the performance of the system. The stability analysis of the closed-loop system has been performed using Lyapunov theory of stability. To validate the effectiveness of the proposed controller structure grey wolf optimization algorithm controller (GW-SMC), a series of comparative simulations have been carried out with other types of recently existing sliding mode control (SMC). The results of numerical simulations indicate the superiority of the sliding mode optimized by the GW-SMC over other types of recently existing controller in terms of tracking errors and robustness towards uncertainties and external disturbances.&lt;/p&gt;