Search results

The purpose of this paper is to understand compression garment in the area of medical industry, compression garments were used initially for patients with circulatory problems. External pressure was created by compression garments on the body surface which prevents blood clots, leg swelling and improves venous hemodynamics.

Compression rehabilitation is a significant element in the effective management of lower limb problems of people associated with venous, lymphatic, fat disorders like lipoedema.

Compression garments have been attributed primarily for the increase in blood flow, improvement in recovery, reduction in muscle vibration that increase stability, improvement in thermoregulation, decrease in muscle pain, elimination of blood lactate and creatine kinase after exercise.

Compression garments are extraordinary clothes that contain elastomeric yarns or fibers that are responsible for applying significant mechanical pressure on the required body surface for compressing, stabilizing and supporting underlying tissues.

The purpose of this review paper is to address the substantial challenges of the outdated exoskeletons used for rehabilitation and further study the current advancements in this field. The shortcomings and technological developments in sensing the input signals to enable the desired motions, actuation, control and training methods are explained for further improvements in exoskeleton research.

Search platforms such as Web of Science, IEEE, Scopus and PubMed were used to collect the literature. The total number of recent articles referred to in this review paper with relevant keywords is filtered to 143.

Exoskeletons are getting smarter often with the integration of various modern tools to enhance the effectiveness of rehabilitation. The recent applications of bio signal sensing for rehabilitation to perform user-desired actions promote the development of independent exoskeleton systems. The modern concepts of artificial intelligence and machine learning enable the implementation of brain–computer interfacing (BCI) and hybrid BCIs in exoskeletons. Likewise, novel actuation techniques are necessary to overcome the significant challenges seen in conventional exoskeletons, such as the high-power requirements, poor back drivability, bulkiness and low energy efficiency. Implementation of suitable controller algorithms facilitates the instantaneous correction of actuation signals for all joints to obtain the desired motion. Furthermore, applying the traditional rehabilitation training methods is monotonous and exhausting for the user and the trainer. The incorporation of games, virtual reality (VR) and augmented reality (AR) technologies in exoskeletons has made rehabilitation training far more effective in recent times. The combination of electroencephalogram and electromyography-based hybrid BCI is desirable for signal sensing and controlling the exoskeletons based on user intentions. The challenges faced with actuation can be resolved by developing advanced power sources with minimal size and weight, easy portability, lower cost and good energy storage capacity. Implementation of novel smart materials enables a colossal scope for actuation in future exoskeleton developments. Improved versions of sliding mode control reported in the literature are suitable for robust control of nonlinear exoskeleton models. Optimizing the controller parameters with the help of evolutionary algorithms is also an effective method for exoskeleton control. The experiments using VR/AR and games for rehabilitation training yielded promising results as the performance of patients improved substantially.

Robotic exoskeleton-based rehabilitation will help to reduce the fatigue of physiotherapists. Repeated and intention-based exercise will improve the recovery of the affected part at a faster pace. Improved rehabilitation training methods like VR/AR-based technologies help in motivating the subject.

The paper describes the recent methods for signal sensing, actuation, control and rehabilitation training approaches used in developing exoskeletons. All these areas are key elements in an exoskeleton where the review papers are published very limitedly. Therefore, this paper will stand as a guide for the researchers working in this domain.

This study discusses the tracking trajectory issue of the exoskeleton under the bounded disturbance and designs an useful tracking trajectory control method to solve it. By using the proposed control method, the tracking error can be successfully convergence to the assigned boundary. Meanwhile, the chattering effect caused by the actuators is already reduced, and the tracking performance of the pneumatic artificial muscles (PAMs) elbow exoskeleton is improved effectively.

A prescribed performance sliding mode control method was developed in this study to fulfill the joint position tracking trajectory task on the elbow exoskeleton driven by two PAMs. In terms of the control structure, a dynamic model was built by conforming to the adaptive law to compensate for the time variety and uncertainty exhibited by the system. Subsequently, a super-twisting algorithm-based second-order sliding mode control method was subjected to the exoskeleton under the boundedness of external disturbance. Moreover, the prescribed performance control method exhibits a smooth prescribed function with an error transformation function to ensure the tracking error can be finally convergent to the pre-designed requirement.

From the theoretical perspective, the stability of the control method was verified through Lyapunov synthesis. On that basis, the tracking performance of the proposed control method was confirmed through the simulation and the manikin model experiment.

As revealed by the results of this study, the proposed control method sufficiently applies to the PAMs elbow exoskeleton for tracking trajectory, which means it has potential application in the actual robot-assisted passive rehabilitation tasks.

To improve the position tracking efficiency of the upper-limb rehabilitation robot for stroke hemiplegia patients, the optimization Learning rate of the membership function based on the fuzzy impedance controller of the rehabilitation robot is propose.

First, the impaired limb’s damping and stiffness parameters for evaluating its physical recovery condition are online estimated by using weighted least squares method based on recursive algorithm. Second, the fuzzy impedance control with the rule has been designed with the optimal impedance parameters. Finally, the membership function learning rate online optimization strategy based on Takagi-Sugeno (TS) fuzzy impedance model was proposed to improve the position tracking speed of fuzzy impedance control.

This method provides a solution for improving the membership function learning rate of the fuzzy impedance controller of the upper limb rehabilitation robot. Compared with traditional TS fuzzy impedance controller in position control, the improved TS fuzzy impedance controller has reduced the overshoot stability time by 0.025 s, and the position error caused by simulating the thrust interference of the impaired limb has been reduced by 8.4%. This fact is verified by simulation and test.

The TS fuzzy impedance controller based on membership function online optimization learning strategy can effectively optimize control parameters and improve the position tracking speed of upper limb rehabilitation robots. This controller improves the auxiliary rehabilitation efficiency of the upper limb rehabilitation robot and ensures the stability of auxiliary rehabilitation training.

The purpose of this paper is to design a new trajectory error compensation method to improve the trajectory tracking performance and compliance of the knee exoskeleton in human–exoskeleton interaction motion.

A trajectory error compensation method based on admittance-extended Kalman filter (AEKF) error fusion for human–exoskeleton interaction control. The admittance controller is used to calculate the trajectory error adjustment through the feedback human–exoskeleton interaction force, and the actual trajectory error is obtained through the encoder feedback of exoskeleton and the designed trajectory. By using the fusion and prediction characteristics of EKF, the calculated trajectory error adjustment and the actual error are fused to obtain a new trajectory error compensation, which is feedback to the knee exoskeleton controller. This method is designed to be capable of improving the trajectory tracking performance of the knee exoskeleton and enhancing the compliance of knee exoskeleton interaction.

Six volunteers conducted comparative experiments on four different motion frequencies. The experimental results show that this method can effectively improve the trajectory tracking performance and compliance of the knee exoskeleton in human–exoskeleton interaction.

The AEKF method first uses the data fusion idea to fuse the estimated error with measurement errors, obtaining more accurate trajectory error compensation for the knee exoskeleton motion control. This work provides great benefits for the trajectory tracking performance and compliance of lower limb exoskeletons in human–exoskeleton interaction movements.

This paper aims to explore and review the potential of robotic rehabilitation as a treatment approach for Alzheimer’s disease (AD) and its impact on the health and quality of life of AD patients.

The present discourse endeavors to provide a comprehensive overview of extant scholarly inquiries that have examined the salience of inhibitory mechanisms vis-à-vis robotic interventions and their impact on patients with AD. Specifically, this review aims to explicate the contemporary state of affairs in this realm by furnishing a detailed explication of ongoing research endeavors. With the objective of elucidating the significance of inhibitory processes in robotic therapies for individuals with AD, this analysis offers a critical appraisal of extant literature that probes the intersection of cognitive mechanisms and assistive technologies. Through a meticulous analysis of diverse scholarly contributions, this review advances a nuanced understanding of the intricate interplay between inhibitory processes and robotic interventions in the context of AD.

According to the review papers, it appears that implementing robot-assisted rehabilitation can serve as a pragmatic and effective solution for enhancing the well-being and overall quality of life of patients and families engaged with AD. Besides, this new feature in the robotic area is anticipated to have a critical role in the success of this innovative approach.

Due to the nascent nature of this cutting-edge technology and the constrained configuration of the mechanized entity in question, further protracted analysis is imperative to ascertain the advantages and drawbacks of robotic rehabilitation vis-à-vis individuals afflicted with Alzheimer’s ailment.

The potential for robots to serve as indispensable assets in the provision of care for individuals afflicted with AD is significant; however, their efficacy and appropriateness for utilization by caregivers of AD patients must be subjected to further rigorous scrutiny.

This paper reviews the current robotic method and compares the current state of the art for the AD patient.

Biofeedback is used for regulating vestibular adaptation and balance by providing real-time stimulus to the individual during physical activities. This study aimed at (1) developing a wearable device, which tracks balance, counts the number and the direction of balance losses and provides haptic biofeedback through real-time vibration stimulus (2) investigating device efficacy on an adolescent medulloblastoma patient during static and dynamic tasks.

A 16-year-old medulloblastoma patient used the device during 10-m walking and single-leg stance tests. The knee joint kinematics and the number and direction of balance losses were recorded for “with” and “without” biofeedback conditions.

The device helped regulate the knee joint kinematics and reduce the number of balance losses of the medulloblastoma patient. The knee joint movement pattern similarity of the control subject was highly correlated (R² = 0.997, RMSE = 1.232). Conversely, medulloblastoma patient knee joint movement pattern similarity was relatively weak (R² = 0.359, RMSE = 18.6) when “with” and “without” biofeedback conditions were compared. The number of balance losses decreased when the medulloblastoma patient was guided with biofeedback.

The major limitation of this pilot study is the lack of a large and homogeneous number of participants. The medulloblastoma patient used the device while walking after she was given enough time to get used to the tactile biological feedback, so the long-term effect of the device and biofeedback guidance were not investigated. Additionally, the potential desensitization with prolonged use of the device was not evaluated.

Biofeedback reduced the number of balance losses; additionally, the knee joint movement pattern was regulated during static and dynamic tasks. This device can be integrated into the physical therapy of patients with balance, vestibular and postural control impairments.

This is compact and has an easy-to-wear design, patients, who have balance and postural control impairments, can practically use the device during their activities of daily living.

The device promotes physical activity adaptation and regulates gait through continuous and real-time balance control. Its design makes it simple for the user to wear it beneath clothing while using the sensor.

Soft grippers have safer and more adaptable human–machine and environment–machine interactions than rigid grippers. However, most soft grippers with single gripping postures have a limited gripping range. Therefore, this paper aims to design a soft gripper with variable gripping posture to enhance the gripping adaptability.

This paper proposes a novel soft gripper consisting of a conversion mechanism and four spring-reinforced soft pneumatic actuators (SSPAs) as soft fingers. By adjusting the conversion mechanism, four gripping postures can be achieved to grip objects of different shapes, sizes and weights. Furthermore, a quasi-static model is established to predict the bending deformation of the finger. Finally, the bending angle of the finger is measured to validate the accuracy of the quasi-static model. The gripping force and gripping adaptability are tested to explore the gripping performance of the gripper.

Through experiments, the results have shown that the quasi-static model can accurately predict the deformation of the finger; the gripper has the most significant gripping force under the parallel posture, and the gripping adaptability of the gripper is highly enhanced by converting the four gripping postures.

By increasing the gripping posture, a novel soft gripper with enhanced gripping adaptability is proposed to enlarge the gripping range of the soft gripper with a single posture. Furthermore, a quasi-static model is established to analyze the deformation of SSPA.

This paper seeks to define a theoretical model for the urban regeneration of mass housing areas based on citizen initiative, self-management and self-financing in the form of the neighbourhood cooperative. This paper aims to identify mechanisms for economic resource generation that enable the improvement of the urban surroundings and its buildings without assuming disproportionate economic burdens by the local residents based on two principles, the economies of scale and service provision.

The research is structured in three phases: a literature review of the different trends in self-financing for urban regeneration and the conceptual framework for the definition of a cooperative model; the definition of theoretical model by analysing community ecosystem, neighbourhood-based services and the requirements for its economic equilibrium; and the discussion of the results and the conclusions.

The results show the potential of the cooperative model to generate a social economy capable of reducing costs and producing additional resources to finance the rehabilitation process. The findings show not only the extent of economic advantages but also multiple social, physical and environmental benefits. Its implementation involves the participation of multiple actors, which is one of its significant advantages.

The main contribution is to approach comprehensive urban rehabilitation from a collaborative understanding, overcoming the main financing difficulties of the current practices based on public subsidy policies. The model also allows an ethical relationship to be built with supplier companies by means of corporate social responsibility.

In certain industrial operations, workers are required to stand for a prolonged duration. This leads to muscular fatigue in the legs, posing a threat to the productivity and well-being of the workers. This paper aims to address this problem of women in the clothing industry with an exoskeleton designed for lower extremities and improve productivity.

Ulrich’s product design approach has been followed with suitable modifications. The methodology involves a study to justify the need for this product and terminating at the physical and virtual evaluations of the product. Required anthropometric parameters are considered along the design process.

The exoskeleton discussed in this paper is an innovative product made of Aluminium 6061 alloy. During the simulation phase of the product, total von-mises stresses to a part bearing 1 leg were 31.5 MPa, 94.7 MPa and 284 MPa for aluminium, SS308 and springs, respectively. These values are below the yield limit by a great margin. Based on a user survey of this product, 72% of the targeted customers were interested in buying. Also, comparing electromyography (EMG) mean value of the voltage between workers’ leg with and without exoskeleton revealed that there was an improvement in the voltage by 2.5% when exoskeleton was used.

This paper emphasizes, for the first time – the necessity of an exoskeleton indigenized for the Indian population and the process of realizing it by designing an exoskeleton.