Wearable Robot Research Articles

Wearable Robot Design Optimization Using Closed-Form Human-Robot Dynamic Interaction Model.

Wearable robots are emerging as a viable and effective solution for assisting and enabling people who suffer from balance and mobility disorders. Virtual prototyping is a powerful tool to design robots, preventing the costly iterative physical prototyping and testing. Design of wearable robots through modelling, however, often involves computationally expensive and error-prone multi-body simulations wrapped in an optimization framework to simulate human-robot-environment interactions. This paper proposes a framework to make the human-robot link segment system statically determinate, allowing for the closed-form inverse dynamics formulation of the link-segment model to be solved directly in order to simulate human-robot dynamic interactions. The paper also uses a technique developed by the authors to estimate the walking ground reactions from reference kinematic data, avoiding the need to measure them. The proposed framework is (a) computationally efficient and (b) transparent and easy to interpret, and (c) eliminates the need for optimization, detailed musculoskeletal modelling and measuring ground reaction forces for normal walking simulations. It is used to optimise the position of hip and ankle joints and the actuator torque-velocity requirements for a seven segments of a lower-limb wearable robot that is attached to the user at the shoes and pelvis. Gait measurements were carried out on six healthy subjects, and the data were used for design optimization and validation. The new technique promises to offer a significant advance in the way in which wearable robots can be designed.

Dynamic Modelling and Optimal Sliding Mode Control of the Wearable Rehabilitative Bipedal Cable Robot with 7 Degrees of Freedom

Although robot-assisted physiotherapy has gained increasing attention in recent years, the use of wearable rehabilitation robots for lower limbs has shown reduced efficiency due to additional equipment and motors located at the center of the joint, increasing complexity and load on disabled patients. This paper proposes a novel rehabilitation approach by eliminating motors and equipment from the center of joints and placing them on a fixed platform using cable-based power transmission. A proposed model of a 14 cable-driven bipedal robot with 7 degrees of freedom has been used to model a lower limb rehabilitation robot corresponding to it. The dynamic equations of the robot are derived using the Euler-Lagrange method. The sliding mode control technique is utilized to offer accurate control for tracking desired trajectories, ensuring smoothness despite disturbances, and reducing tracking errors. This approach is employed to help prevent patients from falling and support them in maintaining balance during rehabilitative exercises. To ensure that cables exert positive tension, the sliding mode controller was combined with quadratic programming optimization, minimizing path error while constraining the controller input torque to be non-negative. The performance of the proposed controller was assessed by considering several control gains resulting in K = 10 identified as the most effective one. The feasibility of this approach to rehabilitation is demonstrated by the numerical results in MATLAB simulation, which show that the RMSE amount of the right and left hip and thigh angles are 0.29, 0.37, 0.31, and 0.44, respectively which verified an improved rehabilitation process. Also, the correlation coefficient between the Adams and MATLAB simulation results for motor torque was found to be 0.98, indicating a high degree of correlation between the two simulation results.

Enhancing Laser-Induced Graphene via Integration of Gold Nanoparticles and Titanium Dioxide for Sensing and Robotics Applications.

Laser-induced graphene (LIG) is a promising material for various applications due to its unique properties and facile fabrication. However, the electrochemical performance of LIG is significantly lower than that of pure graphene, limiting its practical use. Theoretically, integrating other conductive materials with LIG can enhance its performance. In this study, we investigated the effects of incorporating gold nanoparticles (AuNPs) and titanium dioxide (TiO2) into LIG on its electrochemical properties using ReaxFF molecular dynamics (MD) simulations and experimental validation. We found that both AuNPs and TiO2 improved the work function and surface potential of LIG, resulting in a remarkable increase in output voltage by up to 970.5% and output power density by 630% compared to that of pristine LIG. We demonstrated the practical utility of these performance-enhanced LIG by developing motion monitoring devices, self-powered sensing systems, and robotic hand platforms. Our work provides new insights into the design and optimization of LIG-based devices for wearable electronics and smart robotics, contributing to the advancement of sustainable technologies.

Uncharged Monolithic Carbon Fibers Are More Sensitive to Cross-Junction Compression than Charged.

Textile-based wearable robotics increasingly integrates sensing and energy materials to enhance functionality, particularly in physiological monitoring, demanding higher-performing and abundant robotic textiles. Among the alternatives, activated carbon cloth stands out due to its monolithic nature and high specific surface area, enabling uninterrupted electron transfer and energy storage capability in the electrical double layer, respectively. Yet, the potential of monolithic activated carbon cloth electrodes (MACCEs) in wearables still needs to be explored, particularly in sensing and energy storage. MACCE conductance increased by 29% when saturated with Na2SO4 aqueous electrolyte and charged from 0 to 0.375 V. MACCE was validated for measuring pressure up to 28 kPa at all assessed charge levels. Electrode sensitivity to compression decreased by 30% at the highest potential due to repulsive forces between like charges in electrical double layers at the MACCE surface, counteracting compression. MACCE's controllable sensitivity decrease can be beneficial for garments in avoiding irrelevant signals and focusing on essential health changes. A MACCE charge-dependent sensitivity provides a method for assessing local electrode charge. Our study highlights controlled charging and electrolyte interactions in MACCE for multifunctional roles, including energy transmission and pressure detection, in smart wearables.

A portable inflatable soft wearable robot to assist the shoulder during industrial work.

Repetitive overhead tasks during factory work can cause shoulder injuries resulting in impaired health and productivity loss. Soft wearable upper extremity robots have the potential to be effective injury prevention tools with minimal restrictions using soft materials and active controls. We present the design and evaluation of a portable inflatable shoulder wearable robot for assisting industrial workers during shoulder-elevated tasks. The robot is worn like a shirt with integrated textile pneumatic actuators, inertial measurement units, and a portable actuation unit. It can provide up to 6.6 newton-meters of torque to support the shoulder and cycle assistance on and off at six times per minute. From human participant evaluations during simulated industrial tasks, the robot reduced agonist muscle activities (anterior, middle, and posterior deltoids and biceps brachii) by up to 40% with slight changes in joint angles of less than 7% range of motion while not increasing antagonistic muscle activity (latissimus dorsi) in current sample size. Comparison of controller parameters further highlighted that higher assistance magnitude and earlier assistance timing resulted in statistically significant muscle activity reductions. During a task circuit with dynamic transitions among the tasks, the kinematics-based controller of the robot showed robustness to misinflations (96% true negative rate and 91% true positive rate), indicating minimal disturbances to the user when assistance was not required. A preliminary evaluation of a pressure modulation profile also highlighted a trade-off between user perception and hardware demands. Finally, five automotive factory workers used the robot in a pilot manufacturing area and provided feedback.

Paediatric ankle rehabilitation system based on twisted and coiled polymer actuators

Rehabilitation is crucial for children with physical disabilities arising from various conditions. Traditional exoskeletons, reliant on electric motors and rigid components, making them cumbersome, heavy, and unsuitable for use outside clinical facilities. To overcome these, researchers are turning to soft wearable rehabilitation robots (SWRRs) with artificial muscles based on smart materials like twisted and coiled polymer actuators (TCPs). TCPs offer enhanced compliance, adaptability, comfort, safety, and reduced weight—critical for paediatric use. Despite facing challenges like low operating frequencies and high temperatures, TCPs are explored as potential artificial muscles for SWRRs, due to their advantages on the force they can generate, the strain and a linear behaviour. This study details a proof of concept for a paediatric rehabilitation system for ankles based on TCPs, including the actuator characterization, mechanical design, control strategy, and human-computer-interface (HCI). The resulting device achieved a 1.4 Nm torque, a 10° range of motion in dorsiflexion within 5 s, and integrated electromyographic HCI. This research marks a promising step towards innovative, soft wearable rehabilitation solutions for children with physical disabilities.

User-agnostic adaptation of human locomotion intent: Leveraging Teacher-Student-Learning and ensemble modeling

Wearable robot control in complicated contexts requires an understanding of human locomotion intent and behaviors. However, signals from human–robot interfaces are typically reliant on the user, leading to poor performance of the model trained on training user when applied to new end-point users. This study aims to address this problem by developing a novel Teacher-Student-Learning (TSL) approach using Heterogeneous Ensemble Hypotheses (HEH) to achieve unsupervised user-agnostic adaptation. The motivation behind using the Teacher-Student-Learning architecture is to leverage the diverse features extracted by HEH while maintaining computational efficiency. HEH reduces the difference between labeled training users and unlabeled end-point users by incorporating multiple diverse feature generators to extract a wide range of features, thereby increasing classification accuracy and reducing variance. However, this approach sacrifices efficiency due to the ensemble nature of HEH. To address this trade-off, the knowledge from HEH is distilled into a single network using TSL, ensuring precision and efficiency. The proposed approach is evaluated on two publicly available human locomotion datasets and a 2D moon dataset. Experimental results demonstrate the effectiveness of the proposed method, outperforming all other methods. Tested with three datasets, the proposed method can classify end-point users’ data with an average accuracy of 98.9%, 96.7%, and 96.9% while yielding a low processing time (1 ms). Compared to a benchmark method, the suggested strategy improves the average accuracy by 1.5% and 7.2% for categorizing the target users’ locomotor modes and stabilizes the learning curves. The proposed method represents a significant contribution to the field of human activity recognition and human intent prediction for human–robot interaction systems, enhancing the efficiency and generalization capacity of these systems.

Wearable robots for the real world need vision.

To enhance wearable robots, understanding user intent and environmental perception with novel vision approaches is needed.

Design and testing of fabric-based portable soft exoskeleton glove for hand grasping assistance in daily activity

Hand exoskeleton robots have been developed as rehabilitation robots and assistive devices. Based on the material used, they can be soft or hard exoskeletons. Soft materials such as fabric can be used as a component of the wearable robot to increase comfortability. In this paper, we proposed an affordable soft hand exoskeleton based on fabric and motor-tendon actuation for hand flexion/extension motion assistance in daily activities. On-off control and PI compensator were implemented to regulate finger flexion and extension of the soft exoskeleton. The controllers were embedded into a microcontroller using Simulink software. The input signal command comes from the potentiometer and electromyography (EMG) sensor to drive the flexion/extension movement. Based on the experiments, the proposed controller successfully controlled the exoskeleton hand to facilitate a user in grasping various objects. The proposed soft hand exoskeleton is lightweight, comfortable, portable, and affordable, making it easily manufactured using available hardware and open-source code. The developed soft exoskeleton is a potential assistive device for a person who lost the ability to grasp objects.

Woven Fabric Muscle for Soft Wearable Robotic Application Using Two-Dimensional Zigzag Shape Memory Alloy Actuator.

In this study, we propose a fabric muscle based on the Zigzag Shape Memory Alloy (ZSMA) actuator. Soft wearable robots have been gaining attention due to their flexibility and the ability to provide significant power support to the user without hindering their movement and mobility. There has been an increasing focus on the research and development of fabric muscles, which are crucial components of these robots. This article introduces a high-performance fabric muscle utilizing zigzag-shaped shape memory alloy (SMA), ZSMA, a new form of SMA actuator. Through modeling and experimentation of the ZSMA actuator, we identified an optimized actuator design and detailed the fabric muscle fabrication process. The proposed fabric actuator, weighing only 7.5 g, demonstrated the impressive capability to lift a weight of 2 kg with a contraction displacement of 40%. This significant achievement paves the way for future research possibilities in soft wearable robotics.

Exosuit for Exercise?

Hiking is a cost-effective way to encourage physical activity in individuals of all ages, spend time in nature, and promote physical and mental healing. However, the hobby may promote the development of musculoskeletal conditions such as lower back pain (LBP) in older adults, . AireLevate is an emerging technology representing a new era of wearable robotics. The apron-like design uses compressed air to support the lower region of the spine, preventing LBP and minimizing energy usage. However, the influences of economic instability and community support could prevent the use of the technology. Poor economic stability may limit access to the device and supporting resources including electricity. While community support is correlated with elevated technology usage, distrust in Western technology prevalent in many communities may prevent exosuit usage. The intersection of sex and religion, religion and geopolitical factors, and race and geopolitical factors, may serve as barriers to exosuit access, especially among minorities subject to energy poverty and those who practice modesty. Future research of exosuit use in stroke patients holds the promise of enhanced rehabilitation outcomes, increased mobility, and improved quality of life.

Clinical effects of walking exercise program for older adults applied with an exercise assist robot (Bot Fit): A randomized controlled trial

BackgroundInterval walking exercise (IWE) consists of repeated walking for 3 min with high intensity, followed by 3 min of walking with low intensity. A wearable robot is an exoskeleton system that is worn on the body and helps the body move. Research questionThe purpose of this study is to verify the effects of performing IWE using Bot Fit (Samsung Electronics, Korea) on older adults. MethodsThe experimental group (EG; n = 10) performed the IWE program with Bot Fit, and the control group (CG; n = 12) performed the IWE program without Bot Fit, three times a week for six weeks. Both groups were evaluated for spatio-temporal parameters, pelvic movement, function, muscle power, and waist-to-hip ratio (WHR) at before, after three weeks and after six weeks of exercise. ResultsThere was a significant difference between the two groups in the pelvic tilt range after six weeks of exercise (P < 0.05). The pelvic rotation range showed a significant difference after six weeks of exercise in the EG (P < 0.01). During the stance phase, rectus abdominis (RA) muscle power and its contraction ratio significantly increased after six weeks of exercise in the EG (P < 0.05). The WHR was significantly lower after six weeks of exercise in EG than in the CG (P < 0.05). SignificanceBot Fit maximizes the normal walking effect, promotes correct posture and physical activity to prevent falls, improves quality of life (QOL). It has shown clinical effects and has been used for successful aging of older adults.

Comprehensive Approach to Workplace Injury Prevention: Strategies and Technological Solutions

Workplace injuries pose significant risks to employees and organizations across industries. This article explores integrating emerging technologies into comprehensive workplace injury prevention strategies to forge a safer future. It examines traditional approaches, such as hazard assessment, engineering controls, and personal protective equipment (PPE). It delves into cutting-edge technologies like wearable devices, artificial intelligence (AI), virtual reality (VR), and robotics. These innovations offer new avenues for monitoring workers, predicting risks, providing immersive training, and automating hazardous tasks. The article discusses strategies for seamlessly integrating these technologies, highlighting potential benefits, challenges, and best practices for successful implementation. With a focus on continuous improvement, the article presents a vision for leveraging emerging technologies to enhance workplace safety and drive positive outcomes.

Thermogalvanic hydrogel-based e-skin for self-powered on-body dual-modal temperature and strain sensing

Sensing of both temperature and strain is crucial for various diagnostic and therapeutic purposes. Here, we present a novel hydrogel-based electronic skin (e-skin) capable of dual-mode sensing of temperature and strain. The thermocouple ion selected for this study is the iodine/triiodide (I−/I3−) redox couple, which is a common component in everyday disinfectants. By leveraging the thermoelectric conversion in conjunction with the inherent piezoresistive effect of a gel electrolyte, self-powered sensing is achieved by utilizing the temperature difference between the human body and the external environment. The composite hydrogels synthesized from polyvinyl alcohol (PVA) monomers using a simple freeze‒thaw method exhibit remarkable flexibility, extensibility, and adaptability to human tissue. The incorporation of zwitterions further augments the resistance of the hydrogel to dehydration and low temperatures, allowing maintenance of more than 90% of its weight after 48 h in the air. Given its robust thermal current response, the hydrogel was encapsulated and then integrated onto various areas of the human body, including the cheeks, fingers, and elbows. Furthermore, the detection of the head-down state and the monitoring of foot movements demonstrate the promising application of the hydrogel in supervising the neck posture of sedentary office workers and the activity status. The successful demonstration of self-powered on-body temperature and strain sensing opens up new possibilities for wearable intelligent electronics and robotics.

Enhancing wearability: designing wearable suit platforms for industrial workers

PurposeThe objective of this study was to develop wearable suit platforms with various anchoring structure designs with the intention of improving wearability and enhancing user satisfaction.Design/methodology/approachThis study selected fabrics and materials for the suit platform through material performance tests. Two anchoring structure designs, 11-type and X-type are compared with regular clothing under control conditions. To evaluate the comfort level of the wearable suit platform, a satisfaction survey and electroencephalogram (EEG) measurements are conducted to triangulate the findings.FindingsThe 11-type exhibited higher values in comfort indicators such as α, θ, α/High-β and lower values in concentration or stress indicators such as β, ϒ, sensorimotor rhythm (SMR)+Mid-β/θ, and a spectral edge frequency of 95% compared to the X-type while walking. The 11-type offers greater comfort and satisfaction compared to the X-type when lifting based on the EEG measurements and the participants survey.Originality/valueIt is recommended to implement the 11-type when designing wearable suit platforms. These findings offer essential data on wearability, which can guide the development of soft wearable robots.

Sheet‐Based Fluidic Diodes for Embedded Fluidic Circuitry in Soft Devices

The recent development of soft fluidic analogs to electrical components aims to reduce the demand for rigid and bulky electromechanical valves and hard electronic controllers within soft robots. This ongoing effort is advanced in this work by creating sheet‐based fluidic diodes constructed from readily available flexible sheets of polymers and textiles using a layered fabrication approach amenable to manufacturing at scale. These sheet‐based fluidic diodes restrict reverse flow over a wide range of differential pressures—exhibiting a diodicity (the ratio of resistance to reverse vs forward flow) of approximately 100×—to address functional limitations exhibited by prior soft fluidic diodes. By harnessing the diode's highly unidirectional flow, soft devices capable of 1) facilitating the capture and storage of pressurized fluid, 2) performing Boolean operations using diode logic, 3) enabling binary encoding of circuits by preventing interactions between different pressurized input lines, and 4) converting oscillating input pressures to a direct current‐like, positively phased output are realized. This work exemplifies the use of fluidic diodes to achieve complex patterns of actuation and unique capabilities through embedded fluidic circuitry, enabling future development of sheet‐based systems—including wearable and assistive robots made from textiles—as well as other soft robotic devices.

Shape Programmable and Multifunctional Soft Textile Muscles for Wearable and Soft Robotics

Textiles are promising candidates for use in soft robots and wearable devices due to their inherent compliance, high versatility, and skin comfort. Planar fluidic textile‐based actuators exhibit low profile and high conformability, and can seamlessly integrate additional components (e.g., soft sensors or variable stiffness structures [VSSs]) to create advanced, multifunctional smart textile actuators. In this article, a new class of programmable, fluidic soft textile muscles (STMs) that incorporate multilayered silicone sheets with embedded fluidic channels is introduced. The STMs are scalable and fabricated by apparel engineering techniques, offering a fabrication approach able to create large‐scaled multilayered structures that can be challenging for current microfluidic bonding methods. They are also highly automation compatible due to no manual insertion of elastic tubes/bladders into textile structures. Liquid metal is employed for creating fluidic channels. It is not only used for actuation but also used as channels for additional features such as soft piezoresistive sensors with enhanced sensitivity to STMs’ pressure‐induced elongation, or VSSs of either low‐melting‐point alloys or a new thermo‐responsive epoxy with low viscosity and transition temperature. The STMs hold promising prospects for soft robotic and wearable applications, which is demonstrated by an example of a textile‐based wearable 3D skin‐stretch haptic interface.

Muscle-inspired stiffness-tunable flexible fiber jamming structure for wearable robots *

Soft robotics have found their tremendous application prospects in wearable robots due to the inherent compliance of soft materials when interacting with human bodies. However, the limited load-bearing and output capabilities impeded their application in real world. Variable stiffness design contributes to tackling this problem by enhancing the overall structural rigidity. Nevertheless, most of current jamming-based variable stiffness structures realize their stiffness enhancement by squeezing discrete rigid elements, resulting in the loss of structural compliance in the high stiffness state, which could significantly reduce the deformability and even injure the individuals when utilized in wearable robots. In this paper, we propose a muscle-inspired stiffness-continuously-adjustable flexible fiber jamming (FFJ) structure for soft wearable robots. The FFJ structure can achieve continuous stiffness-variation by controlling the fiber overlapping length, which maintains stretchability even in the high stiffness state. We provide a theoretical model to analyze the mechanical performance of the proposed FFJ structure with different design parameters, and verify the model experimentally. The preliminary results show that we achieved 9 times of stiffness enhancement of the proposed FFJ structure by controlling the vacuum pressure, and the maximum tensile stiffness is 4.1 N mm−1. We further demonstrated the effectiveness of the proposed FFJ structure on wearable robots in three different working scenarios: active finger rehabilitation, active elbow rehabilitation, and passive trunk support. The results show that the FFJ structure was able to provide controllable impedance force for active finger/elbow rehabilitation, and help support the human body during long-term labor. This work broadens the frontiers of soft wearable robots and leads a way to the future design of soft and strong robots and devices.

High Performance Proprioceptive Fiber Actuators Based on Ag Nanoparticles-Incorporated Hybrid Twisted and Coiled System.

Thermally driven fiber actuators are emerging as promising tools for a range of robotic applications, encompassing soft and wearable robots, muscle function restoration, assistive systems, and physical augmentation. Yet, to realize their full potential in practical applications, several challenges, such as a high operational temperature, incorporation of intrinsic self-sensing capabilities for closed-loop feedback control, and reliance on bulky, intricate actuation systems, must be addressed. Here, an Ag nanoparticles-based twisted and coiled fiber actuator that achieves a high contractile actuation of ≈36% is reported at a considerably low operational temperature of ≈83°C based on a synergistic effect of constituent fiber elements with low glass transition temperatures. The fiber actuator can monitor its contractile actuation in real-time based on the piezoresistive properties inherent to its Ag-based conductive region, demonstrating its proprioceptive sensing capability. By exploiting this capability, the proprioceptive fiber actuator adeptly maintains its intended contractile behavior, even when faced with unplanned external disturbances. To demonstrate the capabilities of the fiber actuator, this study integrates it into a closed-loop feedback-controlled bionic arm as an artificial muscle, offering fresh perspectives on the future development of intelligent wearable devices and soft robotic systems.

Motion‐Compensation Control of Supernumerary Robotic Arms Subject to Human‐Induced Disturbances

Supernumerary robotic limbs (SRLs) are a novel type of wearable robot used as the third limb to assist the wearer to perform operations that are difficult or impossible for human hands. Although SRLs can compensate for and enhance human physiological abilities, the unpredictable disturbances caused by human movements significantly affect the coordinating control between the robot and wearer. In this study, a general modeling of supernumerary robotic arms (SRAs) on an omnidirectional floating base is presented. Using position and orientation feedback from sensors at the base and tip, three control methods based on different sensor feedback are proposed to improve tracking accuracy. Experiments on point and trajectory tracking are conducted on the SRAs. In the results (point and circular trajectory‐tracking errors with the manipulator as floating base: 1.18 ± 0.56 mm [mean ± standard deviation(SD) error] and 1.42 ± 0.43 mm, point trajectory‐tracking errors with the human shoulder as floating base: 1.37 ± 0.58 mm, and the performance in perforation positioning operation experiment), it is demonstrated that the proposed controllers enable the SRAs to achieve high‐precision tracking and good adaptability to different user movements and frequencies. Also, in the results, future studies on dynamic high‐precision manipulation of SRLs are motivated.