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Pressure ulcer (PU) is the representative skin injury and is a major limiting factor in the long-term use of the wearable robots. For the sake of the health of the wearable robot user and to improve the usability of the wearable robot, we developed a pressure ulcer breakout time estimation model (PUBTEM). The model estimates the possible breakout time of PU at the skin beneath the cuff of the wearable robot, hence, it can be used as a guide for the design, control, and operational strategy of wearable robot. To develop the model, PU breakout mechanisms were analyzed extensively in the biomechanical perspective. From the analysis, skin pressure, skin shear stress and compressive stress in muscle tissue were identified as major factors causing PU and their relationships with time were collected. However, the skin shear stress and compressive stress are either difficult or impossible to measure in the environment where the wearable robot is used. Hence, we converted those two factors into the pressure—a easily measureable quantity—by applying the FEM analysis of the human musculoskeletal model and the relationship with friction coefficient. Through this conversion process, the relationship of all three factors with PU breakout time could be modeled with respect to a single variable, the skin pressure. Finally, the most conservative relationship that has fastest PU occurrence time was established as the PUBTEM. The model was validated with the human subject experiments approved by the IRB. [ABSTRACT FROM AUTHOR]

In the field of rehabilitation engineering, wearable robots for upper limbs tend to help powerless arms of patients smoothly complete daily activities. Compared with traditional rigid exoskeleton, soft exosuit takes the advantage of high movement flexibility and relatively compact structure so that it could be a more adaptive and compliant alternative for the elder and the disabled. In this study, a novel dual-arm exosuit is proposed to provide active assistance for multiple joints through bidirectional cable-driven modules. Several Bowden cables achieve power transmission from actuators mounted on the back to shoulders and elbows. The actuator is designed with reference to the principle of differential mechanism, in order to automatically preload both cables wrapped around it, generate assistive torque in two opposite rotation directions of a joint, and keep the human-robot interaction as safe as possible. This study adopts the constant torque control to assist in the pre-tightening process, and develop a model-based control strategy for bidirectional joint motion enhancement according to mathematical models of the human-robot system. The experimental results demonstrate that the prototype can impose pretension on each cable, and offer enough support on the joint according to the wearers' demands. [ABSTRACT FROM AUTHOR]

This study aimed to develop wearable robotic gloves that can provide comfort to logistics and transportation workers while providing hand assistance and addressing accumulated muscle fatigue caused by repetitive manual handling tasks. Two types of gloves, rivet-type and pouch-type were developed and evaluated using the nine-hole peg test (NHPT) and grip strength tests. Results showed rivet-type gloves had better dexterity, with an 8.14% faster NHPT time, and maintained 85% grip strength compared to 80% for pouch-type gloves, even after fatigue exercises. Wearability tests were conducted by measuring clothing pressure and brainwaves. In contrast to the functional experimental results, the pouch-type gloves exhibited significant decreases in clothing pressure during actuation. According to the difference in brain waves in the frontal lobe region, the beta and gamma waves observed when wearing pouch-type gloves were lower than those of rivet-type gloves, and pouch-type gloves exhibited higher alpha-wave results than rivet-type gloves. These results imply that participants were in a comparatively relaxed state when wearing pouch-type gloves. A wearer's evaluation survey on the overall design, function, comfort, safety, ease of use, usefulness, and use intention was conducted. In summary, the rivet-type gloves exhibited better results in hand performance while the pouch-type gloves showed advantages in wearability, suggesting a tradeoff relationship between force transmission and wearer comfort. The results of this study aimed to improve the work efficiency at logistics and transportation industry sites and help improve the welfare of workers. [ABSTRACT FROM AUTHOR]

Relearning to walk requires progressive training in real scenarios—overground—along with assistance in basic tasks, such as balancing. In addition, user ability must be maximized through compliant robotic assistance as needed. Despite decades of research, gait rehabilitation robotic devices yield controversial results. This article presents the conceptual design of a novel walking assistance and rehabilitation robot, the NIMBLE robot, aimed at providing ambulatory, bodyweight-supported gait training, assisting the user's center of mass trajectory to aid weight transfer and dynamic balance during walking. NIMBLE consists of a robotic mobile frame, a partial bodyweight support (PBWS) system, an ambulatory lower-limb exoskeleton (Exo-H3) and a cable-driven pelvis-assisting robot. Designed as a modular structure, it differentiates hierarchical communication levels through a Robot Operating System (ROS) 2 network. We present the mechatronic design and experimental results assessing the impact of the mechatronic coupling between the robotic modules on the walking kinematics and the frame movement control performance. The robotic frame hardly affects the walking kinematics up to 2 degrees in both the sagittal and frontal planes, making it feasible for lateral balance and weight translation training. Moreover, it successfully tracks and follows user trajectories. The NIMBLE robotic frame assessment shows promising results for ambulatory gait rehabilitation. [ABSTRACT FROM AUTHOR]

In this study, we introduce a two-dimensional (2D) human skeletal model coupled with knee, spine, and shoulder exoskeletons. The primary purpose of this model is to predict the optimal lifting motion and provide torque support from the exoskeleton through the utilization of inverse dynamics optimization. The kinematics and dynamics of the human model are expressed using the Denavit–Hartenberg (DH) representation. The lifting optimization formulation integrates the electromechanical dynamics of the DC motors in the exoskeletons of the knee, spine, and shoulder. The design variables for this study include human joint angle profiles and exoskeleton motor current profiles. The optimization objective is to minimize the squared normalized human joint torques, subject to physical and task-specific lifting constraints. We solve this optimization problem using the gradient-based optimizer SNOPT. Our results include a comparison of predicted human joint angle profiles, joint torque profiles, and ground reaction force (GRF) profiles between lifting tasks with and without exoskeleton assistance. We also explore various combinations of exoskeletons for the knee, spine, and shoulder. By resolving the lifting optimization problems, we designed the optimal torques for the exoskeletons located at the knee, spine, and shoulder. It was found that the support from the exoskeletons substantially lowers the torque levels in human joints. Additionally, we conducted experiments only on the knee exoskeleton. Experimental data indicated that using the knee exoskeleton decreases the muscle activation peaks by 35.00%, 10.03%, 22.12%, 30.14%, 16.77%, and 25.71% for muscles of the erector spinae, latissimus dorsi, vastus medialis, vastus lateralis, rectus femoris, and biceps femoris, respectively. [ABSTRACT FROM AUTHOR]

This paper presents the design, modeling, and control of a novel soft-rigid knee joint robot (SR-KR) for assisting motion. SR-KR is proposed to assist patients with knee joint injuries conducting gait training and completing walking movements. SR-KR consists of a novel soft-rigid bidirectional curl actuator, a thigh clamping structure, and a crus clamping structure. The actuating part of SR-KR is composed of soft materials, which ensures the wearing comfort and safety, while the wearing parts contain rigid structure, which ensures the efficient transmission of torque. The bending deformation model of SR-KR is established, which reveal the relationship among SR-KR's bending curvature, working pressure, and output torque. Experiments show that SR-KR can provide more than 26.3 Nm torque for knee joint motion in human gait range. A double closed loop servo control system including attitude servo and pressure servo is built to better apply SR-KR. Mechanical property test, trajectory-driven test, and lower limb wearing test have been conducted, which show that SR-KR has ability to assist in lower limb motion and has potential in the fields of rehabilitation and human enhancement. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Relearning to walk requires progressive training in real scenarios—overground—along with assistance in basic tasks, such as balancing. In addition, user ability must be maximized through compliant robotic assistance as needed. Despite decades of research, gait rehabilitation robotic devices yield controversial results. This article presents the conceptual design of a novel walking assistance and rehabilitation robot, the NIMBLE robot, aimed at providing ambulatory, bodyweight-supported gait training, assisting the user’s center of mass trajectory to aid weight transfer and dynamic balance during walking. NIMBLE consists of a robotic mobile frame, a partial bodyweight support (PBWS) system, an ambulatory lower-limb exoskeleton (Exo-H3) and a cable-driven pelvis-assisting robot. Designed as a modular structure, it differentiates hierarchical communication levels through a Robot Operating System (ROS) 2 network. We present the mechatronic design and experimental results assessing the impact of the mechatronic coupling between the robotic modules on the walking kinematics and the frame movement control performance. The robotic frame hardly affects the walking kinematics up to 2 degrees in both the sagittal and frontal planes, making it feasible for lateral balance and weight translation training. Moreover, it successfully tracks and follows user trajectories. The NIMBLE robotic frame assessment shows promising results for ambulatory gait rehabilitation.

This study is to determine how a lightweight active soft waist exoskeleton (ASWE) reduces the oxygen consumption and activity of lower back muscles of the wearer performing the repetitive lifting tasks. The heavy and frequent manual lifting operations are usually associated with an increased risk of injury in the industry. An ASWE is designed to assist workers' spine for lifting weights. The structural composition and operation principle were described for the ASWE. Twelve men were recruited in the experiments as the test subjects. Oxygen consumption and electromyography of the thoracic erector spinae (TES) at the T9 level and lumbar erector spinae (LES) at the L3 level were recorded during 90 lifts in 15 min. Subjects' discomfort and effectiveness evaluation were collected after lifting trials. The average value of oxygen consumption was decreased from form 15.9 ml/kg/min (Without-ASWE condition) to 13.7 ml/kg/min (With-ASWE condition). The increase in electromyography root mean square amplitude from the start until the end of the lifting trial was significantly lower when the ASWE was in use for the TES (162.79 vs. 82.08%) and the LES (122.48 vs. 83.87%). The use of the ASWE showed less oxygen consumption and back muscle contraction compared to the nonuse, which might reduce metabolic consumption or slow down the muscle fatigue level of the wearer's back across the lifting trial. Therefore, wearing the ASWE can reduce the discomfort of body parts, lumbar regions that exercise for a long time. [ABSTRACT FROM AUTHOR]

Introduction: Robotic exoskeletons are emerging technologies that have demonstrated their effectiveness in assisting with Activities of Daily Living. However, kinematic disparities between human and robotic joints can result in misalignment between humans and exoskeletons, leading to discomfort and potential user injuries. Methods: In this paper, we present an ergonomic knee exoskeleton based on a dual four-bar linkage mechanism powered by hydraulic artificial muscles for stair ascent assistance. The device comprises two asymmetric four-bar linkage mechanisms on the medial and lateral sides to accommodate the internal rotation of the knee and address the kinematic discrepancies between these sides. A genetic algorithm was employed to optimize the parameters of the four-bar linkage mechanism to minimize misalignment between human and exoskeleton knee joints. The proposed device was evaluated through two experiments. The first experiment measured the reduction in undesired load due to misalignment, while the second experiment evaluated the device's effectiveness in assisting stair ascent in a healthy subject. Results: The experimental results indicate that the proposed device has a significantly reduced undesired load compared to the traditional revolute joint, decreasing from 14.15 N and 18.32 N to 1.88 N and 1.07 N on the medial and lateral sides, respectively. Moreover, a substantial reduction in muscle activities during stair ascent was observed, with a 55.94% reduction in surface electromyography signal. Discussion: The reduced undesired load of the proposed dual four-bar linkage mechanism highlights the importance of the adopted asymmetrical design for reduced misalignment and increased comfort. Moreover, the proposed device was effective at reducing the effort required during stair ascent. [ABSTRACT FROM AUTHOR]

In this study, a wearable exoskeleton with an active drive mechanism was designed for both space-saving and to ensure the safety and comfort of the workers. At the same time, this active wearable exoskeleton mechanism aims to facilitate the daily life of disabled people with its movement assisting feature. For these purposes, an active and wearable exoskeleton with a total of five degrees of freedom, two active (arm and shoulder flexion/extension) and three passive axes (shoulder lateral rotation and shoulder abduction/adduction), was developed. A novel load suspension system has been implemented to the design for absorbtion of the mechanism's own weight. The force-based impedance control method has been used for effective human–robot interaction. Furthermore, a low-cost electromyography sensor has been developed and integrated into the robotic system as biological feedback. As a result of the tests, it has been revealed that the system can help with lifting loads and successfully perform rehabilitation exercises. [ABSTRACT FROM AUTHOR]

Robotic legs, such as for lower-limb exoskeletons and prostheses, have bimodal operation: (1) within a task, like for walking (high speed and low force for the swing phase and low speed and higher force when the leg bears the weight of the system); (2) between tasks, like between walking and sit–stand motions. Sizing a traditional single-ratio actuation system for such extremum operations leads to oversized heavy electric motor and poor energy efficiency at low speeds. This paper explores a bimodal actuation concept where a hydrostatic transmission is dynamically reconfigured using custom motorized ball valves to suit the requirements of a robotic leg with a smaller and more efficient actuation system. First, this paper presents an analysis of the mass and efficiency advantages of the bimodal solution over a baseline solution, for three operating points: high-speed, high-force, and braking modes. Second, an experimental demonstration with a custom-built actuation system and a robotic leg test bench is presented. Control challenges regarding dynamic transition between modes are discussed and a control scheme solution is proposed and tested. The results show the following findings: (1) The actuator prototype can meet the requirements of a leg bimodal operation in terms of force, speed, and compliance while using smaller motors than a baseline solution. (2) The proposed operating principle and control schemes allow for smooth and fast mode transitions. (3) Motorized ball valves exhibit a good trade-off between size, speed, and flow restriction. (4) Motorized ball valves are a promising way to dynamically reconfigure a hydrostatic transmission while allowing energy to be dissipated. [ABSTRACT FROM AUTHOR]

Due to its unique wearing comfort, operational flexibility and human-machine cooperation, the supernumerary robotic limb has a wide range of applications, such as medical rehabilitation, the aerospace, industrial production and building decoration, etc. This study analyzes the research status and development trend of supernumerary robotic limb at home and abroad, and reviews the design of the external limb structure, motion modeling, human-machine information interaction and coordination control. Meanwhile, the advantages and disadvantages of rigid external limb and flexible external limb are analyzed, the core and key of the motion modeling of the external limb are illustrated, and the technical challenges of human-machine interaction and optimal cooperative control are revealed. Finally, the main research points of the supernumerary robotic limb are summarized, and its future development direction and trend are prospected.

In this study, we introduce a two-dimensional (2D) human skeletal model coupled with knee, spine, and shoulder exoskeletons. The primary purpose of this model is to predict the optimal lifting motion and provide torque support from the exoskeleton through the utilization of inverse dynamics optimization. The kinematics and dynamics of the human model are expressed using the Denavit–Hartenberg (DH) representation. The lifting optimization formulation integrates the electromechanical dynamics of the DC motors in the exoskeletons of the knee, spine, and shoulder. The design variables for this study include human joint angle profiles and exoskeleton motor current profiles. The optimization objective is to minimize the squared normalized human joint torques, subject to physical and task-specific lifting constraints. We solve this optimization problem using the gradient-based optimizer SNOPT. Our results include a comparison of predicted human joint angle profiles, joint torque profiles, and ground reaction force (GRF) profiles between lifting tasks with and without exoskeleton assistance. We also explore various combinations of exoskeletons for the knee, spine, and shoulder. By resolving the lifting optimization problems, we designed the optimal torques for the exoskeletons located at the knee, spine, and shoulder. It was found that the support from the exoskeletons substantially lowers the torque levels in human joints. Additionally, we conducted experiments only on the knee exoskeleton. Experimental data indicated that using the knee exoskeleton decreases the muscle activation peaks by 35.00%, 10.03%, 22.12%, 30.14%, 16.77%, and 25.71% for muscles of the erector spinae, latissimus dorsi, vastus medialis, vastus lateralis, rectus femoris, and biceps femoris, respectively.

Since abnormal posture of the trunk due to aging decreases walking ability, the use of a trunk device is required to maintain and improve posture. Wearable assistive devices for the purpose of extending healthy life expectancy must be lightweight, have a simple mechanism, and have a drive system that cooperates with human movements. In our previous study, we developed an adjustable stiffness mechanism to correct the posture of the trunk. In this study, we propose a rotation mechanism that can support trunk rotation during walking and posture correction. The mechanism is a simple structure consisting of a bearing mechanism to reduce rotational resistance and a plastic block connected to pneumatic soft actuator bellows. Using a pneumatic soft actuator provides high adaptability to sudden human movements. This paper explains the outline of the proposed mechanism and the mathematical model of the actuator, followed by a description of the rotational stiffness adjustment method to support trunk rotation movements. Finally, the validity of the proposed mechanism and the effectiveness of the stiffness adjustment method are described based on the results of evaluation experiments.

Introduction: Robotic exoskeletons are emerging technologies that have demonstrated their effectiveness in assisting with Activities of Daily Living. However, kinematic disparities between human and robotic joints can result in misalignment between humans and exoskeletons, leading to discomfort and potential user injuries.Methods: In this paper, we present an ergonomic knee exoskeleton based on a dual four-bar linkage mechanism powered by hydraulic artificial muscles for stair ascent assistance. The device comprises two asymmetric four-bar linkage mechanisms on the medial and lateral sides to accommodate the internal rotation of the knee and address the kinematic discrepancies between these sides. A genetic algorithm was employed to optimize the parameters of the four-bar linkage mechanism to minimize misalignment between human and exoskeleton knee joints. The proposed device was evaluated through two experiments. The first experiment measured the reduction in undesired load due to misalignment, while the second experiment evaluated the device’s effectiveness in assisting stair ascent in a healthy subject.Results: The experimental results indicate that the proposed device has a significantly reduced undesired load compared to the traditional revolute joint, decreasing from 14.15 N and 18.32 N to 1.88 N and 1.07 N on the medial and lateral sides, respectively. Moreover, a substantial reduction in muscle activities during stair ascent was observed, with a 55.94% reduction in surface electromyography signal.Discussion: The reduced undesired load of the proposed dual four-bar linkage mechanism highlights the importance of the adopted asymmetrical design for reduced misalignment and increased comfort. Moreover, the proposed device was effective at reducing the effort required during stair ascent.

Wearable robots, sometimes known as exoskeletons, are incredible devices for improving human strength, reducing fatigue, and restoring impaired mobility. The control of powered exoskeletons, on the other hand, is still a challenge. This necessitates the development of a technique to simulate exoskeleton–wearer interaction. This study uses a two-dimensional human skeletal model with a powered knee exoskeleton to predict the optimal lifting motion and assistive torque. For lifting motion prediction, an inverse dynamics optimization formulation is utilized. In addition, the electromechanical dynamics of the exoskeleton DC motor are modeled in the lifting optimization formulation. The design variables are human joint angle profiles and exoskeleton motor current profiles. The human joint torque square is minimized subject to physical and lifting task constraints. Then, the lifting optimization problem is solved by the gradient-based sparse nonlinear optimizer (SNOPT). Furthermore, the optimal exoskeleton torque is implemented through a two-phase control strategy to provide optimal assistance in lifting. Experimental validations of the optimal control with 6 Nm and 16 Nm maximum assistive torque are presented. Both 6 Nm and 16 Nm maximum optimal assistance of the exoskeletons reduce the mean values of vastus lateralis, biceps femoris, and latissimus dorsi muscle activations compared to the lifting without the exoskeleton. However, the mean value of the vastus medialis activation is increased by a small amount for the exoskeleton case, although its peak value is reduced. Finally, the experimental results demonstrate that the proposed lifting optimization formulation and control strategy are promising for powered knee exoskeleton for lifting tasks. [ABSTRACT FROM AUTHOR]

This study introduces a novel convolutional neural network (CNN) architecture, encompassing both single and multi-head designs, developed to identify a user's locomotion activity while using a wearable lower limb robot. Our research involved 500 healthy adult participants in an activities of daily living (ADL) space, conducted from 1 September to 30 November 2022. We collected prospective data to identify five locomotion activities (level ground walking, stair ascent/descent, and ramp ascent/descent) across three terrains: flat ground, staircase, and ramp. To evaluate the predictive capabilities of the proposed CNN architectures, we compared its performance with three other models: one CNN and two hybrid models (CNN-LSTM and LSTM-CNN). Experiments were conducted using multivariate signals of various types obtained from electromyograms (EMGs) and the wearable robot. Our results reveal that the deeper CNN architecture significantly surpasses the performance of the three competing models. The proposed model, leveraging encoder data such as hip angles and velocities, along with postural signals such as roll, pitch, and yaw from the wearable lower limb robot, achieved superior performance with an inference speed of 1.14 s. Specifically, the F-measure performance of the proposed model reached 96.17%, compared to 90.68% for DDLMI, 94.41% for DeepConvLSTM, and 95.57% for LSTM-CNN, respectively. [ABSTRACT FROM AUTHOR]

Patients with hand paralysis have motor and sensory dysfunction of their hands. They can neither flex/extend their fingers nor feel the gripping force. To enable the gripping motion with sensory information, sensory information has to be acquired simultaneously as the fingers are assisted. Since the skin plays a role in increasing friction with the grasped object in addition to acquiring sensory information, it is important for the skin to be in direct contact with the object. Therefore, it is necessary to enable gripping motion and measure the gripping force with an open finger pad. In this study, a wearable system was developed to enable gripping motion and gripping force measurements with an open finger pad. A tendon-driven finger-assist glove assisted the flexion/extension of the fingers and adduction/abduction of the thumb; moreover, a sensor was developed to estimate the fingertip force by measuring the lateral expansion force of the finger tissue. We conducted an evaluation experiment for the developed sensor and object grasping experiments for the developed wearable system with the sensor. The root mean square error (RMSE) in force estimation was approximately 0.2 N. In addition, the system could assist the motions of the thumb/index/middle finger in grasping objects. [ABSTRACT FROM AUTHOR]

Children with cerebral palsy (CP) experience reduced quality of life due to limited mobility and independence. Recent studies have shown that lower-limb exoskeletons (LLEs) have significant potential to improve the walking ability of children with CP. However, the number of prototyped LLEs for children with CP is very limited, while no single-leg exoskeleton (SLE) has been developed specifically for children with CP. This study aims to fill this gap by designing the first size-adjustable SLE for children with CP aged 8 to 12, covering Gross Motor Function Classification System (GMFCS) levels I to IV. The exoskeleton incorporates three active joints at the hip, knee, and ankle, actuated by brushless DC motors and harmonic drive gears. Individuals with CP have higher metabolic consumption than their typically developed (TD) peers, with gravity being a significant contributing factor. To address this, the study designed a model-based gravity-compensator impedance controller for the SLE. A dynamic model of user and exoskeleton interaction based on the Euler–Lagrange formulation and following Denavit–Hartenberg rules was derived and validated in Simscape™ and Simulink® with remarkable precision. Additionally, a novel systematic simplification method was developed to facilitate dynamic modelling. The simulation results demonstrate that the controlled SLE can improve the walking functionality of children with CP, enabling them to follow predefined target trajectories with high accuracy. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Shanghai Jiaotong University (Science) is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The observation of gait phases provides essential information for controller design and performance evaluation of lower extremity wearable robots. Specifically, gait events are often defined and detected to distinguish the transition of gait phases. To achieve this, rule-based gait event detection algorithms detect gait events by utilizing the repetitive features in human walking with very few sensors and simple logic. Besides, many of these algorithms define gait events as characteristic features that are detectable from the sensor measurements. However, conventional methods have not fully considered the correlation between the sensor measurement and characteristics of the human motion. Moreover, these methods were only accurate for a limited condition of human motion, for example, walking only or running without sensor noise. Therefore, in this paper, we propose a gait event detection algorithm considering the full kinematic characteristics of the lower extremity under various gait conditions. The proposed algorithm demonstrates robust performance for both walking and running. Besides, to minimize the time delay and the false information in the detected gait events, this paper also proposes a robust signal dithering algorithm that reduces the sensor noise with a limited phase delay. Overall, the performances of the proposed methods are verified through gait experiments with human subjects. [ABSTRACT FROM AUTHOR]

Most mobile-type hip exoskeletons only assist on a sagittal plane with a single actuator per hip joint for compactness, lightweightness, and low cost. Even though a new concept of hip mechanism that allows assistance not only on a sagittal plane but also on a frontal plane only with a single actuator has been proposed recently, it has several limitations, such as having a small range of motion and being applicable only on a single gait-mode. Herein, we propose a novel design approach that is a well-combined procedure of target design with clinical walking data, multi-objective design problem definition, type synthesis of mechanism, and analysis of the obtained Pareto-front solutions. We take the hip spherical mechanism’s kinematic trade-offs into account. By utilizing a more complex type of 1-DOF(Degrees of Freedom) mechanism (6-bar Stephenson-III) and multi-objective optimization approach, we successfully enhanced both compactness and hip moment assistance in the single-actuator hip exoskeleton mechanism, and its performance was validated via benchtop experiment of its prototype.

We developed a wearable assistive robot that directly measures the contact force acting between the robot and the human body, aiming to enhance the safety of such wearable devices. The force acting on the body is not directly measured, instead, it is estimated by measuring the torque acting on the robot joint in the wearable assistive robot. Despite the risk of failing to recognize dangerous forces due to modeling errors, the forces actually at work have not been examined. Here, we developed an arm-mounted assistive robot that directly measures the contact force as the distribution information to build a system and evaluate safety; in addition, the contact state between the robot and the human body was discussed. Accordingly, two experiments were conducted with 10 subjects. The first verified the contact force measurement performance of the robot, while the second demonstrated the application of contact force information to check the safety of the robot. The proposed robot can accurately measure the contact force, and the robot movement is safe under general control, for example, using the pain tolerance limit as the safety index. This eliminated the risk of not directly monitoring the forces acting on the surface of the human body. Furthermore, our result have implication for evaluating structural problems of the robot by evaluating contact conditions during movements.

OBJECTIVES The purpose of this study was to investigate the effects of assist and resistance torque on the spatiotemporal gait characteristics, and the symmetry and asymmetry of gait using a Gait Enhancing and Motivating System (GEMS) in the elderly. METHODS A cross-sectional and repeated measure design was used. A total of 18 participants (9 males, 9 females; age: 63.5 ± 5.02 years; mass: 64.26 ± 6.87 kg; height: 164.06 ± 7.15 cm) were recruited from a local community, and spatiotemporal gait data were collected with OptoGait system and GEMS. Spatiotemporal gait variables and differences between the dominant and non-dominant legs of these variables were assessed (step length, step time, stance phase, swing phase, single support, load response, pre swing phase, stride time, stride length, double support, cadence, and gait speed). The effects of three modes including normal, assist, and resist modes using GEMS were investigated twice for each participant on a 9-meter walkway. A one-way repeated measure analysis of variance followed by Bonferroni post-hoc tests was conducted. RESULTS The assist mode increased step time, swing phase, stride time and reduced stance phase, pre-swing phase, double support, cadence, and gait speed as compared to normal mode. The resist mode increased stance phase, load response, pre-swing phase, double support, cadence, and reduced step time, swing phase, and stride time. In dominant leg, assist mode showed increased step time and reduced pre-swing phase than normal mode, and greater step time than resist mode (p < 0.05). However, there was no effect of external torque on symmetry and asymmetry between both legs (p > 0.05). CONCLUSIONS The resistance and assist torque of GEMS alter spatiotemporal characteristics during the stance and swing phase of gait in the elderly. However, the resistance torque and assist torque of GEMS did not increase or decrease the gait asymmetry between the dominant and non-dominant legs.

Work-related musculoskeletal disorders is a serious problem affecting the construction workforce. Pipe workers are subjected to forward bending tasks that cause back injuries. Recent advancements in wearable robotic technologies have led to a growing interest in the use of back-support exoskeletons as a potential solution to reduce the occurrences of back injuries. However, without the willingness of workers to use exoskeletons, the intervention will not be successful in the industry. This study conducted a user assessment of a commercially available passive back-support exoskeleton for pipework in terms of usability, level of perceived discomfort, and subjective perception of the benefits, barriers to adoption, and design modifications. Fourteen pipe workers performed their regular work tasks using a passive back-support exoskeleton and provided feedback on their experience with the device. The results indicate that the exoskeleton is easy to use (4.13±0.34) and did not affect workers' productivity (2.07±1.22). Participants reported willingness to use the exoskeleton but raised concerns about the compatibility of the exoskeleton with the safety harness. Reduced perceived discomfort was observed in the lower back. However, there was an increase in discomfort at the chest (20%), thigh (73%), and shoulder (250%). There was a strong correlation (p<0.05) between discomfort at the chest, thigh, shoulder, and upper arm and workers' perception of usability of the exoskeleton. Health benefits such as reduction in stress in the back muscle were reported. Discomfort was experienced while using the exoskeleton in confined spaces. Design modifications, such as the integration of the safety harness and the tool strap with the exoskeleton, were identified. The findings are expected to inspire studies in the area of human-wearable robot interaction and task-specific applications of exoskeletons for construction work. [ABSTRACT FROM AUTHOR]

Background: Wearable devices for robot-assisted gait training (RAGT) provide overground gait training for the rehabilitation of neurological injuries. We aimed to evaluate the effectiveness and safety of RAGT in patients with a neurologic deficit. Methods: Twenty-eight patients receiving more than ten sessions of overground RAGT using a joint-torque-assisting wearable exoskeletal robot were retrospectively analyzed in this study. Nineteen patients with brain injury, seven patients with spinal cord injury and two patients with peripheral nerve injury were included. Clinical outcomes, such as the Medical Research Council scale for muscle strength, Berg balance scale, functional ambulation category, trunk control tests, and Fugl–Meyer motor assessment of the lower extremities, were recorded before and after RAGT. Parameters for RAGT and adverse events were also recorded. Results: The Medical Research Council scale scores for muscle strength (36.6 to 37.8), Berg balance scale (24.9 to 32.2), and functional ambulation category (1.8 to 2.7) significantly improved after overground RAGT (p < 0.05). The familiarization process was completed within six sessions of RAGT. Only two mild adverse events were reported. Conclusions: Overground RAGT using wearable devices can improve muscle strength, balance, and gait function. It is safe in patients with neurologic injury. [ABSTRACT FROM AUTHOR]

In recent years, the advent of soft robotics has changed the landscape of wearable technologies. Soft robots are highly compliant and malleable, thus ensuring safe human-machine interactions. To date, a wide variety of actuation mechanisms have been studied and adopted into a multitude of soft wearables for use in clinical practice, such as assistive devices and rehabilitation modalities. Much research effort has been put into improving their technical performance and establishing the ideal indications for which rigid exoskeletons would play a limited role. However, despite having achieved many feats over the past decade, soft wearable technologies have not been extensively investigated from the perspective of user adoption. Most scholarly reviews of soft wearables have focused on the perspective of service providers such as developers, manufacturers, or clinicians, but few have scrutinized the factors affecting adoption and user experience. Hence, this would pose a good opportunity to gain insight into the current practice of soft robotics from a user's perspective. This review aims to provide a broad overview of the different types of soft wearables and identify the factors that hinder the adoption of soft robotics. In this paper, a systematic literature search using terms such as "soft", "robot", "wearable", and "exoskeleton" was conducted according to PRISMA guidelines to include peer-reviewed publications between 2012 and 2022. The soft robotics were classified according to their actuation mechanisms into motor-driven tendon cables, pneumatics, hydraulics, shape memory alloys, and polyvinyl chloride muscles, and their pros and cons were discussed. The identified factors affecting user adoption include design, availability of materials, durability, modeling and control, artificial intelligence augmentation, standardized evaluation criteria, public perception related to perceived utility, ease of use, and aesthetics. The critical areas for improvement and future research directions to increase adoption of soft wearables have also been highlighted. [ABSTRACT FROM AUTHOR]

Robotic legs, such as for lower-limb exoskeletons and prostheses, have bimodal operation: (1) within a task, like for walking (high speed and low force for the swing phase and low speed and higher force when the leg bears the weight of the system); (2) between tasks, like between walking and sit–stand motions. Sizing a traditional single-ratio actuation system for such extremum operations leads to oversized heavy electric motor and poor energy efficiency at low speeds. This paper explores a bimodal actuation concept where a hydrostatic transmission is dynamically reconfigured using custom motorized ball valves to suit the requirements of a robotic leg with a smaller and more efficient actuation system. First, this paper presents an analysis of the mass and efficiency advantages of the bimodal solution over a baseline solution, for three operating points: high-speed, high-force, and braking modes. Second, an experimental demonstration with a custom-built actuation system and a robotic leg test bench is presented. Control challenges regarding dynamic transition between modes are discussed and a control scheme solution is proposed and tested. The results show the following findings: (1) The actuator prototype can meet the requirements of a leg bimodal operation in terms of force, speed, and compliance while using smaller motors than a baseline solution. (2) The proposed operating principle and control schemes allow for smooth and fast mode transitions. (3) Motorized ball valves exhibit a good trade-off between size, speed, and flow restriction. (4) Motorized ball valves are a promising way to dynamically reconfigure a hydrostatic transmission while allowing energy to be dissipated.

In physical rehabilitation, exoskeleton assistive devices aim to restore lost motor functions of a patient suffering from neuromuscular or musculoskeletal disorders. These assistive devices are classified as operating in one of two modes: (1) passive mode, in which the exoskeleton passively moves its joints through the full range (or a subset) of the patient's motion during engagement, or (2) assist-as-needed (AAN) mode, in which the exoskeleton provides assistance to the joints of the patient, either by initiating the movements or assisting the patient's movements to complete the task at hand. Achieving high physical human-robot interaction (pHRI) transparency is an open problem for multiple degrees-of-freedom (DOFs) redundant exoskeletons. Using the EXO-UL8 exoskeleton, this study compares two multi-joint admittance control schemes (hyper parameter- based, and Kalman Filter-based) with comfort optimization to improve human-exoskeleton transparency. The control schemes were tested by three healthy subjects who completed reaching tasks while assisted by the exoskeleton. Kinematic information in both joint and task space, as well as force- and torque-based power exchange between the human arm and exoskeleton, are collected and analyzed. The results show that the preliminary Kalman Filter-based control scheme matches the performance of the existing hyper parameter-based scheme, highlighting the potential of the Kalman Filter-based approach for additional performance.

Surface electromyography (sEMG) control interface is a common method for human-centered robotics. Researchers have frequently improved the recognition accuracy of sEMG through multichannel or high-precision signal acquisition devices. However, this increases the cost and complexity of the control system. Therefore, this study developed a control interface based on the sEMG enveloped signal for a collaborative wearable robot to improve the accuracy of sEMG recognition based on the time-domain (TD) features. Specifically, an acquisition device is developed to obtain the sEMG envelope signal, and 11 types of TD features are extracted from the sEMG envelope signal acquired from the upper limb. Furthermore, a dimension reduction method based on the correlation coefficient is proposed, transforming the 11-dimensional feature into a five-dimensional envelope feature set without decreasing the accuracy. Moreover, a recognition algorithm based on a neural network has also been proposed for gesture classification. Finally, the recognition accuracy of the proposed method, principal component analysis (PCA) feature set, and Hudgins TD feature set is compared, with their accuracy at 84.39%, 72.44%, and 70.89%, respectively. Therefore, the results indicate that the envelope feature set performs better than the common gesture recognition method based on signal channel sEMG envelope signal.

The use of textiles in soft robotics is gaining popularity because of the advantages textiles offer over other materials in terms of weight, conformability, and ease of manufacture. The purpose of this research is to examine the stitching process used to construct fabric-based pneumatic bending actuators as well as the effect of segment types on the actuators' properties when used in soft robotic glove applications. To impart bending motion to actuators, two techniques have been used: asymmetry between weave and weft knit fabric layers and mechanical anisotropy between these two textiles. The impacts of various segment types on the actuators' grip force and bending angle were investigated further. According to experiments, segmenting the actuator with a sewing technique increases the bending angle. It was discovered that actuators with high anisotropy differences in their fabric combinations have high gripping forces. Textile-based capacitive strain sensors are also added to selected segmented actuator types, which possess desirable properties such as increased grip force, increased bending angle, and reduced radial expansion. The sensors were used to demonstrate the controllability of a soft robotic glove using a closed-loop system. Finally, we demonstrated that actuators integrated into a soft wearable glove are capable of grasping a variety of items and performing various grasp types. [ABSTRACT FROM AUTHOR]

• A wearable robot for lower limb fracture reduction and rehabilitation is developed. • The parameters of the robot are designed by multi-objective optimization. • A hierarchical control strategy with three control modes is developed. Most current orthopedic robots focused on fracture reduction surgery with limited involvement in postoperative rehabilitation training. However, post-surgical orthopedic rehabilitation training directly impacts the recovery of mobility, ambulation, and limb function in patients. Here, we propose a six degree-of-freedom (DoF) parallel robot that can perform fracture reduction surgery as well as postoperative rehabilitation training for lower limb. The actuation system is switchable to reduce the weight in fixed status and reuse the actuation units for lowering treatment costs. An optimal parameter design based on multi-objective optimization is presented for maintaining lightweight and high stiffness. The wearable robot has a 1.7 kg weight in electric mode and 1.3 kg in manual mode, with >80 kg payload. A hierarchical control strategy with three control modes is developed to meet the requirements of different stages of fracture treatment. Our preliminary experiments on bone models demonstrated the potential effectiveness of the proposed wearable robot for lower limb fracture reduction and rehabilitation training. [ABSTRACT FROM AUTHOR]

In this study, we developed an upper-limb power-assisted wearable robot designed to reduce the burden of handling repetitive medium- to low-weight loads for daily logistics workers, thereby enhancing their work efficiency and overall safety. This study proposes a practical wearable robot with a well-designed structure for effectively supporting pick-and-place tasks at waist-to-shoulder height by applying a vertical force directly to the wearer's wrist. The proposed robot features two active joints that are minimal for vertical assistance, resulting in a lightweight and compact structure. It offers six degrees of freedom per arm, including four passive joints, allowing free end-effector movement. Designed to connect only to the wearer's wrist, the robot's linkage is positioned along the wearer's arm, not requiring alignment with the human–robot joint center, making it easy to wear and having a simple structure. This paper presents a method for calculating the joint torque that accounts for the deformation of the robot's lightweight and slim links. This approach enhances the gravity compensation accuracy, and the proposed method demonstrates a lower RMS error compared to calculations based on the statics of the rigid link model. Experimental results demonstrated that the robot allowed for a wide range of motion and consistently applied an assistive force of 2 kgf per arm, facilitating the handling of objects weighing several kilograms. • Active actuation and non-anthropomorphic structure. • 6 DOF per arm, allowing for a wide range of upper-limb motion, with only two active joints equipped with actuators. • Method for calculating and controlling joint torques by considering link deflection and the inclination of the wearer's upper body. • Directly reducing the load on the wearer's shoulders and arms and transferring it to the wearer's pelvis, effectively assisting in lifting and moving objects. [ABSTRACT FROM AUTHOR]

This study introduces a novel convolutional neural network (CNN) architecture, encompassing both single and multi-head designs, developed to identify a user’s locomotion activity while using a wearable lower limb robot. Our research involved 500 healthy adult participants in an activities of daily living (ADL) space, conducted from 1 September to 30 November 2022. We collected prospective data to identify five locomotion activities (level ground walking, stair ascent/descent, and ramp ascent/descent) across three terrains: flat ground, staircase, and ramp. To evaluate the predictive capabilities of the proposed CNN architectures, we compared its performance with three other models: one CNN and two hybrid models (CNN-LSTM and LSTM-CNN). Experiments were conducted using multivariate signals of various types obtained from electromyograms (EMGs) and the wearable robot. Our results reveal that the deeper CNN architecture significantly surpasses the performance of the three competing models. The proposed model, leveraging encoder data such as hip angles and velocities, along with postural signals such as roll, pitch, and yaw from the wearable lower limb robot, achieved superior performance with an inference speed of 1.14 s. Specifically, the F-measure performance of the proposed model reached 96.17%, compared to 90.68% for DDLMI, 94.41% for DeepConvLSTM, and 95.57% for LSTM-CNN, respectively.

Predicting the user’s intended locomotion mode is critical for wearable robot control to assist the user’s seamless transitions when walking on changing terrains. Although machine vision has recently proven to be a promising tool in identifying upcoming terrains in the travel path, existing approaches are limited to environment perception rather than human intent recognition that is essential for coordinated wearable robot operation. Hence, in this study, we aim to develop a novel system that fuses the human gaze (representing user intent) and machine vision (capturing environmental information) for accurate prediction of the user’s locomotion mode. The system possesses multimodal visual information and recognizes user’s locomotion intent in a complex scene, where multiple terrains are present. Additionally, based on the dynamic time warping algorithm, a fusion strategy was developed to align temporal predictions from individual modalities while producing flexible decisions on the timing of locomotion mode transition for wearable robot control. System performance was validated using experimental data collected from five participants, showing high accuracy (over 96% in average) of intent recognition and reliable decision-making on locomotion transition with adjustable lead time. The promising results demonstrate the potential of fusing human gaze and machine vision for locomotion intent recognition of lower limb wearable robots.

The COVID-19 pandemic impacted collaborative activities, travel, and physical contact, increasing the demand for real-time interactions with remote environments. However, the existing remote communication solutions provide limited interactions and do not convey a high sense of presence within a remote environment. Therefore, we propose a snake-shaped wearable telexistence robot, called Piton, that can be remotely used for a variety of collaborative applications. To the best of our knowledge, Piton is the first snake-shaped wearable telexistence robot. We explain the implementation of Piton, its control architecture, and discuss how Piton can be deployed in a variety of contexts. We implemented three control methods to control Piton: HM—using a head-mounted display (HMD), HH—using an HMD and hand-held tracker, and FM—using an HMD and a foot-mounted tracker. We conducted a user study to investigate the applicability of the proposed control methods for telexistence, focusing on body ownership (Alpha IVBO), mental and physical load (NASA-TLX), motion sickness (VRSQ), and a questionnaire to measure user impressions. The results show that both the HM and HH provide relevantly high levels of body ownership, had high perceived accuracy, and were highly favored, whereas the FM control method yielded the lowest body ownership effect and was least favored. We discuss the results and highlight the advantages and shortcomings of the control methods with respect to various potential application contexts. Based on our design and evaluation of Piton, we extracted a number of insights and future research directions to deepen our investigation and realization of wearable telexistence robots. [ABSTRACT FROM AUTHOR]

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