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The performanceof previous machine learning models for gait phase is only satisfactory under limited conditions. First, they produce accurate estimations only when the ground truth of the gait phase (of the target subject) is known. In contrast, when the ground truth of a target subject is not used to train an algorithm, the estimation error noticeably increases. Expensive equipment is required to precisely measure the ground truth of the gait phase. Thus, previous methods have practical shortcoming when they are optimized for individual users. To address this problem, this study introduces an unsupervised domain adaptation technique for estimation without the true gait phase of the target subject. Specifically, a domain-adversarial neural network was modified to perform regression on continuous gait phases. Second, the accuracy of previous models can be degraded by variations in stride time. To address this problem, this study developed an adaptive window method that actively considers changes in stride time. This model considerably reduces estimation errors for walking and running motions. Finally, this study proposed a new method to select the optimal source subject (among several subjects) by defining the similarity between sequential embedding features.

This paper proposes a new version of a variable gravity compensation mechanism (CVGC-II) for mobile manipulation robots such as mobile manipulators and exoskeletons. CVGC-II, which incorporated an energy-free variable mechanism in a smaller design space, exhibited improved performance with a wider range of variable torque. These enhancements were achieved by adopting an optimal curved lever and hybrid spring system. First, the mechanism concept and specifications of the CVGC mechanism are described. Next, the contribution of the curved lever and hybrid spring system to the performance enhancement of CVGC-II is explained. Subsequently, the design methodologies for the main mechanical elements, including the lever, hybrid spring, and cam, are introduced. In the lever design, Hermite spline and B-spline curve model based optimization is performed to generate optimal curved shape of the lever. The hybrid spring system, consisting of compression coil springs and layered leaf springs, helps achieve a wider variable range by maximizing the storable energy in a limited design space. Finally, the enhanced performance of CVGC-II is evaluated experimentally. The results showed that CVGC-II exhibited a 6.8 times wider variable range and energy-free variable mechanism under a 1.5 and 1.3 times smaller size and weight, respectively.

This study proposes the Auto-Fit Dial, which is suitable for high-speed fitting; it includes a function that can wind wire at high speed using an energy storage–release mechanism. The Auto-Fit Dial can store energy in advance in the spiral spring via the rotation of the knob cover, and it releases the stored energy to wind the wire when required by pushing the knob cover. Firstly, the concept design and working principle of the Auto-Fit Dial are explained. Next, a detailed design and structural stability analysis of the mechanical components are described based on the design formula and finite-element analysis. An Auto-Fit Dial prototype is manufactured according to the detailed design with the weight, diameter, and height of 9.7 g, 30.5 mm, and 16.7 mm, respectively. The maximum number of rotations is 5.2 turns, which can wind a wire up to a length of 320 mm. The pulling force applied when the Auto-Fit Dial pulls the wire is initially measured as 5.10 N. The time required to wind a 320 mm wire is 0.015 s, which results in an average speed of 21.33 m/s. Moreover, the Auto-Fit Sleeve is fabricated and applied to the arm sleeve to verify the utility of the Auto-Fit Dial, which combines wire and fabric. Finally, the Auto-Fit Vest is developed by applying a protective vest to the Auto-Fit Dial.

PurposeThe purpose of this research was to develop clothing-typed soft wearable robot embedded with textile-based actuators on ankles for elderly adults needing gait assistance.Design/methodology/approachDesign guidelines were developed and they included function (type, targeting area, routing line and anchor points), design (size/fit, fabric/material, fastener, detail, color) and actuator (shape memory alloy type, size, deformation type, integration material, integration technique and evaluation method). Fabric-based actuator, integration methods to fabrics, routing lines and anchoring points were developed based on the guidelines and evaluated. Then, three long socks types and a pants type were designed and prototyped. Routing line position displacement measurement test was conducted with the prototypes. A survey was conducted to investigate satisfaction, likeness and use intention on the design/prototype to modify the designs.FindingsImportant design factors were identified, and design guidelines for clothing-typed soft wearable robots (SWRs) were developed. People satisfied the developed SWR designs and prototypes with mean scores over 4.60.Originality/valueThe results are expected to be helpful for designers and developers of SWRs in the development process, and they will ultimately be beneficial to members of the elderly population who have gait difficulties.

In this article, we propose a compact variable gravity compensation (CVGC) mechanism with a geometrically optimized lever shape. The CVGC mechanism can be used to generate gravity compensation torque by employing a cam and lever mechanism and can also amplify the gravity compensation torque by varying the pivot point of the lever. Among these advantages, we aimed to maximize the variable ratio of torque generation with an optimized lever. First, the mechanism concept and details of the CVGC mechanism are explained. Next, the conceptual benefit of using a curved lever instead of the original lever is explained. Afterward, the modeling and mechanics of the testbed using a curved lever are presented for force analysis. Based on these mechanics and B-spline curve representation, the methodology for optimizing the curved lever and cam profile design is presented. Finally, the performance of variable gravity compensation using the optimized lever is verified through experiments that compare the designed and measured gravity compensation torque. As we had hoped, the verification test shows that using the optimized curved lever improves the variable ratio from 5.27 to 14.43.

Injuries in the anterior cruciate ligament (ACL), including partial tear and lengthening of the ACL, change the dynamic function of the knee. However, there is a lack of information on the effect of ACL partial tear on knee kinematics during walking. This study aimed to investigate the effects of different levels of ACL injuries on knee stability and ACL tensional force to identify the critical injury level. Motion data of five normal subjects were acquired along with the ground reaction force. A knee model with 14 ligaments was developed using cadaveric specimen data. The initial length and stiffness of the ACL were changed to develop ACL-injured knee models. Musculoskeletal simulations of the knee models were performed using the measured gait data. The average tibial anterior translation increased significantly by 2.6 ± 0.7 mm when the ACL stiffness decreased to 25% of its original stiffness. The average tibial anterior translation increased significantly by 2.6 ± 0.3 mm at an increase in initial length of 10%. The knee with partial ACL tear had a nonlinear decrease in ACL forces owing to the increase in the level of ACL injury, while the knee with ACL lengthening had linear decreased ACL forces. The partial tear of the ACL caused translational instability, while the complete tear caused both rotational and translational instabilities during the musculoskeletal walking simulation. This study presents the effects of partial ACL injuries on joint kinematics and ACL tensional force during the dynamic motion of walking.

Lowering locomotion's metabolic cost Walking and running require different gaits, with each type of motion putting a greater bias on different muscles and joints. Kim et al. developed a soft, fully portable, lightweight exosuit that is able to reduce the metabolic rate for both running and walking by assisting each motion via the hip extension (see the Perspective by Pons). A waist belt holds most of the mass, thus reducing the cost of carrying the suit. By tracking the motion of the user, the suit is able to switch modes between the two types of motion automatically. Science , this issue p. 668 ; see also p. 636

We report copper(II) arsenite (CuAS)-integrated polymer micelles (CuAS-PMs) as a new class of Fenton-like catalytic nanosystem that can display reactive oxygen species (ROS)-manipulating anticancer therapeutic activity. CuAS-PMs were fabricated through metal-catechol chelation-based formation of the CuAS complex on the core domain of poly (ethylene glycol)-b-poly(3,4-dihydroxy-L-phenylalanine) (PEG-PDOPA) copolymer micelles. CuAS-PMs maintained structural robustness under serum conditions. The insoluble state of the CuAS complex was effectively retained at physiological pH, whereas, at endosomal pH, the CuAS complex was ionized to release arsenite and cuprous Fenton catalysts (Cu

In this paper, we propose a one-piece gravity compensation mechanism (OGCM), which improves energy efficiency by compensating for the gravity torque of the target structure using a combination of a cam mechanism and a compression spring. First, the gravity compensation methodology of the OGCM is explained. Next, an analysis of how to design cam mechanisms as a function of the design variables of other mechanical parts is presented. Finally, the gravity compensation performance of the OGCM is verified through experiments by comparing the designed and actual gravity compensation torques. In addition, we simply evaluate the gravity compensation performance of the OGCM visually by testing it on an actual target structure. Both the verification tests show that the OGCM provides decent performance as a gravity compensation mechanism. The proposed OGCM has many advantages. Because it can be constructed as an independent one-piece structure, it can be easily installed on the target platform without many modifications. Moreover, because of its compactness, the size and inertia of the target platform do not increase considerably after installation. The OGCM can also be operated in the entire 360° range, so it does not interfere with the existing workspace of the target platform after installation. Because of these advantages, the OGCM can be used effectively on a variety of platforms and structures.

Previous studies on the optimal operation planning of redundantly actuated parallel mechanisms have focused on optimal torque distribution for a predefined trajectory. However, the optimized result obtained for a predefined trajectory cannot guarantee an optimal operation plan, because the torque distribution ability of a redundantly actuated parallel mechanism is highly dependent on the shape of the end-effector trajectory. Therefore, we can expect the redundantly actuated parallel mechanism performance to be enhanced when both the trajectory and torque distribution are optimized during the optimal operation planning stage. We propose a novel redundantly actuated parallel mechanism optimization procedure that can optimize both the end-effector trajectory and torque distribution. The proposed procedure is composed of two stages of optimizers, i.e. upper- and lower-level optimizers that generate the end-effector trajectory and distribute the torques along the generated trajectory, respectively. Composition of these two stages of the optimization procedure allows optimization of both the trajectory and torque distribution, despite the correlation between them. The proposed optimization procedure is simulated using two types of cost functions. All the simulation results show that the proposed procedure facilitates optimization of the end-effector trajectory and the torque distribution concurrently. Also, the cost function value is minimized to a greater extent than in the result with the optimal torque distribution along the initial trajectory.

For gait phase estimation, time-series data of lower-limb motion can be segmented according to time windows. Time-domain features can then be calculated from the signal enclosed in a time window. A set of time-domain features is used for gait phase estimation. In this approach, the components of the feature set and the length of the time window are influential parameters for gait phase estimation. However, optimal parameter values, which determine a feature set and its values, can vary across subjects. Previously, these parameters were determined empirically, which led to a degraded estimation performance. To address this problem, this paper proposes a new feature extraction approach. Specifically, the components of the feature set are selected using a binary genetic algorithm, and the length of the time window is determined through Bayesian optimization. In this approach, the two optimization techniques are integrated to conduct a dual optimization task. The proposed method is validated using data from five walking and five running motions. For walking, the proposed approach reduced the gait phase estimation error from 1.284% to 0.910%, while for running, the error decreased from 1.997% to 1.484%.

We present a novel haptic interface, named VirtuaPower, having a high-force display capability (FDC) and a wide workspace with a six-degree-of-freedom position measurement and FDC. The overall mechanism of VirtuaPower is designed based on a parallel pair of five-bar mechanisms supporting the end-platform. This novel mechanism enhances the high-FDC and overcomes the problem of small-size workspace, which are the pros and cons of parallel mechanisms, respectively. First, we present the conceptual design and prototype of VirtuaPower. Then, we formulate the forward kinematic and the constraint and space Jacobian. Using these formulations, we analyze two types of workspaces and FDC. In both analyses, VirtuaPower shows remarkable performances, especially in terms of its FDC, compared to other haptic interfaces having an equivalent size. In addition, we validate the static, step, and frequency responses of the force-display performance by performing experiments using the test bench of fixed end setup with a six-dimensional force/torque sensor. Finally, we evaluate the suitability of VirtuaPower as a haptic interface by realizing two types of virtual sphere walls and a virtual reality environment.

In this paper, we propose a new compact variable gravity compensation mechanism (CVGC). The CVGC can be used to generate gravity compensation torque by using the cam and lever mechanism and can also amplify the target gravity compensation torque by varying the pivot point of the lever. The feature of variable gravity compensation is very useful to the mobile platform, which needs to handle unstandardized tasks with a high variation of the workpiece weight. The proposed CVGC has many advantages. Most importantly, it is designed as a compact, independent one-piece structure and is lightweight, meaning it can easily be used as a mobile platform with a simple modification. The CVGC can also have a full range of compensation angle $(360^{\circ})$, so it does not restrict any of the original workspaces of the target platform when it is installed. First, the mechanism concept and details are explained. Next, the mechanics of the prototype for force analysis are presented. Based on these mechanics and cam theory, the methodology of the cam profile design is presented. Finally, the performance of variable gravity compensation is verified through experiments that compare the designed and measured gravity compensation torque. The verification test shows adequate performance, as we had hoped, which shows potential for the development of the CVGC.

A kinematic optimization of a redundantly actuated parallel mechanism is developed via the Taguchi method to maximize the sum of energy efficiency and workspace. In the optimization process, the energy consumption in a representative pathway of a predefined workspace is used as the performance index of the energy efficiency. The horizontal reach and stroke, and the vertical reach of mechanism, are used for the performance index of the workspace. The kinematic parameters of a chain that was added to the proposed non-redundantly actuated parallel mechanism as an extension to achieve redundant actuation are selected as the controllable factors. The velocity of the end-effector is considered to be a noise factor. Because the Taguchi method was originally used for robust optimization, we can improve the energy efficiency and workspace under various velocities for the end-effector. In the first stage of optimization, the number of controllable factors is reduced, and their correlations are eliminated using a response analysis. Quasi-optimized results are derived after the second stage of optimization. The optimized redundantly actuated parallel mechanism result is validated by comparing the energy efficiencies and workspaces of the original and optimal redundantly actuated parallel mechanisms.

This paper shows that redundant actuation can reduce the energy consumption of parallel mechanisms, in some cases by a considerable margin. A theoretical analysis for the energy-saving mechanism is elucidated, and an energy consumption model for a servo-motor system is proposed. Our hypothesis is experimentally verified with a widely used two degree of freedom parallel mechanism design driven by three actuators. Experimental results show that redundant actuation can reduce the electrical energy consumption of the actuators by up to 45% compared to the corresponding nonredundantly actuated version of the mechanism.

Although previous research has improved the energy efficiency of humanoid robots to increase mobility, no study has considered the offset between hip joints to this end. Here, we optimized the offsets of hip joints in humanoid robots via the Taguchi method to maximize energy efficiency. During optimization, the offsets between hip joints were selected as control factors, and the sum of the root-mean-square power consumption from three actuated hip joints was set as the objective function. We analyzed the power consumption of a humanoid robot model implemented in physics simulation software. As the Taguchi method was originally devised for robust optimization, we selected turning, forward, backward, and sideways walking motions as noise factors. Through two optimization stages, we obtained near-optimal results for the humanoid hip joint offsets. We validated the results by comparing the root-mean-square (RMS) power consumption of the original and optimized humanoid models, finding that the RMS power consumption was reduced by more than 25% in the target motions. We explored the reason for the reduction of power consumption through bio-inspired analysis from human gait mechanics. As the distance between the left and right hip joints in the frontal plane became narrower, the amplitude of the sway motion of the upper body was reduced. We found that the reduced sway motion of the upper body of the optimized joint configuration was effective in improving energy efficiency, similar to the influence of the pathway of the body&rsquo, s center of gravity (COG) on human walking efficiency.

Soft exosuits are a new approach for assisting with human locomotion, which applies assistive torques to the wearer through functional apparel. In this paper, we present a new version of autonomous multi-joint soft exosuit for gait assistance, particularly designed for overground walking. The soft exosuit assists with ankle plantarflexion, hip flexion, and hip extension, equally distributing the forces between ankle plantarflexion and hip flexion. A mobile actuation system was developed to generate high assistive forces, and Bowden cables are used to transmit the forces to the exosuit. A sensor harness connects two load cells and three IMU s per leg that are used to measure real-time data for a controller that commands desired force profiles as a function of the walking cycle. In addition, a control adaptation method was developed which adjusts control parameters while walking on irregular surfaces. In preliminary studies, the proposed method substantially improved the force consistency while walking over uneven terrain. Specifically, the number of steps where the peak force deviated from the target force decreased from 100 to 57 out of 250 steps, and RMS error on the peak force decreased from 90.0 N to 76.6 N with respect to 300 N target force. Also, a two-subject case study on country-course walking demonstrated the potential of this soft exosuit to improve human energy economy while walking overground.

We present an autonomous and portable hip-only soft exosuit, for augmenting human walking and running that assists hip extension by delivering peak forces of 300N to the user. Different fixed assistance profiles for walking and running were applied based on an online classification algorithm. The approach is based on the biomechanical understanding that the center of mass potential energy fluctuations during walking and running are out of phase. Specifically, we monitor the vertical acceleration with an abdomen-mounted IMU at the moment of maximum hip extension. Validation is demonstrated with six subjects on the treadmill and with eight subjects outdoors. Our results demonstrated a 99.99% accuracy on average over the fourteen participants for various speeds (0.5 - 4m/s), slopes (−10 −20%), treadmill and overground terrain, loaded (13.6 kg) and unloaded, Exo On and Exo Off conditions, and different shoe types. Results from an evaluation outdoors overground on the energetics of eight subjects demonstrated a significant reduction for running when comparing Exo On to No Exo (3.9%) and for walking and running when comparing Exo On to Exo Off (12.2% and 8.2% respectively). This study represents the first demonstration of an autonomous wearable robot reducing the energy cost of running. Significant variation in response across subjects was observed, highlighting further improvements may be possible via assistance profile individualization with human-in-the-Ioop optimization.

Wall-to-wall transitions, attachment to various materials, and high payload capacity are important requirements for high-rise building cleaning using robots. In this paper, we present a new robotic platform, called the “MultiTrack”, that satisfies these requirements. The MultiTrack employs a multi-linked track mechanism and pneumatic adhesion technology. The MultiTrack can perform wall-to-wall transitions by dexterous motion, can be attached to various materials by suction, and can provide high payload capacity. The robot consists of five driving modules and two connecting links that are connected by six active joints. The center of the robot has a steering suction pad that is used in steering. Each driving module has a caterpillar track with six suction pads. During the rotation of the track, the suction pads are automatically activated or deactivated by mechanical valves and guide rails. The locomotion strategy for wall-to-wall transitions is determined by kinematic analysis. A stability analysis of the worst-case scenario was performed to derive relationships between the required adhesion force and other design parameters. The MultiTrack is 1600 mm × 1000 mm × 300 mm in size, weighs 70 kg, and has a 15-kg payload capacity. It can transit from a floor to a vertical wall and can climb over a thin (130-mm-thick) wall.