After decades of research and development, the United States Army is taking yet another run at developing a powered exoskeleton to help soldiers carry heavy loads on the battlefield--but don't expect a futuristic suit of combat armor straight out of Starship Troopers or Iron Man anytime soon. Soldiers assigned to the Army's 1-78 Field Artillery Battalion training unit at Fort Sill, Oklahoma, recently completed a three-day "proof of concept" evaluation of several off-the-shelf "exoskeleton suits" in late September and early October, officials confirmed to WIRED. The evaluation was overseen by the service's Combat Capabilities Development Command (DEVCOM), the organization responsible for developing new technology for soldiers. Official photos from the evaluation published to social media showed Advanced Individual Training students hauling artillery shells to and from a M109 Paladin self-propelled howitzer and M777-towed howitzer with telltale black exoskeleton harnesses contrasted against their camouflage uniforms, part of a field exercise undertaken "to assess the potential of human augmentation, improve soldier performance, and determine if these exoskeletons meet the demands of our warfighters," as the service put it. While a DEVCOM spokesperson declined to identify which commercially produced systems were evaluated by soldiers, the Army announced its intent in August to award a contract to exoskeleton maker SUITX to "give users experience of advanced soldier augmentation technologies," according to a government notice.

Details of the Model Architecture The detailed encoder architecture is depicted in Figure 7. Some implementation details that we use in the decoder, and the decoder architecture are depicted in Figure 8. We design the grouped 1x1 convolutions to be able to mix channels. For each group, the same number of channels are extracted from one half of the feature map separated by coupling layers and the other half, respectively. Figure 8c shows an example.

This study focuses on enhancing the design of an existing knee exoskeleton by addressing limitations in the range of motion (ROM) during Sit-to-Stand (STS) motions. While current knee exoskeletons emphasize toughness and rehabilitation, their closed-loop mechanisms hinder optimal ROM, which is crucial for effective rehabilitation. This research aims to optimize the exoskeleton design to achieve the necessary ROM, improving its functionality in rehabilitation. This can be achieved by utilizing kinematic modeling and formulation, the existing design was represented in the non-linear and non-convex mathematical functions. Optimization techniques, considering constraints based on human leg measurements, were applied to determine the best dimensions for the exoskeleton. This resulted in a significant increase in ROM compared to existing models. A MATLAB program was developed to compare the ROM of the optimized exoskeleton with the original design. To validate the practicality of the optimized design, analysis was conducted using a mannequin with average human dimensions, followed by constructing a cardboard dummy model to confirm simulation results. The STS motion of an average human was captured using a camera and TRACKER software, and the motion was compared with that of the dummy model to identify any misalignments between the human and exoskeleton knee joints. Furthermore, a prototype of the knee joint exoskeleton is being developed to further investigate misalignments and improve the design. Future work includes the use of EMG sensors for more detailed analysis and better results.

With rapid advancements in exoskeleton hardware technologies, successful assessment and accurate control remain challenging. This study introduces a modular sensor-based system to enhance biomechanical evaluation and control in lower-limb exoskeletons, utilizing advanced sensor technologies and fuzzy logic. We aim to surpass the limitations of current biomechanical evaluation methods confined to laboratories and to address the high costs and complexity of exoskeleton control systems. The system integrates inertial measurement units, force-sensitive resistors, and load cells into instrumented crutches and 3D-printed insoles. These components function both independently and collectively to capture comprehensive biomechanical data, including the anteroposterior center of pressure and crutch ground reaction forces. This data is processed through a central unit using fuzzy logic algorithms for real-time gait phase estimation and exoskeleton control. Validation experiments with three participants, benchmarked against gold-standard motion capture and force plate technologies, demonstrate our system's capability for reliable gait phase detection and precise biomechanical measurements. By offering our designs open-source and integrating cost-effective technologies, this study advances wearable robotics and promotes broader innovation and adoption in exoskeleton research.

Getting the neural interface hooked up to a prosthetic takes two steps. First is surgery involving the portions of muscle that remain after a lower-leg amputation. The operation reconnects shin muscle, which contracts to make the ankle flex upward, to calf muscle, which counteracts this movement. The prosthetic can also be fitted at this point. In addition to enabling the prosthetic to move more dynamically, the procedure can reduce phantom-limb pain, and patients are less likely to trip and fall.

Prosthetic limb abandonment remains an unsolved challenge as amputees consistently reject their devices. Current prosthetic designs often fail to balance human-like perfomance with acceptable device weight, highlighting the need for optimised designs tailored to modern tasks. This study aims to provide a comprehensive dataset of joint kinematics and kinetics essential for performing activities of daily living (ADL), thereby informing the design of more functional and user-friendly prosthetic devices. Functionally required Ranges of Motion (ROM), velocities, and torques for the Glenohumeral (rotation), elbow, Radioulnar, and wrist joints were computed using motion capture data from 12 subjects performing 24 ADLs. Our approach included the computation of joint torques for varying mass and inertia properties of the upper limb, while torques induced by the manipulation of experimental objects were considered by their interaction wrench with the subjects hand. Joint torques pertaining to individual ADL scaled linearly with limb and object mass and mass distribution, permitting their generalisation to not explicitly simulated limb and object dynamics with linear regressors (LRM), exhibiting coefficients of determination R = 0.99 pm 0.01. Exemplifying an application of data-driven prosthesis design, we optimise wrist axes orientations for two serial and two differential joint configurations. Optimised axes reduced peak power requirements, between 22 to 38 percent compared to anatomical configurations, by exploiting high torque correlations between Ulnar deviation and wrist flexion/extension joints. This study offers critical insights into the functional requirements of upper limb prostheses, providing a valuable foundation for data-driven prosthetic design that addresses key user concerns and enhances device adoption.

User-centered evaluations are a core requirement in the development of new user related technologies. However, it is often difficult to recruit sufficient participants, especially if the target population is small, particularly busy, or in some way restricted in their mobility. We bypassed these problems by conducting studies on trade fairs that were specifically designed for our target population (potentially care-receiving individuals in wheelchairs) and therefore provided our users with external incentive to attend our study. This paper presents our gathered experiences, including methodological specifications and lessons learned, and is aimed to guide other researchers with conducting similar studies. In addition, we also discuss chances generated by this unconventional study environment as well as its limitations.

Using lower-limbs exoskeletons provides potential advantages in terms of productivity and safety associated with reduced stress. However, complex issues in human-robot interaction are still open, such as the physiological effects of exoskeletons and the impact on the user's subjective experience. In this work, an innovative exoskeleton, the Wearable Walker, is assessed using the EXPERIENCE benchmarking protocol from the EUROBENCH project. The Wearable Walker is a lower-limb exoskeleton that enhances human abilities, such as carrying loads. The device uses a unique control approach called Blend Control that provides smooth assistance torques. It operates two models simultaneously, one in the case in which the left foot is grounded and another for the grounded right foot. These models generate assistive torques combined to provide continuous and smooth overall assistance, preventing any abrupt changes in torque due to model switching. The EXPERIENCE protocol consists of walking on flat ground while gathering physiological signals such as heart rate, its variability, respiration rate, and galvanic skin response and completing a questionnaire. The test was performed with five healthy subjects. The scope of the present study is twofold: to evaluate the specific exoskeleton and its current control system to gain insight into possible improvements and to present a case study for a formal and replicable benchmarking of wearable robots.

Humans rely on ankle torque to maintain standing balance, particularly in the presence of small to moderate perturbations. Reductions in maximum torque (MT) production and maximum rate of torque development (MRTD) occur at the ankle with age, diminishing stability. Ankle exoskeletons are powered orthotic devices that may assist older adults by compensating for reduced muscle force and power production capabilities. They may also be able to assist with ankle strategies used for balance. However, no studies have investigated the effect of such devices on balance in older adults. Here, we model the effect ankle exoskeletons have on stability in physics-based models of healthy young and old adults, focusing on the mitigation of age-related deficits such as reduced MT and MRTD. We show that an ankle exoskeleton moderately reduces feasible stability boundaries in users who have full ankle strength. For individuals with age-related deficits, there is a trade-off. While exoskeletons augment stability in low velocity conditions, they reduce stability in some high velocity conditions. Our results suggest that well-established control strategies must still be experimentally validated in older adults.

Due to Motor Neurone Diseases, a large population remains disabled worldwide, negatively impacting their independence and quality of life. This typically involves a weakness in the hand and forearm muscles, making it difficult to perform fine motor tasks such as writing, buttoning a shirt, or gripping objects. This project presents a vision-enabled rehabilitation hand exoskeleton to assist disabled persons in their hand movements. The design goal was to create an accessible tool to help with a simple interface requiring no training. This prototype is built on a commercially available glove where a camera and embedded processor were integrated to help open and close the hand, using air pressure, thus grabbing an object. An accelerometer is also implemented to detect the characteristic hand gesture to release the object when desired. This passive vision-based control differs from active EMG-based designs as it does not require individualized training. Continuing the research will reduce the cost, weight, and power consumption to facilitate mass implementation.