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Exoskeletons and exosuits (collectively termed EXOs) have the potential to reduce the risk of work-related musculoskeletal disorders (WMSDs) by protecting workers from exertion and muscle fatigue due to physically demanding, repetitive, and prolonged work in construction workplaces. However, the use of EXOs in construction is in its infancy, and much of the knowledge required to drive the acceptance, adoption, and application of this technology is still lacking. The objective of this research is to identify the facilitators, barriers, and corresponding solutions to foster the adoption of EXOs in construction workplaces through a sequential, multistage Delphi approach. Eighteen experts from academia, industry, and government gathered in a workshop to provide insights and exchange opinions regarding facilitators, barriers, and potential solutions from a holistic perspective with respect to business, technology, organization, policy/regulation, ergonomics/safety, and end users (construction-trade professionals). Consensus was reached regarding all these perspectives, including top barriers and potential solution strategies. The outcomes of this study will help the community gain a comprehensive understanding of the potential for EXO use in the construction industry, which may enable the development of a viable roadmap for the evolution of EXO technology and the future of EXO-enabled workers and work in construction workplaces.

The real-world measurement of minimum foot clearance (mFC) during the swing phase of gait is critical in efforts to understand and reduce the risk of trip-and-fall incidents in populations with gait impairments. Past research has focused on measuring clearance of a single point on a person’s foot, typically the toe—however, this may overestimate mFC and may even be the wrong region of the foot in cases of gait impairments or interventions. In this work, we present a novel method to reconstruct the swing-phase trajectory of an arbitrary number of points on a person’s shoe and estimate the instantaneous height and location of whole-foot mFC. This is achieved using a single foot-mounted inertial sensor and personalized shoe geometry scan, assuming a rigid-body IMU-shoe system. This combination allows collection and analysis using out-of-lab tests, potentially including clinical environments. Validation of single marker location using the proposed method vs. motion capture showed height errors with bias less than 0.05 mm, and 95% confidence interval of − 8.18 to + 8.09 mm. The method is demonstrated in an example data set comparing different interventions for foot drop, and it shows clear differences among no intervention, functional electrical stimulation, and ankle–foot orthosis conditions. This method offers researchers and clinicians a rich understanding of a person’s gait by providing objective 3D foot kinematics and allowing a unique opportunity to view the regions of the foot where minimum clearance occurs. This information can contribute to a more informed recommendation of specific interventions or assistive technology than is currently possible in standard clinical practice. [ABSTRACT FROM AUTHOR]

Frontal plane ankle motion is important for balance in walking but is seldom controlled in robotic prostheses. This article describes the design, control and performance of a semi-active two-degree-of-freedom robotic prosthetic ankle. The mechanism uses a non-backdrivable wedge cam system based on rotating inclined planes, allowing actuation only during swing phases for low power, light weight and compactness. We present details of the mechanism and its kinematic and mechatronic control, and a benchtop investigation of the system's speed and accuracy in ankle angle control. The two-axis ankle achieves angular reorientation movements spanning ±10 deg in any direction in less than 0.9 s. It achieves a plantarflexion/dorsiflexion error of 0.35 ± 0.27 deg and an inversion/eversion error of 0.29 ± 0.25 deg. Backdriven motion during walking tests is negligible. Strengths of the design include self-locking behavior for low power and simple kinematic control. Two-axis ankle angle control could enable applications such as balance augmentation, turning assistance, and wearable perturbation training. [ABSTRACT FROM AUTHOR]

Motion reconstruction using wearable sensors enables broad opportunities for gait analysis outside laboratory environments. Inertial Measurement Unit (IMU)-based foot trajectory reconstruction is an essential component of estimating the foot motion and user position required for any related biomechanics metrics. However, limitations remain in the reconstruction quality due to well-known sensor noise and drift issues, and in some cases, limited sensor bandwidth and range. In this work, to reduce drift in the height direction and handle the impulsive velocity error at heel strike, we enhanced the integration reconstruction with a novel kinematic model that partitions integration velocity errors into estimates of acceleration bias and heel strike vertical velocity error. Using this model, we achieve reduced height drift in reconstruction and simultaneously accomplish reliable terrain determination among level ground, ramps, and stairs. The reconstruction performance of the proposed method is compared against the widely used Error State Kalman Filter-based Pedestrian Dead Reckoning and integration-based foot-IMU motion reconstruction method with 15 trials from six subjects, including one prosthesis user. The mean height errors per stride are 0.03 ± 0.08   c m on level ground, 0.95 ± 0.37   c m on ramps, and 1.27 ± 1.22   c m on stairs. The proposed method can determine the terrain types accurately by thresholding on the model output and demonstrates great reconstruction improvement in level-ground walking and moderate improvement on ramps and stairs. [ABSTRACT FROM AUTHOR]

Introduction: Simulations based on computational musculoskeletal models are powerful tools for evaluating the effects of potential biomechanical interventions, such as implementing a novel prosthesis. However, the utility of simulations to evaluate the effects of varied prosthesis design parameters on gait mechanics has not been fully realized due to the lack of a readily-available limb loss-specific gait model and methods for efficiently modeling the energy storage and return dynamics of passive foot prostheses. The purpose of this study was to develop and validate a forward simulation-capable gait model with lower-limb loss and a semi-active variable-stiffness foot (VSF) prosthesis. Methods: A seven-segment 28-DoF gait model was developed and forward kinematics simulations, in which experimentally observed joint kinematics were applied and the resulting contact forces under the prosthesis evolved accordingly, were computed for four subjects with unilateral below-knee amputation walking with a VSF. Results: Model-predicted resultant ground reaction force (GRFR) matched well under trial-specific optimized parameter conditions (mean R²: 0.97, RMSE: 7.7% body weight (BW)) and unoptimized (subject-specific, but not trial-specific) parameter conditions (mean R²: 0.93, RMSE: 12% BW). Simulated anterior-posterior center of pressure demonstrated a mean R² = 0.64 and RMSE = 14% foot length. Simulated kinematics remained consistent with input data (0.23 deg RMSE, R² > 0.99) for all conditions. Conclusions: These methods may be useful for simulating gait among individuals with lower-limb loss and predicting GRFR arising from gait with novel VSF prostheses. Such data are useful to optimize prosthesis design parameters on a user-specific basis. [ABSTRACT FROM AUTHOR]

Lower limb amputation has been associated with secondary impairments such as knee osteoarthritis in the uninvolved limb. Greater knee loading in the frontal plane has been related to severity and rate of progression in knee osteoarthritis. Reduced push-off work from the involved limb can increase uninvolved limb knee loading. However, little is known about specific effects that prosthetic foot damping may have on uninvolved limb loading. We hypothesized that uninvolved limb peak knee internal abduction moment (IAM) and loading rates would be greater when using a high-damping foot compared with a low-damping foot, across walking speeds. Eight healthy, young subjects walked in a prosthesis simulator boot using the experimental feet. Greater uninvolved limb first peak IAM (+16% in fast speed, P = .002; +11% in slow speed, P = .001) and loading rates (+11% in fast speed, P = .003) were observed when using the high-damping foot compared with low-damping foot. Within each foot, uninvolved limb first peak IAM and loading rates had a trend to increase with increased walking speed. These findings suggest that damping properties of prosthetic feet are related to uninvolved limb peak knee IAM and loading rates. [ABSTRACT FROM AUTHOR]

Passive energy storage and return (ESR) feet are current performance standard in lower limb prostheses. A recently developed semi-active variable-stiffness foot (VSF) prosthesis balances the simplicity of a passive ESR device with the adaptability of a powered design. The purpose of this study was to model and simulate the ESR properties of the VSF prosthesis. The ESR properties of the VSF were modeled as a lumped parameter overhung beam. The overhung length is variable, allowing the model to exhibit variable ESR stiffness. Foot-ground contact was modeled using sphere-to-plane contact models. Contact parameters were optimized to represent the geometry and dynamics of the VSF and its foam base. Static compression tests and gait were simulated. Simulation outcomes were compared to corresponding experimental data. Stiffness of the model matched that of the physical VSF (R²: 0.98, root-mean-squared error (RMSE): 1.37 N/mm). Model-predicted resultant ground reaction force (GRFR) matched well under optimized parameter conditions (R²: 0.98, RMSE: 5.3% body weight,) and unoptimized parameter conditions (R2: 0.90, mean RMSE: 13% body weight). Anterior-posterior center of pressure matched well with R² > 0.94 and RMSE < 9.5% foot length in all conditions. The ESR properties of the VSF were accurately simulated under benchtop testing and dynamic gait conditions. These methods may be useful for predicting GRFR arising from gait with novel prostheses. Such data are useful to optimize prosthesis design parameters on a user-specific basis. [ABSTRACT FROM AUTHOR]