This study evaluated the effects of a back-support exoskeleton on the trunk and hip joint angles, lower back muscle activity and heart rate during four patient handling tasks: assisting a patient from sitting to lying, laterally repositioning the patient and turning the patient in two directions. Eight participants performed these tasks with and without the exoskeleton. Results demonstrated a significant reduction in the lower back muscle activity, but less pronounced effects for other tasks involving minimal trunk flexion. Hip flexion angles were reduced for all tasks when the exoskeleton was worn. The amount of reduction in the muscle activity and changes in the trunk and hip angles varied by task. The exoskeleton did not affect the heart rate across all tasks. The exoskeleton appeared to be more effective in tasks requiring substantial trunk flexion, indicating its potential benefits for reducing lower back muscle strain during such activities.

It is necessary to analyze the whole-body kinematics (including joint locations and joint angles) to assess risks of fatal and musculoskeletal injuries in occupational tasks. Human pose estimation has gotten more attention in recent years as a method to minimize the errors in determining joint locations. However, the joint angles are not often estimated, nor is the quality of joint angle estimation assessed. In this paper, we presented an end-to-end approach on direct joint angle estimation from multi-view images. Our method leveraged the volumetric pose representation and mapped the rotation representation to a continuous space where each rotation was uniquely represented. We also presented a new kinematic dataset in the domain of residential roofing with a data processing pipeline to generate necessary annotations for the supervised training procedure on direct joint angle estimation. We achieved a mean angle error of 7.19° on the new Roofing dataset and 8.41° on the Human3.6M dataset, paving the way for employment of on-site kinematic analysis using multi-view images. © 2023 Elsevier Inc.

Industrial exoskeletons have been used to assist workers during occupational activities, such as overhead work, tool-use, mobility, stooping/squatting, and/or load carrying in various industries. Despite the promise of reducing the risk of work-related musculoskeletal disorders, there is a lack of sufficient evidence to support the safe and effective use of industrial exoskeletons. To assess the merits and residual risks of various types of exoskeletons in different work settings, more comprehensive evaluation procedures are needed. This review study aims to provide an overview of the existing viable and promising methods for evaluating the effectiveness of industrial exoskeletons. The different evaluation methods are organized into three categories-in vitro, in vivo, and in silico studies. The limitations and challenges in different types of evaluation approaches are also discussed. In summary, this review sheds light on choosing appropriate evaluation approaches and may help with decision-making during the development, evaluation, and application of industrial exoskeletons.

The anterior and posterior iliac spine markers frequently used to define the pelvis, are commonly occluded during three-dimensional (3D) motion capture. The occlusion of these markers leads to the use of various tracking marker configurations on the pelvis, which affect kinematic results. The purpose of this investigation was to examine the agreement of CODA pelvis kinematic results when two different tracking marker configurations were used during roofing tasks. 3D motion data were collected on seven male subjects while mimicking two roofing tasks. Hip joint angles (HJAs) were computed using the CODA pelvis with two different tracking marker configurations, the trochanter tracking method (TTM), and virtual pelvis tracking method (VPTM). Agreement between tracking marker configurations was assessed using cross-correlations, bivariate correlations, mean absolute differences (MADs), and Bland-Altman (BA) plots. The correlations displayed no time lag and strong agreement (all r>0.83) between the HJA from the VPTM and TTM, suggesting the timing occurrence of variables are comparable between the two tracking marker configurations. The MAD between the VPTM and TTM displayed magnitude differences, but most of the differences were within a clinically acceptable range. Caution should still be used when comparing kinematic results between various tracking marker configurations, as differences exist. © 2023 World Scientific Publishing Company.

Residential roofers are often exposed to awkward postures and motions in a prolonged time, which may not only reduce their body stability and increase fall potential, but also increase the risk of musculoskeletal disorders (MSDs). To assess their risks of fatal and musculoskeletal injuries, it is crucial to capture 3D body poses of workers during roofing tasks. In this paper, we proposed a novel two-stage motion estimation approach based on a convolution neural network to estimate residential roofer’s body poses using three-view video data. Our approach includes two stages: (1) use of an offline multi-view model to estimate the 3D pose in a single frame; (2) use of a multi-frame model to apply temporal convolutions to refine the multi-view outputs. The performance of the approach was evaluated by comparing our estimation with the gold-standard marker-based 3D human pose during one of the common residential roofing tasks–shingle installation. The evaluation results show that the proposed multi-frame model can effectively improve the accuracy of the coordinate sequence. Moreover, these results prove that the proposed video-based motion estimation approach can efficiently and accurately locate 3D body joints and pave the way for future onsite motion analysis during roofing activities. © This work was authored as part of the Contributor’s official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.

Musculoskeletal Disorders (MSDs) remain a major concern for workers in the healthcare industry. Healthcare workers are at high risk of work-related MSDs mainly caused by overexertion from manually handling patients. Exoskeletons may be a useful tool to help reduce the risk of MSDs during patient handling. As a review study, we surveyed articles focusing on applying exoskeletons to patient handling tasks specifically. We also reviewed relevant government databases and other studies related to Safe Patient Handling and Mobility (SPHM) programs and exoskeleton applications in general. The exoskeletons specifically designed for patient handling were found to be sparse. To have a better understanding of the needs and challenges of developing and using exoskeletons for reducing risks of work-related MSDs in healthcare workers during patient handling, this critical review (1) provided an overview of the existing issues and projected future burdens related to work-related MSDs during patient handling tasks, (2) recognized current and potential roles and applications of existing exoskeletons, and (3) identified challenges and needs for future exoskeleton products. In conclusion, we do not expect exoskeletons to replace the existing SPHM programs, but rather play a complementary role to these multi-pronged programs. We expect that emerging exoskeleton products can be introduced to uncontrolled or specialized healthcare environments. There are various expectations and requirements for an exoskeleton used in different healthcare settings. Additionally, introducing certain types of exoskeletons for patients to assist them during treatment and rehabilitation may help reduce the MSD risks to the healthcare workers. 2022