Estimation of lower back muscle force in a lifting task using wearable IMUs.

Low back pain is commonly reported in occupational settings due to factors such as heavy lifting and poor ergonomic practices, often resulting in significant healthcare expenses and lowered productivity. Assessment tools for human motion and ergonomic risk at the workplace are still limited. Therefore, this study aimed to assess lower back muscle and joint reaction forces in laboratory conditions using wearable inertial measurement units (IMUs) during weight lifting, a frequently high-risk workplace task. Ten able-bodied participants were instructed to lift a 28 lbs. box while surface electromyography sensors, IMUs, and a camera-based motion capture system recorded their muscle activity and body motion. The data recorded by IMUs and motion capture system were used to estimate lower back muscle and joint reaction forces via musculoskeletal modeling. Lower back muscle patterns matched well with electromyography recordings. The normalized mean absolute differences between muscle forces estimated based on measurements of IMUs and cameras were less than 25 %, and the statistical parametric mapping results indicated no significant difference between the forces estimated by both systems. However, abrupt changes in motion, such as lifting initiation, led to significant differences (p < 0.05) between the muscle forces. Furthermore, the maximum L5-S1 joint reaction force estimated using IMU data was significantly lower (p < 0.05) than those estimated by cameras during weight lifting and lowering. The study showed how kinematic errors from IMUs propagated through the musculoskeletal model and affected the estimations of muscle forces and joint reaction forces. Our findings showed the potential of IMUs for in-field ergonomic risk evaluations.

A framework for evaluation and adoption of industrial exoskeletons.

Work-related Musculoskeletal Disorders (WMSDs) account for a significant portion of worker illnesses and injuries, resulting in high costs and productivity losses to employers globally. In recent years, there has been an increased interest in the use of exoskeleton technology to reduce rates of WMSDs in industrial worksites. Despite the potential of exoskeletons to mitigate the risks of WMSDs, the required steps to properly assess and implement the technology for industrial applications are not clear. This paper proposes a framework that can help organizations successfully evaluate and adopt industrial exoskeletons. Through a focus group of industry professionals, researchers, and exoskeleton experts, and by building on existing literature, an overarching adoption framework is developed. The identified stages and tasks within the framework enable an organization to evaluate and adopt exoskeletons through a systematic approach and to identify the existing gaps in their technology adoption process. The findings also highlight the areas where further studies are needed to promote the adoption of industrial exoskeletons, including large-scale field studies and long-term monitoring.

A Dynamic Procedure to Detect Maximum Voluntary Contractions in Low Back.

Surface electromyography (sEMG) is generally used to measure muscles' activity. The sEMG signal can be affected using several factors and vary among individuals and even measurement trials. Thus, to consistently evaluate data among individuals and trials, the maximum voluntary contraction (MVC) value is usually calculated and used to normalize sEMG signals. However, the sEMG amplitude collected from low back muscles can be frequently larger than that found when conventional MVC measurement procedures are used. To address this limitation, in this study, we proposed a new dynamic MVC measurement procedure for low back muscles. Inspired by weightlifting, we designed a detailed dynamic MVC procedure, and then collected data from 10 able-bodied participants and compared their performances using several conventional MVC procedures by normalizing the sEMG amplitude for the same test. The sEMG amplitude normalized by our dynamic MVC procedure showed a much lower value than those obtained using other procedures (Wilcoxon signed-rank test, with p < 0.05), indicating that the sEMG collected during dynamic MVC procedure had a larger amplitude than those of conventional MVC procedures. Therefore, our proposed dynamic MVC obtained sEMG amplitudes closer to its physiological maximum value and is thus more capable of normalizing the sEMG amplitude for low back muscles.

A Systematic Review of Industrial Exoskeletons for Injury Prevention: Efficacy Evaluation Metrics, Target Tasks, and Supported Body Postures.

Industrial workplaces expose workers to a high risk of injuries such as Work-related Musculoskeletal Disorders (WMSDs). Exoskeletons are wearable robotic technologies that can be used to reduce the loads exerted on the body's joints and reduce the occurrence of WMSDs. However, current studies show that the deployment of industrial exoskeletons is still limited, and widespread adoption depends on different factors, including efficacy evaluation metrics, target tasks, and supported body postures. Given that exoskeletons are not yet adopted to their full potential, we propose a review based on these three evaluation dimensions that guides researchers and practitioners in properly evaluating and selecting exoskeletons and using them effectively in workplaces. Specifically, evaluating an exoskeleton needs to incorporate: (1) efficacy evaluation metrics based on both subjective (e.g., user perception) and objective (e.g., physiological measurements from sensors) measures, (2) target tasks (e.g., manual material handling and the use of tools), and (3) the body postures adopted (e.g., squatting and stooping). This framework is meant to guide the implementation and assessment of exoskeletons and provide recommendations addressing potential challenges in the adoption of industrial exoskeletons. The ultimate goal is to use the framework to enhance the acceptance and adoption of exoskeletons and to minimize future WMSDs in industrial workplaces.

Refractive errors and corrections for OCT images in an inflated lung phantom.

Visualization and correct assessment of alveolar volume via intact lung imaging is important to study and assess respiratory mechanics. Optical Coherence Tomography (OCT), a real-time imaging technique based on near-infrared interferometry, can image several layers of distal alveoli in intact, ex vivo lung tissue. However optical effects associated with heterogeneity of lung tissue, including the refraction caused by air-tissue interfaces along alveoli and duct walls, and changes in speed of light as it travels through the tissue, result in inaccurate measurement of alveolar volume. Experimentally such errors have been difficult to analyze because of lack of 'ground truth,' as the lung has a unique microstructure of liquid-coated thin walls surrounding relatively large airspaces, which is difficult to model with cellular foams. In addition, both lung and foams contain airspaces of highly irregular shape, further complicating quantitative measurement of optical artifacts and correction. To address this we have adapted the Bragg-Nye bubble raft, a crystalline two-dimensional arrangement of elements similar in geometry to alveoli (up to several hundred µm in diameter with thin walls) as an inflated lung phantom in order to understand, analyze and correct these errors. By applying exact optical ray tracing on OCT images of the bubble raft, the errors are predicted and corrected. The results are validated by imaging the bubble raft with OCT from one edge and with a charged coupled device (CCD) camera in transillumination from top, providing ground truth for the OCT.