Background: Hospital nurses and caregivers are reported to have the highest number of workplace injuries every year, which directly leads to missed days of work, a large amount of compensation costs, and staff shortage issues in the healthcare industry. Hence, this research study provides a new technique to evaluate the risk of injuries for healthcare workers using a combination of unobtrusive wearable devices and digital human technology. The seamless integration of JACK Siemens software and the Xsens motion tracking system was used to determine awkward postures adopted for patient transfer tasks. This technique allows for continuous monitoring of the healthcare worker’s movement which can be obtained in the field. Methods: Thirty-three participants underwent two common tasks: moving a patient manikin from a lying position to a sitting position in bed and transferring the manikin from a bed to a wheelchair. By identifying, in these daily repetitive patient-transfer tasks, potential inappropriate postures that can be conducive to excessive load on the lumbar spine, a real-time monitoring process can be devised to adjust them, accounting for the effect of fatigue. Experimental Result: From the results, we identified a significant difference in spinal forces exerted on the lower back between genders at different operational heights. Additionally, we revealed the main anthropometric variables (e.g., trunk and hip motions) that are having a large impact on potential lower back injury. Conclusions: These results will lead to implementation of training techniques and improvements in working environment design to effectively reduce the number of healthcare workers experiencing lower back pain, which can be conducive to fewer workers leaving the healthcare industry, better patient satisfaction and reduction of healthcare costs.

A large percentage of musculoskeletal disorder cases occur in brewing companies. The aim of this research study is to evaluate the risk of injuries for workers in the local brewing industry by integrating the actual human motion, which was captured by the Xsens MVN Awinda motion tracking system, with the JACK Siemens ergonomics tools. This proposed fusion technology greatly overcomes the time-consuming issue in the traditionally full-body simulation and the posture sensitivity issue in the current digital human modelling (DHM) technology. In this study, the subjects performed a series of daily lifting tasks utilizing 72 kg kegs. The forces exerted on the lower back of brewery workers were fully analyzed. The maximum load applied on the hands for each of the tasks was also estimated to prevent workers from injuries. Additionally, the key factors that highly correlate to lower back injuries were emphasized. Due to the heavy load applied by the kegs, large spinal forces were exerted on the lower back of workers. Moreover, reducing trunk and hip flexion is also important to prevent workers from injuries. The results of this study can greatly improve the implementation of training techniques, environmental modifications, and assistive device design, which aim to eliminate injury risk and increase the productivity of workers within the breweries.

The posture accuracy of full-body dynamic simulation has been successfully evaluated in JACK Siemens software via analyzing two common push and pull tasks. The difference in joint angles between the actual and predicted human movement directly results in the strength of force exposed on the lumbar spine. In this study, the individual factors, such as body height, body weight, trunk and hip flexion, shoulder movement, and muscle strength between genders, have shown a strong association with the adopted postures and exposed spinal forces during task performance. To provide robust ergonomics analysis, these individual variables should be adequately considered in software design for the long-term goal of injury prevention in diverse occupational workplaces.

Wearable devices are becoming ubiquitous and can be used to better estimate postures and movements to reduce the risk of injuries. Thirty-three participants were recruited in this study to perform two daily repetitive patient transfer tasks while the full body movements were acquired using a set of magneto-inertial wearable devices. The use of wearable devices allowed for the estimation of the forces provoked on the lower back during the entire task performance. In postures where the forces exceeded the warning threshold found in the literature, healthcare workers were considered to have a greater risk of injury. Additionally, the maximum force exerted by each hand to avoid injury to the spinal column was also estimated. Knowing the key anthropometric variables associated with musculoskeletal disorders (MSDs) will enable engineers and researchers to design better assistive devices and injury prevention programs in diverse workplaces.

In this study, we are reporting the fabrication of a nanocellulose (NFC) paper-based food indicator for chicken breast spoilage detection by both visual color change observation and smartphone image analysis. The indicator consists of a nanocellulose paper (nanopaper) substrate and a pH-responsive dye, bromocresol green (BCG), that adsorbs on the nanopaper. The nanopaper is prepared through vacuum filtration and high-pressure compression. The nanopaper exhibits good optical transparency and strong mechanical strength. The color change from yellow to blue in the nanopaper indicator corresponding to an increase in the solution pH and chicken breast meat storage data were observed and analyzed, respectively. Further, we were able to use color differences determined by the RGB values from smartphone images to analyze the results, which indicates a simple, sensitive, and readily deployable approach toward the development of future smartphone-based food spoilage tests.

Latent heat thermal energy storage (LHTES) systems can be used to combat the limited collection and long-term storage of renewable energy sources. The key component of an LHTES system is its phase change material (PCM), which thermally stores energy. Despite extensive research on thermal conductivity enhancement within PCM, little attention has been paid to the heat transfer fluid (HTF) within the system. This study aimed to observe the impact of variable HTF flow rates and temperatures on the speed of charging and discharging an LHTES system enhanced with annular fins. Two copper fin configurations of 10 and 20 annular fins were tested within an LHTES system with Rubitherm RT-55 PCM. The configurations were tested during charging processes with HTF parameters of 65 °C and 70 °C at 1, 2, and 3 gpm. Discharging processes were tested with HTF parameters of 15 °C and 20 °C at 0.5, 1, and 1.5 gpm. The system energy response and PCM temperature were recorded throughout the tests. The results of the study revealed that a higher flow rate produced a shorter processing time, but furthermore, that a larger temperature gradient between the PCM and HTF caused a more significant decrease in charging and discharging times.