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The paradigm of Industry 5.0 pushes the transition from the traditional to a novel, smart, digital, and connected industry, where well-being is key to enhance productivity, optimize man–machine interaction and guarantee workers' safety. This work aims to conduct a systematic review of current methodologies for monitoring and analyzing physical and cognitive ergonomics. Three research questions are addressed: (1) which technologies are used to assess the physical and cognitive well-being of workers in the workplace, (2) how the acquired data are processed, and (3) what purpose this well-being is evaluated for. This way, individual factors within the holistic assessment of worker well-being are highlighted, and information is provided synthetically. The analysis was conducted following the PRISMA 2020 statement guidelines. From the sixty-five articles collected, the most adopted (1) technological solutions, (2) parameters, and (3) data analysis and processing were identified. Wearable inertial measurement units and RGB-D cameras are the most prevalent devices used for physical monitoring; in the cognitive ergonomics, and cardiac activity is the most adopted physiological parameter. Furthermore, insights on practical issues and future developments are provided. Future research should focus on developing multi-modal systems that combine these aspects with particular emphasis on their practical application in real industrial settings. [ABSTRACT FROM AUTHOR]

The field of ergonomics has been significantly shaped by the advent of evolving technologies linked to new industrial paradigms, often referred to as Industry 4.0 (I4.0) and, more recently, Industry 5.0 (I5.0). Consequently, several studies have reviewed the integration of advanced technologies for improved ergonomics in different industry sectors. However, studies often evaluate specific technologies, such as extended reality (XR), wearables, artificial intelligence (AI), and collaborative robot (cobot), and their advantages and problems. In this sense, there is a lack of research exploring the state of the art of I4.0 and I5.0 virtual and digital technologies in evaluating work-related biomechanical risks. Addressing this research gap, this study presents a comprehensive review of 24 commercial tools and 10 academic studies focusing on work-related biomechanical risk assessment using digital and virtual technologies. The analysis reveals that AI and digital human modelling (DHM) are the most commonly utilised technologies in commercial tools, followed by motion capture (MoCap) and virtual reality (VR). Discrepancies were found between commercial tools and academic studies. However, the study acknowledges limitations, including potential biases in sample selection and search methodology. Future research directions include enhancing transparency in commercial tool validation processes, examining the broader impact of emerging technologies on ergonomics, and considering human-centred design principles in technology integration. These findings contribute to a deeper understanding of the evolving landscape of biomechanical risk assessment. [ABSTRACT FROM AUTHOR]

The occupational health and safety of agricultural workers is a topic that has a direct impact on the agricultural sector worldwide. For this reason, investigations into ergonomic factors are relevant to the health and safety of agricultural workers. In this study, nine variables of the physical–ergonomic dimension were analyzed to determine which factors represent occupational risks for agricultural workers in Mayo Valley, Mexico. A sample of 200 people was considered. The sample was separated by gender and divided into groups according to age. A closed-ended survey was developed and validated to assess physical ergonomics variables using a five-level Likert scale. Using Principal Component Analysis, it was found that there are physical ergonomic variables that affect male agricultural workers more than female workers (the risk of carrying heavy objects, PE3, and the risk of performing repetitive movements, PE4). It was also found that certain physical ergonomic variables are not perceived as hazardous by agricultural workers (the risk of using inappropriate materials, PE9). In addition, various research findings are discussed to determine the implications and recommendations for improving the occupational health and safety of agricultural workers in Mayo Valley, Mexico. [ABSTRACT FROM AUTHOR]

This review explores human factors and ergonomics (HFE) in the engineering subject areas and analyzes research over the last five years across physical, cognitive, and organizational ergonomics and is associated with the Industrial Revolution era. This review aims to identify existing trends in HFE research related to the Industrial Revolution. This study used a systematic four-step methodology and drew from the Science Direct and Scopus databases. The methodology involves conducting a careful literature search, selecting pertinent and suitable literature references, conducting bibliometric analysis, and participating in qualitative discussions. A total of 353 articles are identified for further analysis. Our findings indicate that the current state of Human Factors and Ergonomics (HFE) research remains largely situated within the research paradigm of the Industrial Revolution 3.0 era. Investigations oriented towards the Industrial Revolution 4.0, such as integrating machine learning and artificial intelligence into physical, cognitive, and organizational ergonomics, are still limited. The insufficient adoption of these advancements underscores the necessity for ongoing development of HFE research to leverage these advancements in order to align with the trajectory towards Industry 4.0. [ABSTRACT FROM AUTHOR]

Introduction: Ergonomics is the scientific study of the interactions between humans and other elements of a system to improve human well-being and overall system performance. In larger scope ergonomics examines human behavioral, psychological, and physiological capabilities and limitations. It has given a huge impact on the workers comfort which directly affects the work efficiency and productivity. In Malaysia, the electronics industry is the leading industry in the manufacturing sector and one of the largest employers. This study was conducted to examine the relationship between ergonomics factors and job performance among employees in electronics industry. Material and Method: A total of 155 employees in electronic industry were involved as respondents in this study. A cross-sectional study was conducted using self-administered questionnaires consisting of sections on physical ergonomics, cognitive ergonomics, and organizational ergonomics and job performance. The data were analysed using SPSS version 25, and descriptive statistics, person correlation and multiple liner regressions were used to identify the factors associated with job performance. Results: The findings showed that there is a significant relationship between ergonomics factors (physical ergonomics, cognitive ergonomics, and organizational ergonomics) and employee performance with p<0.05. While the multiple linear regression analysis found that the most contributing ergonomics factors was physical ergonomics that significantly affects job performance in the electronics industry in Malaysia. Conclusion: Ergonomics factors can be used to promote improved performance and productivity from the employees in the organization such as awareness training and education. [ABSTRACT FROM AUTHOR]

Objective: Assess operator performance in a simulation of US Coast Guard small boat recovery to a larger vessel on a large scale, six degree-of-freedom, full motion simulator. Background: Studies of human performance in small boat recovery task have never been conducted on a high amplitude, low frequency simulator. Empirical evidence of small boat recovery task performance in challenging motion conditions is needed to inform future maritime systems designs. Method: Experienced active-duty boat crewmembers (N = 13) conducted a small boat recovery task in three sea states on the Vertical Motion Simulator (VMS) at the NASA Ames Research Center. Task performance was assessed using a task equivalent for time to complete the task. Participant behaviors associated with increasing motion severity were observed. Results: Task performance declined as motion conditions became more severe. Participants were more likely to use at least one hand to maintain balance during motion conditions, becoming more frequent with increasing motion severity. Many participants used one hand to complete the task despite contrary instructions and previous experience. Conclusion: Two design recommendations were proposed to counter declining task performance in increasingly severe motion conditions. Handholds available to participants during the task, and task design supporting single handed completion were recommended for small boat recovery systems. Application: This research is directly applicable to gross motor tasks requiring simultaneous maintenance of balance in a maritime environment, and may be extended to other environments where humans experience complex motions while completing tasks. [ABSTRACT FROM AUTHOR]

This review explores human factors and ergonomics (HFE) in the engineering subject areas and analyzes research over the last five years across physical, cognitive, and organizational ergonomics and is associated with the Industrial Revolution era. This review aims to identify existing trends in HFE research related to the Industrial Revolution. This study used a systematic four-step methodology and drew from the Science Direct and Scopus databases. The methodology involves conducting a careful literature search, selecting pertinent and suitable literature references, conducting bibliometric analysis, and participating in qualitative discussions. A total of 353 articles are identified for further analysis. Our findings indicate that the current state of Human Factors and Ergonomics (HFE) research remains largely situated within the research paradigm of the Industrial Revolution 3.0 era. Investigations oriented towards the Industrial Revolution 4.0, such as integrating machine learning and artificial intelligence into physical, cognitive, and orga­ni­zational ergonomics, are still limited. The insufficient adoption of these advancements under­scores the necessity for ongoing development of HFE research to leverage these advancements in order to align with the trajectory towards Industry 4.0.

Background: Due to the increasing spread of musculoskeletal problems (MSDs), it is necessary to examine and compare the ergonomic risk factors of the workplace with general and specific methods. The present study was conducted to evaluate the ergonomics of the office work environment using two specific and general evaluation techniques in two universities of medical sciences in the country. Methods: The prevalence of MSDs was evaluated using the Nordic standard questionnaire and the ergonomic assessment of employees in the workplace using ROSA's quick assessment of administrative stress and REBA's quick assessment of the whole body. Descriptive statistics and chi-score, independent t-tests, and logistic regression tests were used to describe and analyze the data. Results: The difference in mean ROSA score and mean monitor height between two groups of employees who have experienced MSDs during the last 12 months and the group who have not experienced them is significant. For one unit increase in ROSA score and one centimeter of monitor height, considering other intervening variables, the chance of MSDs increases by 45% and 13%, respectively. Conclusion: The ROSA tool is a more reliable method to evaluate the ergonomics of the office work environment than REBA. The overall score of the ROSA method and workstation parameters such as monitor height can be used in office jobs to design interventions to reduce MSDs. More studies on the reliability of ROSA are needed to increase the validity of ergonomic interventions based on this method.

This study aims to shed light on the types of ergonomics and the extent of their contribution to improving the performance of workers in the province of liquefied petroleum gas Bashar and this is because the nature of work in the province differs between a closed space and an open one, the descriptive analytical approach was used to describe the phenomena of ergonomics and its types, occupational health and safety and the phenomenon of worker performance, and the questionnaire tool was used in order to answer a set of questions by workers, the results were that the type of Organizational ergonomics has a significant impact on improving workers' performance compared to physical and occupational safety and health dimension has an impact on improving workers' performance in terms of prevention measures and equipment and compliance with strict laws and procedures in order to preserve human and material resources.

The field of ergonomics has been significantly shaped by the advent of evolving technologies linked to new industrial paradigms, often referred to as Industry 4.0 (I4.0) and, more recently, Industry 5.0 (I5.0). Consequently, several studies have reviewed the integration of advanced technologies for improved ergonomics in different industry sectors. However, studies often evaluate specific technologies, such as extended reality (XR), wearables, artificial intelligence (AI), and collaborative robot (cobot), and their advantages and problems. In this sense, there is a lack of research exploring the state of the art of I4.0 and I5.0 virtual and digital technologies in evaluating work-related biomechanical risks. Addressing this research gap, this study presents a comprehensive review of 24 commercial tools and 10 academic studies focusing on work-related biomechanical risk assessment using digital and virtual technologies. The analysis reveals that AI and digital human modelling (DHM) are the most commonly utilised technologies in commercial tools, followed by motion capture (MoCap) and virtual reality (VR). Discrepancies were found between commercial tools and academic studies. However, the study acknowledges limitations, including potential biases in sample selection and search methodology. Future research directions include enhancing transparency in commercial tool validation processes, examining the broader impact of emerging technologies on ergonomics, and considering human-centred design principles in technology integration. These findings contribute to a deeper understanding of the evolving landscape of biomechanical risk assessment.

The paradigm of Industry 5.0 pushes the transition from the traditional to a novel, smart, digital, and connected industry, where well-being is key to enhance productivity, optimize man–machine interaction and guarantee workers’ safety. This work aims to conduct a systematic review of current methodologies for monitoring and analyzing physical and cognitive ergonomics. Three research questions are addressed: (1) which technologies are used to assess the physical and cognitive well-being of workers in the workplace, (2) how the acquired data are processed, and (3) what purpose this well-being is evaluated for. This way, individual factors within the holistic assessment of worker well-being are highlighted, and information is provided synthetically. The analysis was conducted following the PRISMA 2020 statement guidelines. From the sixty-five articles collected, the most adopted (1) technological solutions, (2) parameters, and (3) data analysis and processing were identified. Wearable inertial measurement units and RGB-D cameras are the most prevalent devices used for physical monitoring; in the cognitive ergonomics, and cardiac activity is the most adopted physiological parameter. Furthermore, insights on practical issues and future developments are provided. Future research should focus on developing multi-modal systems that combine these aspects with particular emphasis on their practical application in real industrial settings.

The occupational health and safety of agricultural workers is a topic that has a direct impact on the agricultural sector worldwide. For this reason, investigations into ergonomic factors are relevant to the health and safety of agricultural workers. In this study, nine variables of the physical–ergonomic dimension were analyzed to determine which factors represent occupational risks for agricultural workers in Mayo Valley, Mexico. A sample of 200 people was considered. The sample was separated by gender and divided into groups according to age. A closed-ended survey was developed and validated to assess physical ergonomics variables using a five-level Likert scale. Using Principal Component Analysis, it was found that there are physical ergonomic variables that affect male agricultural workers more than female workers (the risk of carrying heavy objects, PE3, and the risk of performing repetitive movements, PE4). It was also found that certain physical ergonomic variables are not perceived as hazardous by agricultural workers (the risk of using inappropriate materials, PE9). In addition, various research findings are discussed to determine the implications and recommendations for improving the occupational health and safety of agricultural workers in Mayo Valley, Mexico.

Objective: This study evaluated a standing armrest to provide more acceptable ergonomic guidelines that may reduce the cost of standing computer workstations. Background: Of the many advantages of standing workstations, there have been no efforts to minimize the biomechanical cost, such as larger wrist extension and greater forearm muscle activity than sitting. Method: Sixteen participants were asked to perform a typing task under a combination of the following factors: (1) desk shape (rectangular and concave); (2) desk height (0, +5, -5 cm from 90° elbow flexion); and (3) monitor height (0, −10 cm from the eyes). During the trials, the trunk kinematics, muscle activation levels, and CoP were recorded. Results: Both arms were further away from the upper body under the concave and +5 desk height than under the normal condition, but significant decreases in the extensor carpi radialis (8.6%), anterior deltoid (28.8%), and L4 paraspinals (5.5%) were observed. Similarly, the wrist extension angle decreased by 10.5° (42%) under this condition, but the posture required a 2.2° (19%) increase in wrist adduction angle. The CoP irregularity was greater under the concave workstation, indicating more complex motion. Conclusion: A higher and concave desk can provide an armrest effect while engaged in a standing workstation by reducing the wrist extension and related muscle activation level, but at the cost of a larger wrist adduction angle. Application: Providing a standing armrest (+5 cm height and concave desk) could reduce the stresses on the upper extremities, but a split keyboard should be considered to minimize wrist adduction. [ABSTRACT FROM AUTHOR]

Copyright of Knihovna is the property of Library Institute of the Czech National Library and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objective: To investigate the digit force control during a five-digit precision grasp in aligned (AG) and unaligned grasping (UG) configurations. Background: The effects of various cylindrical handles for tools on power grasp performance have been previously investigated. However, there is little information on force control strategy of precision grasp to fit various grasping configurations. Method: Twenty healthy young adults were recruited to perform a lift-hold-lower task. The AG and UG configurations on a cylindrical simulator with force transducers were adjusted for each individual. The applied force and moment, the force variability during holding, and force correlations between thumb and each finger were measured. Result: No differences in applied force, force correlation, repeatability, and variability were found between configurations. However, the moments applied in UG were significantly larger than those in AG. Conclusion: The force control during precision grasp did not change significantly across AG and UG except for the digit moment. The simulator is controlled efficiently with large moment during UG, which is thus the optimal configuration for precision grasping with a cylindrical handle. Further research should consider the effects of task type and handle design on force control, especially for individuals with hand disorders. Application: To design the handle of specific tool, one should consider the appropriate configuration according to the task requirements of precision grasping to reduce the risk of accumulating extra loads on digits with a cylindrical handle. [ABSTRACT FROM AUTHOR]

This study aims to shed light on the types of ergonomics and the extent of their contribution to improving the performance of workers in the province of liquefied petroleum gas Bashar and this is because the nature of work in the province differs between a closed space and an open one, the descriptive analytical approach was used to describe the phenomena of ergonomics and its types, occupational health and safety and the phenomenon of worker performance, and the questionnaire tool was used in order to answer a set of questions by workers, the results were that the type of Organizational ergonomics has a significant impact on improving workers' performance compared to physical and occupational safety and health dimension has an impact on improving workers' performance in terms of prevention measures and equipment and compliance with strict laws and procedures in order to preserve human and material resources. [ABSTRACT FROM AUTHOR]

BACKGROUND: Conducting practical studies in ergonomics requires attention to all aspects of ergonomics with a comprehensive approach and focus on continuous improvement cycles. OBJECTIVE: This study aimed to develop and present an ergonomics management model in the workplace. METHODS: This study was performed using a three-stage Delphi study with 30 experts and a fuzzy analytical hierarchy process. According to the literature review and experts' opinions, the general cycle of the ergonomics management system with eight steps was developed. New methods were formed in two of these eight steps: the 3rd step (developing an ergonomic evaluation method) and the 5th step (creating a cost-benefit evaluation method). RESULTS: The eight implementation steps of the TEMA were determined as follows: 1) Performing task analysis (TTA), 2) Ergonomic hazard identification, 3) Estimating the ergonomic index, 4) Determining control measures, 5) Evaluating cost-benefit parameter, 6) Implementing control measures, 7) Continuous monitoring, and 8) Evaluating the effectiveness of control measures. The Delphi study revealed that the number of deleted parameters includes one item (burnout), and the remaining parameters were 16 items. The mean CVI and CVR values were 0.92 and 0.80, respectively. Cronbach's alpha values for each of the physical, environmental, and cognitive components and the entire model were 0.91, 0.87, 0.85, and 0.89, respectively. CONCLUSION: Using the mentioned management model can be a practical step towards properly evaluating the most critical dimensions of ergonomics in the workplace and optimal planning to implement control measures to establish a dynamic management system to reduce ergonomic risk factors in the workplace. [ABSTRACT FROM AUTHOR]

Manual material handling and load lifting are activities that can cause work-related musculoskeletal disorders. For this reason, the National Institute for Occupational Safety and Health proposed an equation depending on the following parameters: intensity, duration, frequency, and geometric characteristics associated with the load lifting. In this paper, we explore the feasibility of several Machine Learning (ML) algorithms, fed with frequency-domain features extracted from electromyographic (EMG) signals of back muscles, to discriminate biomechanical risk classes defined by the Revised NIOSH Lifting Equation. The EMG signals of the multifidus and erector spinae muscles were acquired by means of a wearable device for surface EMG and then segmented to extract several frequency-domain features relating to the Total Power Spectrum of the EMG signal. These features were fed to several ML algorithms to assess their prediction power. The ML algorithms produced interesting results in the classification task, with the Support Vector Machine algorithm outperforming the others with accuracy and Area under the Receiver Operating Characteristic Curve values of up to 0.985. Moreover, a correlation between muscular fatigue and risky lifting activities was found. These results showed the feasibility of the proposed methodology—based on wearable sensors and artificial intelligence—to predict the biomechanical risk associated with load lifting. A future investigation on an enriched study population and additional lifting scenarios could confirm the potential of the proposed methodology and its applicability in the field of occupational ergonomics. [ABSTRACT FROM AUTHOR]

Objective: The objective is to analytically determine the expected CG and build hardware to measure and verify the suited subject's CG for lunar extravehicular activity (EVA) training in an underwater environment. Background: For lunar EVAs, it is necessary for astronauts to train with a spacesuit in a simulated partial gravity environment. NASA's Neutral Buoyancy Laboratory (NBL) can provide these conditions by producing negative buoyancy for a submerged suited subject. However, it is critical that the center of gravity (CG) for the human-spacesuit system to be accurate for conditions expected during planetary EVAs. Methods: An underwater force-transducer system and individualized human-spacesuit model was created to provide real-time measurement of CG, including recommendations for weight placement locations and quantity of weight needed on the spacesuit to achieve a realistic lunar spacesuit CG. This method was tested with four suited subjects. Results: Across tested weighout configurations, it was observed that an aft and high CG location will have large postural differences when compared to low and fore CG locations, highlighting the importance of having a proper CG. The system had an accuracy of ±5lbs of the total lunar weight and within ± 15 cm for fore-aft and left-right CG directions of the model predictions. Conclusion: The developed method offers analytical verification of the suited subject's CG and improves simulation quality of lunar EVAs. Future suit design can also benefit by recommending hardware changes to create ideal CG locations that improve balance and mobility. Application: The developed methodology can be used to verify a proper CG location in future planetary EVA simulations such as different reduced gravity training analogs (e.g. active cable offloading systems). [ABSTRACT FROM AUTHOR]

Automotive assembly operations require power tools to secure fasteners and these operations have been linked to increased risk of musculoskeletal disorders. This work was designed to develop physical capability limits for direct current right-angle power tool (RAPT) operations using psychophysics. Forty females fastened joints of different hardness's using three fastening strategies, at three fastening frequencies. Participants chose to fasten, independent of orientation, joints up to 89 (10.6) Nm using Atlas Copco's TurboTight®, compared to 51.8 (8.1) Nm using Atlas Copco's Quickstep and 48.6 (10.2) Nm using Stanley's Automatic Tightening Control. The differences between fastening strategies were not as large when fastening soft joints; 59.2 (16.2), 52.3 (14.6), and 53.5 (11.3) Nm, respectively. As fastening frequency increased, participants chose lower target torque magnitudes to fasten. Based on this work, RAPT manufactures can adjust fastening strategies to improve their tool's ergonomics performance. Practitioner summary: Fastening tasks was identified as posing an injury risk to workers performing automotive assembly, yet presently there are no published physical capability limits for direct current right-angle power tool operation. Using a psychophysical methodology, physical capability limits for RAPT fastenings were established for different joint hardness, fastening frequencies and RAPT position/orientation. [ABSTRACT FROM AUTHOR]

Objective: The aim was to review the biomechanical origins of occupational shoulder damage, while considering the complexity of shoulder mechanics and musculoskeletal consequences of diverse task demands. Background: Accessible measures of physical exposures are the primary focus of occupational shoulder assessments and analyses. This approach has led to guidelines and intervention strategies that are often inadequate for mitigating shoulder disorders amongst the complexity of modern workplace demands. Integration of complex shoulder mechanics into occupational assessments, analyses, and interventions is critical for reducing occupational shoulder injury risk. Method: This narrative review describes shoulder biomechanics in the context of common injury mechanisms and consequent injuries, with a particular focus on subacromial impingement syndrome. Several modulators of shoulder injury risk are reviewed, including fatigue, overhead work, office ergonomics considerations, and pushing and pulling task configurations. Results: Relationships between work requirements, muscular demands, fatigue, and biomechanical tissue loads exist. This review highlights that consideration of specific workplace factors should be integrated with our knowledge of the intricate arrangement and interpersonal variability of the shoulder complex to proactively evaluate occupational shoulder demands and exposures. Conclusion: A standard method for evaluating shoulder muscle exposures during workplace tasks does not exist. An integrated approach is critical for improved work design and prevention of shoulder tissue damage and accompanying disability. Application: This review is particularly relevant for researchers and practitioners, providing guidance for work design and evaluation for shoulder injury prevention by understanding the importance of the unique and complex mechanics of the shoulder. [ABSTRACT FROM AUTHOR]

Copyright of Human Factors in Design is the property of Universidade do Estado de Santa Catarina and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Smart workwear systems with embedded inertial measurement unit sensors are developed for convenient ergonomic risk assessment of occupational activities. However, its measurement accuracy can be affected by potential cloth artifacts, which have not been previously assessed. Therefore, it is crucial to evaluate the accuracy of sensors placed in the workwear systems for research and practice purposes. This study aimed to compare in-cloth and on-skin sensors for assessing upper arms and trunk postures and movements, with the on-skin sensors as the reference. Five simulated work tasks were performed by twelve subjects (seven women and five men). Results showed that the mean (±SD) absolute cloth–skin sensor differences of the median dominant arm elevation angle ranged between 1.2° (±1.4) and 4.1° (±3.5). For the median trunk flexion angle, the mean absolute cloth–skin sensor differences ranged between 2.7° (±1.7) and 3.7° (±3.9). Larger errors were observed for the 90th and 95th percentiles of inclination angles and inclination velocities. The performance depended on the tasks and was affected by individual factors, such as the fit of the clothes. Potential error compensation algorithms need to be investigated in future work. In conclusion, in-cloth sensors showed acceptable accuracy for measuring upper arm and trunk postures and movements on a group level. Considering the balance of accuracy, comfort, and usability, such a system can potentially be a practical tool for ergonomic assessment for researchers and practitioners. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to model the effect of body armor coverage on body core temperature elevation and wet-bulb globe temperature (WBGT) offset. Background: Heat stress is a critical factor influencing the health and safety of military populations. Work duration limits can be imposed to mitigate the risk of exertional heat illness and are derived based on the environmental conditions (WBGT). Traditionally a 3°C offset to WBGT is recommended when wearing body armor; however, modern body armor systems provide a range of coverage options, which may influence thermal strain imposed on the wearer. Method: The biophysical properties of four military clothing ensembles of increasing ballistic protection coverage were measured on a heated sweating manikin in accordance with standard international criteria. Body core temperature elevation during light, moderate, and heavy work was modeled in environmental conditions from 16°C to 34°C WBGT using the heat strain decision aid. Results: Increasing ballistic protection resulted in shorter work durations to reach a critical core temperature limit of 38.5°C. Environmental conditions, armor coverage, and work intensity had a significant influence on WBGT offset. Conclusion: Contrary to the traditional recommendation, the required WBGT offset was >3°C in temperate conditions (<27°C WBGT), particularly for moderate and heavy work. In contrast, a lower WBGT offset could be applied during light work and moderate work in low levels of coverage. Application: Correct WBGT offsets are important for enabling adequate risk management strategies for mitigating risks of exertional heat illness. [ABSTRACT FROM AUTHOR]

Physical ergonomics has established itself as a valid strategy for monitoring potential disorders related, for example, to working activities. Recently, in the field of physical ergonomics, several studies have also shown potential for improvement in experimental methods of ergonomic analysis, through the combined use of artificial intelligence, and wearable sensors. In this regard, this review intends to provide a first account of the investigations carried out using these combined methods, considering the period up to 2021. The method that combines the information obtained on the worker through physical sensors (IMU, accelerometer, gyroscope, etc.) or biopotential sensors (EMG, EEG, EKG/ECG), with the analysis through artificial intelligence systems (machine learning or deep learning), offers interesting perspectives from both diagnostic, prognostic, and preventive points of view. In particular, the signals, obtained from wearable sensors for the recognition and categorization of the postural and biomechanical load of the worker, can be processed to formulate interesting algorithms for applications in the preventive field (especially with respect to musculoskeletal disorders), and with high statistical power. For Ergonomics, but also for Occupational Medicine, these applications improve the knowledge of the limits of the human organism, helping in the definition of sustainability thresholds, and in the ergonomic design of environments, tools, and work organization. The growth prospects for this research area are the refinement of the procedures for the detection and processing of signals; the expansion of the study to assisted working methods (assistive robots, exoskeletons), and to categories of workers suffering from pathologies or disabilities; as well as the development of risk assessment systems that exceed those currently used in ergonomics in precision and agility. [ABSTRACT FROM AUTHOR]

The objective of this research was to design and examine a new tool for the removal of chamber lids (manhole covers) called the chamber lid removal tool (CLRT). The CLRT was compared to a pickaxe and J-hook for removing two types of lids using a handheld force meter and an inertial motion capture system. Wearable motion capture was used for monitoring motions in the field. At L4/L5, resultant moment was significantly lower when removing the lids with the CLRT. Significant (p <.05) decreases in resultant moment were observed for the left and right shoulder when using the CLRT. [ABSTRACT FROM AUTHOR]

Manual material handling and load lifting are activities that can cause work-related musculoskeletal disorders. For this reason, the National Institute for Occupational Safety and Health proposed an equation depending on the following parameters: intensity, duration, frequency, and geometric characteristics associated with the load lifting. In this paper, we explore the feasibility of several Machine Learning (ML) algorithms, fed with frequency-domain features extracted from electromyographic (EMG) signals of back muscles, to discriminate biomechanical risk classes defined by the Revised NIOSH Lifting Equation. The EMG signals of the multifidus and erector spinae muscles were acquired by means of a wearable device for surface EMG and then segmented to extract several frequency-domain features relating to the Total Power Spectrum of the EMG signal. These features were fed to several ML algorithms to assess their prediction power. The ML algorithms produced interesting results in the classification task, with the Support Vector Machine algorithm outperforming the others with accuracy and Area under the Receiver Operating Characteristic Curve values of up to 0.985. Moreover, a correlation between muscular fatigue and risky lifting activities was found. These results showed the feasibility of the proposed methodology—based on wearable sensors and artificial intelligence—to predict the biomechanical risk associated with load lifting. A future investigation on an enriched study population and additional lifting scenarios could confirm the potential of the proposed methodology and its applicability in the field of occupational ergonomics.

Objective: The purpose of the study was to examine the effectiveness of a novel supported dynamic lumbar extension with the abdominal drawing-in maneuver (ADIM) technique on stature change, deep abdominal muscle activity, trunk muscle fatigue, and pain intensity during prolonged sitting in chronic low back pain (CLBP) participants.Background: Prolonged sitting can cause trunk muscle fatigue from continuous contraction of deep trunk muscles in seated postures. Deficiency of activity of deep muscles can reduce muscular support of the spine, causing stress on spinal structures, which could result in pain.Method: Thirty participants with CLBP were randomly allocated: (a) control-sitting without exercise, and (b) intervention-supported dynamic lumbar extension with the ADIM technique.Results: Compared to the intervention condition, the control condition demonstrated significantly greater deterioration in stature change, increased levels of deep trunk muscle fatigue, and an increase in pain during prolonged sitting.Conclusion: The supported dynamic lumbar extension with the ADIM technique appears to provide a protective effect on detrimental stature change and deep trunk muscle fatigue. In addition, it prevented an increase in pain intensity during prolonged sitting in people with CLBP.Application: Sedentary behavior harms health, particularly affecting the lower back. Clinicians can use the intervention to induce dynamic lumbar movement, and this exercise can maintain deep trunk muscle activity during prolonged sitting, thereby helping to prevent low back pain (LBP) problems. [ABSTRACT FROM AUTHOR]

Adoption of human–robot collaboration is hindered by barriers in collaborative task design. A new approach for solving these problems is to empower operators in the design of their tasks. However, how this approach may affect user welfare or performance in industrial scenarios has not yet been studied. Therefore, in this research, the results of an experiment designed to identify the influences of the operator’s self-designed task on physical ergonomics and task performance are presented. At first, a collaborative framework able to accept operator task definition via parts’ locations and monitor the operator’s posture is presented. Second, the framework is used to tailor a collaborative experience favoring decision autonomy using the SHOP4CF architecture. Finally, the framework is used to investigate how this personalization influences collaboration through a user study with untrained personnel on physical ergonomics. The results from this study are twofold. On one hand, a high degree of decision autonomy was felt by the operators when they were allowed to allocate the parts. On the other hand, high decision autonomy was not found to vary task efficiency nor the MSD risk level. Therefore, this study emphasizes that allowing operators to choose the position of the parts may help task acceptance and does not vary operators’ physical ergonomics or task efficiency. Unfortunately, the test was limited to 16 participants and the measured risk level was medium. Therefore, this study also stresses that operators should be allowed to choose their own work parameters, but some guidelines should be followed to further reduce MSD risk levels.

Smart workwear systems with embedded inertial measurement unit sensors are developed for convenient ergonomic risk assessment of occupational activities. However, its measurement accuracy can be affected by potential cloth artifacts, which have not been previously assessed. Therefore, it is crucial to evaluate the accuracy of sensors placed in the workwear systems for research and practice purposes. This study aimed to compare in-cloth and on-skin sensors for assessing upper arms and trunk postures and movements, with the on-skin sensors as the reference. Five simulated work tasks were performed by twelve subjects (seven women and five men). Results showed that the mean (±SD) absolute cloth–skin sensor differences of the median dominant arm elevation angle ranged between 1.2° (±1.4) and 4.1° (±3.5). For the median trunk flexion angle, the mean absolute cloth–skin sensor differences ranged between 2.7° (±1.7) and 3.7° (±3.9). Larger errors were observed for the 90th and 95th percentiles of inclination angles and inclination velocities. The performance depended on the tasks and was affected by individual factors, such as the fit of the clothes. Potential error compensation algorithms need to be investigated in future work. In conclusion, in-cloth sensors showed acceptable accuracy for measuring upper arm and trunk postures and movements on a group level. Considering the balance of accuracy, comfort, and usability, such a system can potentially be a practical tool for ergonomic assessment for researchers and practitioners.

Objective: To better study human motion inside the space suit and suit-related contact, a multifactor statistical model was developed to predict torso body shape changes and lumbar motion during suited movement by using fabric strain sensors that are placed on the body. Background: Physical interactions within pressurized space suits can pose an injury risk for astronauts during extravehicular activity (EVA). In particular, poor suit fit can result in an injury due to reduced performance capabilities and excessive body contact within the suit during movement. A wearable solution is needed to measure body motion inside the space suit. Methods: An array of flexible strain sensors was attached to the body of 12 male study participants. The participants performed specific static lumbar postures while 3D body scans and sensor measurements were collected. A model was created to predict the body shape as a function of sensor signal and the accuracy was evaluated using holdout cross-validation. Results: Predictions from the torso shape model had an average root mean square error (RMSE) of 2.02 cm. Subtle soft tissue deformations such as skin folding and bulges were accurately replicated in the shape prediction. Differences in posture type did not affect the prediction error. Conclusion: This method provides a useful tool for suited testing and the information gained will drive the development of injury countermeasures and improve suit fit assessments. Application: In addition to space suit design applications, this technique can provide a lightweight and wearable system to perform ergonomic evaluations in field assessments. [ABSTRACT FROM AUTHOR]

Voice ergonomics considers the load issues and identifies physical and emotional factors that affect voice quality. Therefore, voice ergonomics can be studied in the aspect of a physical load as well as in cognitive and organisational aspects. This study aims to explore the choir conductors' unique individual experience obtained in their professional work with choirs within the context of voice ergonomics. This study was qualitative research, where data were obtained by individual semistructured interviews. The research involved six well-known choir conductors with a long professional experience conducting professional and non-professional choirs of different ages and a broad pedagogical work experience in music. The method of thematic analysis was employed for analysing interview outcomes. Interview answers were structured and analysed in such thematic fields as use of voice and a vocal load, vocal fatigue, body posture, knowledge and understanding about voice ergonomics, organisation of rehearsal processes, and room environment. Conclusion: the main factors affecting the quality of voice sounding were an increased vocal load, fatigue, stress, body posture and air quality of rooms. [ABSTRACT FROM AUTHOR]

Abstract Objectives This study aimed to compare the knowledge attained by third‐year dental students in physical ergonomics altering live lectures and videos in teaching. The second aim was to investigate implementation of the theoretical knowledge on ergonomics into practice. Material and methods Forty‐five students divided into two groups attended a live lecture (45 min) or viewed videos (45 min). After the first teaching session, the groups changed parts. All students answered a questionnaire with 13 true or false‐questions on ergonomics at baseline and immediately after both teaching sessions. Friedman's test and Wilcoxon signed rank test were used to compare questionnaire scores of the student groups. Additionally, we photographed 17 randomly selected students 3 months after baseline during a simulation workshop on endodontics. We analyzed the photographs for ergonomic postures using a specific 12‐point checklist. Results At baseline, no difference in the knowledge between the two groups was discovered, when both scored 72%. After the first teaching session, significant improvement in both groups (p