An ergonomic evaluation using a deep learning approach for assessing postural risks in a virtual reality-based smart manufacturing context

This study proposes an integrated ergonomic evaluation designed to identify unsafe postures, whereby postural risks during industrial work are assessed in the context of virtual reality-based smart manufacturing. Unsafe postures were recognised by identifying the displacements of the centre of mass (COM) of body keypoints using a computer vision-based deep learning (DL) convolutional neural network approach. The risk levels for the identified unsafe postures were calculated using ergonomic risk assessment tools rapid upper limb assessment and rapid whole-body assessment. An analysis of variance was conducted to determine significant differences between the vertical and horizontal directions of postural movements associated with the most unsafe postures. The findings assess the ergonomic risk levels and identify the most unsafe postures during industrial work in smart manufacturing using DL method. The identified postural risks can help industry managers and researchers acquire a better understanding of unsafe postures.

Spatial relationship-aware rapid entire body fuzzy assessment method for prevention of work-related musculoskeletal disorders

In the advent of Industry 5.0, advances in human-centered smart manufacturing (HSM) accentuate the role of humans in human-machine collaboration. This development has catapulted human health in human-machine systems to the forefront of the conversation. Although various tools have emerged to mitigate work-related musculoskeletal disorders (WMSDs), combining biomechanics with human morphology, the extant methods primarily hinge on expert scoring. Such methods display a step-wise change between risk levels, yielding inadequate assessment accuracy and posing challenges to human health assurance in HSM. To address these issues, this study proposes a spatial relationship-aware rapid entire body fuzzy assessment technique. The proposed method enhances the rapid entire body assessment (REBA) by enacting a dynamic evaluation of WMSD-related risk via a deep learning-based 3D pose reconstruction. Contrary to the step-wise transitions between REBA's different risk levels, the proposed method actualizes a fuzzy assessment of WMSD risk by introducing weights between these levels. This innovation allows for a more accurate risk assessment for workers engaged in HSM. Validation through experiments conducted on data from an automobile production line demonstrates that the proposed method can achieve a precision rate of 99.31%. Demo videos and code are available at https://github.com/giim-hf-lab/REBA-PLUS.

Compensation Method for Missing and Misidentified Skeletons in Nursing Care Action Assessment by Improving Spatial Temporal Graph Convolutional Networks

With the increasing aging population, nursing care providers have been facing a substantial risk of work-related musculoskeletal disorders (WMSDs). Visual-based pose estimation methods, like OpenPose, are commonly used for ergonomic posture risk assessment. However, these methods face difficulty when identifying overlapping and interactive nursing tasks, resulting in missing and misidentified skeletons. To address this, we propose a skeleton compensation method using improved spatial temporal graph convolutional networks (ST-GCN), which integrates kinematic chain and action features to assess skeleton integrity and compensate for it. The results verified the effectiveness of our approach in optimizing skeletal loss and misidentification in nursing care tasks, leading to improved accuracy in calculating both skeleton joint angles and REBA scores. Moreover, comparative analysis against other skeleton compensation methods demonstrated the superior performance of our approach, achieving an 87.34% REBA accuracy score. Collectively, our method might hold promising potential for optimizing the skeleton loss and misidentification in nursing care tasks.

Work-Related Musculoskeletal Disorders Risk Assessment during Manual Lymphatic Drainage with Compressive Bands among Physiotherapists

BACKGROUND

Complete decongestive therapy is the standard treatment for lymphedema. Manual lymphatic drainage and short-stretch multilayer compression bandaging are two daily stages of complete decongestive therapy during which physiotherapists work with patients.

OBJECTIVE

The aim of this study was to assess the risks of musculoskeletal disorders to which physiotherapists are exposed during these two phases.

METHOD

Five physiotherapists performed five 20 min manual lymphatic drainages, followed by the compression bandaging phase. From the video recordings, 8477 postures defined by 13 joint angles were grouped into clusters using hierarchical cluster analysis. The risk of musculoskeletal disorders in physiotherapists' postures was assessed using ergonomic tools.

RESULTS

Seven clusters, called generic postures (GP), were identified and defined throughout the mean joint angle values and standard deviation. Four seated GPs were found for the drainage phase, and three standing GPs were identified for the bandaging phase. This phase corresponded to a quarter of the total duration. The GP's ergonomic scores ranged from 4.51 to 5.63 and from 5.08 to 7.12, respectively, for the Rapid Upper Limb Assessment (RULA) and Rapid Entire Body Assessment (REBA). GP1, GP3, and GP4 presented the highest ergonomic scores (RULA scores: 5.27 to 5.63; REBA scores: 6.25 to 7.12). The most affected areas were the neck (flexion > 20° for all GPs), trunk (flexion between 25 and 30° for GP2, and GP7 during the bandaging phase and GP4 during the drainage phase), and shoulder (flexion and abduction >20° for all GPs except GP5).

CONCLUSIONS

These results highlighted that the two complete decongestive therapy phases could be described as a combination of GP. Ergonomic assessment showed that compression bandaging as well as drainage phases expose physiotherapists to moderate musculoskeletal disorder risks that require "further investigation and change soon".

A Neural Networks Approach to Determine Factors Associated With Self-Reported Discomfort in Picking Tasks

OBJECTIVE

A neural networks approach has been proposed to handle various inputs such as postural, anthropometric and environmental variables in order to estimate self-reported discomfort in picking tasks. An input reduction method has been proposed, reducing the input variables to the minimum data required to estimate self-reported discomfort with similar accuracy as the neural network fed with all variables.

BACKGROUND

Previous works have attempted to explore the relationship between several factors and self-reported discomfort using observational methods. The results showed that this relationship was not a simple linear relationship. Another study used neural networks to model the function returning reported discomfort according to static posture, age, and anthropometrics variables. The results demonstrated the model's ability to predict reported discomfort. But all the available variables were used to design the neural network.

METHOD

Eleven subjects carried-out picking tasks with various masses (0, 1, 3 kg) and imposed duration (5, 10, or 15 s). Continuous REBA score, anthropometric and environmental data were computed, and subjects' discomfort were collected. The data set of this work consisted in the computed continuous REBA score, anthropometric, environmental data and collected subjects' discomfort.

RESULTS

The results showed that the correlation between the estimated and experimental tested data was equal to 0.775 when using all the 14 available variables. After data reduction, only 6 variables were left, with a very close performance when predicting discomfort.

CONCLUSION

A neural network approach has been proposed to estimate self-reported discomfort according to a minimum set of postural, anthropometric and environmental variables in picking tasks.

APPLICATION

This method has the potential to support ergonomists in workstation designing processes, by adding discomfort prediction to virtual manikins' behaviors in simulation tools.

Ergonomic risk assessment of working postures of nurses working in a medical faculty hospital with REBA and RULA methods

The aim of the study is to reach objective results about the ergonomic risks of nurses' working postures not only by using questionnaires but also by using Rapid Entire Body Assessment (REBA) and Rapid Upper Limb Assessment (RULA) methods, which are risk assessment methods used in engineering fields. This study is a cross-sectional study. First of all, 383 nurses were evaluated with a survey. 91.4% of the nurses were women and 6.5% were men. Average age (female: 38.20; male: 31.5), average weight (female: 65.60 kg; male: 81.50 kg), average height (female: 162.7 cm; male: 176.80 cm) and average body mass index (female: 24.80; male: 26) were calculated. In the hospital, which we grouped into in the hospital, which we divided into eight workstations, the REBA and RULA scores of the three nurses working at each workstation were calculated and the average REBA and RULA scores of the workstations were determined. The percentage of those who experienced musculoskeletal pain in the last 1 year at each workstation and the mean REBA-RULA scores were as follows; ward (92%; 6.92-5.69), operating room (98%; 10-7), emergency department (100%; 6.08-5.33), outpatient clinic (75%; 5.5-5.16), intensive care (94%; 6.21-5.57), administrative affairs (94%; 5-5), laboratory (95%; 5.80-5.2) and interventional procedure (92%; 6.4-5.4). In these stations, the highest scores were seen in the operating room. In the questionnaire, 92.46% of the nurses reported having complaints in at least one part of the musculoskeletal system in the last year. The hospital weighted mean score was REBA 6.86 and RULA 5.71. When REBA and RULA measurements were evaluated, it was determined that the risk in the departments where the nurses worked was generally at the medium risk level. REBA and RULA scores indicate that ergonomic changes and adjustments should be made. For this determination, the risks of working postures should be determined with quantitative methods.

Beyond Magnification and Illumination: Ergonomics with a 3D Exoscope in Lumbar Spine Microsurgery to Reduce Musculoskeletal Injuries

OBJECTIVE

The risk of musculoskeletal injuries (MSIs) increases over years of practice which may lead to career-ending among surgeons. Exoscopes represent a new generation of imaging systems that help surgeons operate in a more comfortable posture. This article aimed to assess advantages and limitations, especially ergonomics with a 3D exoscope in lumbar spine microsurgery versus an operating microscope (OM) to reduce MSIs.

METHODS

From March 2018 to May 2020, 90 patients with lumbar disc herniation undergoing a single-level minimally invasive transforaminal lumbar interbody fusion (MIS-TLIF) procedure were included. Forty-seven patients were operated with the assistance of the exoscope and 43 patients were operated with the assistance of the OM. Clinical data, magnification, and illumination were evaluated. In particular, the ergonomics of surgeons was evaluated by a questionnaire (subjective) and a rapid entire body assessment (REBA; objective).

RESULTS

The postoperative outcomes were reasonably well balanced between the two groups. The handling of the exoscope was comparable to that of the OM. The depth perception, image quality, and illumination of the exoscope were inferior to those of the OM in MIS-TLIF with long and deep approaches. The educational and training function of the exoscope was superior to that of the OM. Importantly, surgeons rated the ergonomics of the exoscope as very high on the questionnaire and the REBA to the OM (P = 0.017).

CONCLUSIONS

This study showed that the exoscope was a safe and effective alternative to the OM for assisting the MIS-TLIF procedure with the unique advantage of ergonomics to reduce musculoskeletal injuries.

Assessment of risk of musculoskeletal discomforts in physiotherapists treating neurological patients: A pilot study

Background

Musculoskeletal disorders (MSDs) are conditions that are caused and/or aggravated by work. The most important reason behind work-related musculoskeletal disorder is abnormal and/or stressful position of joints while working. Physiotherapists are very much prone to develop work-related musculoskeletal disorders, especially while treating neurologically challenged patients. Postural assessment is a key to identify a person at risk of developing work-related musculoskeletal disorders. Proper assessment of some of the areas like neck, spine, upper and lower extremities is the key to get risk factor analysis. REBA (Rapid Entire Body Assessment) is a tool which can be used on field to quantify areas of the body which are more likely to develop work-related musculoskeletal disorders.

Aims

To find out risk of MSDs among physiotherapists treating neurologically challenged patients.

Study Setting and Design

At neuro-paediatric department of SBB College of Physiotherapy, an observational pilot study was conducted.

Materials and Methods

Photographs of the participants were captured with their consent through smart phone camera during treatment of different patients both adult and paediatric. Selected postures were analysed and quantified based on the REBA sheet.

Statistical Analysis

Descriptive analysis was done based on areas at higher risk for MSDs according to REBA sheet.

Results

More than 50% of participants were at moderate to high risk of developing MSDs.

Conclusion

Physiotherapists working with neurological patients were found to be at high to medium risk of work-related musculoskeletal disorders. There is a need to assess MSD risk in detail in all physiotherapists.

Risk factors of musculoskeletal disorders in loading and unloading tasks of couriers

BACKGROUND

The use of home delivery services has expanded due to coronavirus disease - 2019, and couriers' high level of work intensity has become a severe social issue in various nations.

OBJECTIVE

This study investigates the risk factors of musculoskeletal disorders (MSDs) caused by frequent loading and unloading actions, known to be the most demanding tasks for couriers.

METHODS

A self-report survey and post-hoc interview were employed to collect personal information, task frequency, and the incidence of MSDs. Frequent actions during loading and unloading packages were identified, and the Rapid Entry Body Assessment (REBA) and National Institute for Occupational Safety and Health (NIOSH) lifting equations were assessed.

RESULTS

Approximately 29.5% of the 44 subjects suffered from MSDs, and identify the types of actions that frequently occur during loading and unloading packages. According to the REBA survey, 60% of the responses for both loading and unloading are distributed within the risk range of 8-13 points, suggesting a high risk (mean REBA score: 8.8 (loading), 8.5 (unloading)). In every case, NIOSH determined that the lifting index (LI) was harmful (mean LI: 1.62). Thereby, the bending or twisting posture of the hands and neck, long horizontal distance between the packages and the body, and high lifting frequency were identified as major problems.

CONCLUSION

The study identified a very high level of musculoskeletal risk for couriers, and the detailed working methods and body parts vulnerable to MSDs.

Analysis of the Reduction of Ergonomic Risks through the Implementation of an Automatic Tape Packaging Machine

Many industrial sectors still lack automation resources to optimize their production processes, aiming to make manufacturing leaner and offer better working conditions to operators. Without these improvements, workers can suffer physical and even psychological damage from the ergonomic risks of the activities performed. Thus, the aim of this paper is to present the ergonomic evaluation of packaging tapes workstation before and after the implementation of an automatic packaging machine, called Guzzetti. In the Guzzetti context, the paper shows the implementation of an electrical system based on controlling a mechanical device powered by servomotors and controlled by a PLC is necessary. For ergonomic evaluation, the paper presents the application of three methods: Suzanne Rodger, Strain Index, called Moore and Garg and REBA (Rapid Entire Body Assessment). With the results collection, was possible to obtain improvements in ergonomic risks that changed from the intermediate level to low level in all methods.

Accuracy Assessment of Joint Angles Estimated from 2D and 3D Camera Measurements

To automatically evaluate the ergonomics of workers, 3D skeletons are needed. Most ergonomic assessment methods, like REBA, are based on the different 3D joint angles. Thanks to the huge amount of training data, 2D skeleton detectors have become very accurate. In this work, we test three methods to calculate 3D skeletons from 2D detections: using the depth from a single RealSense range camera, triangulating the joints using multiple cameras, and combining the triangulation of multiple camera pairs. We tested the methods using recordings of a person doing different assembly tasks. We compared the resulting joint angles to the ground truth of a VICON marker-based tracking system. The resulting RMS angle error for the triangulation methods is between 12° and 16°, showing that they are accurate enough to calculate a useful ergonomic score from.

Systematic Comparison of OWAS, RULA, and REBA Based on a Literature Review

This study aimed to systematically compare three representative observational methods for assessing musculoskeletal loadings and their association with musculoskeletal disorders (MSDs): Ovako Working Posture Analysis System (OWAS), Rapid Upper Limb Assessment (RULA), and Rapid Entire Body Assessment (REBA). The comparison was based on a literature review without time limitations and was conducted on various factors related to observational methods. The comparisons showed that although it has a significant limitation of comprising only two classifications for the leg postures, (1) the RULA is the most frequently used method among the three techniques; (2) many studies adopted the RULA even in evaluation of unstable lower limb postures; (3) the RULA assessed postural loads as higher risk levels in most studies reviewed in this research; (4) the intra- and inter-reliabilities for the RULA were not low; and (5) the risk levels assessed by the RULA were more significantly associated with postural load criteria such as discomfort, MHTs and % capable at the trunk, and MSDs.

Ergonomic assessment in metal-based small industries in Bogor Regency, Indonesia, 2019

OBJECTIVE

Small and medium-sized enterprises (SMEs) play a major role in economic growth and employment, and they come with a greater risk of work-related illnesses for workers. Metal-based SMEs are recognised as the sector with the most demanding physical work activities and awkward postures, which are considered risk factors of musculoskeletal disorders (MSDs). This study analysed the risk factors of MSDs associated with different work postures during production.

METHODS

Body postures were examined using the Rapid Entire Body Assessment (REBA) method, and the data on musculoskeletal symptoms were collected using the Nordic Musculoskeletal Questionnaire (NMQ).

RESULTS

The results were calculated using the REBA method to determine the level of risk of various postures, namely, low risk (3.6%), medium risk (25.0%), high risk (60.7%), and very high risk (10.7%). The NMQ results indicated that most of the symptoms and discomfort were in the lower back (65%), wrist (45%), shoulder (35%), and ankle (35%) regions.

CONCLUSIONS

The physical factors contributed more to the musculoskeletal symptoms in the body regions affected. The use of tools in lifting activities could decrease the level of risk.

Musculoskeletal Disorders in Tyre Manufacturing Workers

Background

Tyre manufacturing workers are at risk of developing WRMSDs as their job repeatedly involves elevated arm postures, lifting of tyres, pushing or pulling trolleys, trunk bending and twisting.

Aim

To assess WRMSDs in tyre manufacturing workers.

Methodology

This was an observational study involving 99 tyre manufacturing workers. Persons with any history of recent trauma, major hospitalization or surgery in past 12 months were excluded. Workers were screened according to Nordic questionnaire for assessing the musculoskeletal disorders and REBA analysis was done. They were also assessed for flexibility of hamstring using AKE test and isometric endurance of back extensors using Sorenson test.

Results

97% workers were under 30 years of age and 91% were males. The average duration of work was 27 months. In the past 12 months, 36% workers reported low back pain, 24.2% shoulder pain, 24.2% neck pain, 19% knee pain and 20% ankle/foot pain. REBA analysis revealed TBR and PCR manufacturing workers to be at higher and lower end of medium risk category, respectively. Average AKE values were 39.45⁰ and 38.45⁰ on the right and left, respectively, indicating that hamstring tightness was common, average back muscle endurance was 40.68 sec. However, AKE or back muscle endurance was not statistically related to back pain (P > 0.05).

Conclusion

Tyre workers showed involvement of multiple joints. LBP was predominant complaint but was not related to hamstrings tightness or back muscle endurance.

Landscaping Work: Work-related Musculoskeletal Problems and Ergonomic Risk Factors

Background

Work-related musculoskeletal disorders (WRMSDs) are considered one of the foremost reason of disability globally with significant economic impact due to loss of productivity. Landscaping work is considered a high-risk industry in the service sector. Landscape workers are susceptible to WRMSDs as they are exposed to high physical demands at work, and exert significant physical effort to complete daily repetitive tasks during long working hours. The aim of this study was to determine the prevalence of WRMSDs and to identify the ergonomic risk factors among landscape workers in a university setting.

Methods

This was a cross-sectional study conducted among landscape workers at a public university in Kota Kinabalu, Sabah. Interviews were conducted due to low literacy of the participants, using structured questionnaires which consist of personal characteristics, work descriptions, ergonomic risk factors, as well as self-reported WRMSD symptoms using NORDIC questionnaire. Ergonomic risk assessment (ERA) using rapid entire body assessment (REBA) was then conducted.

Results

Fifty-five of 60 landscape workers agreed to participate (92% response rate). The overall prevalence of WRMSDs among landscape workers was 85.5%. The highest prevalence involving the shoulder (65.5%), followed by neck (23.6%), wrist/hand (23.6%), and lower back (20.0%) regions based on their self-reported WRMSD symptoms over the past 12 months. Awkward posture was the risk factor identified through ergonomic risk assessment (ERA) conducted by ERA trained personnel. None of the working postures during assessment was noted to be appropriate. Although no significant difference was associated with self-reported WRMSDs, majority of the landscape workers (71%) were classified as medium ergonomic risk group using REBA, with the remaining 29% considered to be high ergonomic risk group.

Conclusion

Improvement in awareness campaigns, modification of working tools, and enhanced administrative approaches are among the control and prevention measures recommended to delay or prevent the occurrence of WRMSDs.

Electromechanical rolling whiteboard for improving posture and comfort of users in classrooms

BACKGROUND

The prevalence of musculoskeletal disorders is high among teachers. Poor posture when writing on whiteboards is considered among the important causes of these disorders.

OBJECTIVE

The present study aimed to evaluate an electromechanical rolling whiteboard for educational environments as an ergonomic intervention.

METHODS

Thirty university lecturers volunteered to take part in the study. Participants performed a 5-minute writing task on a regular board and on the newly modified whiteboard in random order. The comfort and effectiveness of the boards and the perceived physical effort and posture of the participants were evaluated and compared by applying the verbal rating scale, Borg's rating of physical exertion scale, and rapid entire body assessment, respectively.

RESULTS

A total of 83.2% of participants reported the new whiteboard to be comfortable or more comfortable to use than the regular whiteboard, and 76.6% of them found the new whiteboard to be higher or much higher in effectiveness and usefulness in comparison with the regular whiteboard. The comfort and posture ratings revealed that exertion was significantly less and posture improved while writing on the new board as compared to its counterpart (p < 0.0001).

CONCLUSION

The new whiteboard increased user comfort, reduced physical effort, and improved posture, hopefully leading to a decreased number of work-related musculoskeletal disorders.

Application of AULA Risk Assessment Tool by Comparison with Other Ergonomic Risk Assessment Tools

Agricultural upper limb assessment (AULA), which was developed for evaluating upper limb body postures, was compared with the existing assessment tools such as rapid upper limb assessment (RULA), rapid entire body assessment (REBA), and ovako working posture analysis system (OWAS) based on the results of experts’ assessments of 196 farm tasks in this study. The expert group consisted of ergonomists, industrial medicine experts, and agricultural experts. As a result of the hit rate analysis, the hit rate (average: 48.6%) of AULA was significantly higher than those of the other assessment tools (RULA: 33.3%, REBA: 30.1%, and OWAS: 34.4%). The quadratic weighted kappa analysis also showed that the kappa value (0.718) of AULA was significantly higher than those of the other assessment tools (0.599, 0.578, and 0.538 for RULA, REBA, and OWAS, respectively). Based on the results, AULA showed a better agreement with expert evaluation results than other evaluation tools. In general, other assessment tools tended to underestimate the risk of upper limb posture in this study. AULA would be an appropriate evaluation tool to assess the risk of various upper limb postures.

Gender differences in prevalence of musculoskeletal disorders and physiological stress among the brick field workers of West Bengal, India

BACKGROUND

The manual brick field industry is one of the most important and oldest industries in India, where millions of male and female workers make their livelihood.

OBJECTIVE

To estimate the different ergonomic risk factors associated with brick making, identify potential gender differences and the prevalence of Work-related musculoskeletal disorders (WMSDs), physiological and psychological stress among the brickfield workers.

METHODS

Brickfield workers - 152 male and 148 female were randomly selected from the 12 brickfields. The Modified Nordic Questionnaire was applied to assess the discomfort reported among both groups of brickfield workers. Objective measurement of physiological parameters and lung function values were also recorded.

RESULTS

From this study, it was revealed that there is significantly higher discomfort reported in hands, lower back and knees among female brick molders than male brick molders. The physiological parameters did not show any significant change between male brickfield workers and female brickfield workers. The mean values of FVC, FEV1 and PEFR for females were lower than those for male brickfield workers.

CONCLUSION

This study concludes that female brickfield workers reported more discomfort than male brickfield workers; perhaps in part due to their additional domestic work responsibilities.

Risk Assessment for Musculoskeletal Disorders in Forestry: A Comparison between RULA and REBA in the Manual Feeding of a Wood-Chipper

The analysis of the postural attitude of workers during the interaction with workstation’s elements and working environment is essential in the evaluation and prevention of biomechanical overload risk in workplaces. RULA (Rapid Upper Limb Assessment) and REBA (Rapid Entire Body Assessment) are the two easiest methods for postural risk assessment in the workplace. Few studies investigated postural risk in forestry sector with regard to human–machine interaction, in particular manually fed wood-chippers. The aim of this study was to evaluate the postures assumed by an operator during the manual feeding of a wood-chipper, and to compare RULA and REBA, in order to identify the more effective and appropriate method for the assessment of the risk of biomechanical postural overload. The results pointed out several postural issues of the upper limbs, and showed that RULA is a more precautionary method to protect operator’s health during the targeted tasks. Implications to improve the human–wood-chipper interaction are discussed.

Prediction of Y haplogroup by polymerase chain reaction-reverse blot hybridization assay

BACKGROUND

The analysis of Y-SNPs from crime scene samples is helpful for investigators in narrowing down suspects by predicting biogeographical ancestry.

OBJECTIVE

In this study, a PCR-reverse blot hybridization assay (REBA) for predicting Y-chromosome haplogroups was employed to determine the major haplogroups worldwide, including AB, DE, C, C3, F, K, NO, O, O2, and O3 and evaluated.

METHODS

The REBA detects nine biallelic Y chromosome markers (M9, M89, M122, M145, M175, M214, M217, P31, and RPS4Y₇₁₁) simultaneously using multiple probes.

RESULTS

The REBA for Y-single nucleotide polymorphisms (SNP) genotyping was performed using 40 DNA samples from Asians-14 Koreans, 10 Indonesians, six Chineses, six Thais, and four Mongolians. 40 Asian samples were identified as haplogroup O2 (40%), O3 (32.5%), C3 (17.5%), O (7.5%) and K (2.5%). These cases were confirmed by DNA sequence analysis (κ = 1.00; P < 0.001).

CONCLUSION

PCR-REBA is a rapid and reliable method that complements other SNP detection methods. Therefore, implementing REBA for Y-SNP testing may be a useful tool in predicting Y-chromosome haplogroups.

XML Skeleton Definitions for Human Posture Assessments

In this paper, we show how the XML dialect SKAML (Skeletal Assessment Markup Language) can be used to use data from one or more Motion Capture systems to perform human posture assessments with multiple assessment methods. We show an implementation example using an inertial measuring suit and both OWAS and REBA assessment methods. SKAML makes it possible to implement classifiers for a Motion Capture system once and adapt the classifier by-configuration to various ergonomics assessment methods. We anticipate our work as help for researchers and developers that implement new assessment methods or motion capture systems.

Development of a Rapid Reverse Blot Hybridization Assay for Detection of Clinically Relevant Antibiotic Resistance Genes in Blood Cultures Testing Positive for Gram-Negative Bacteria

Rapid and accurate identification of the causative pathogens of bloodstream infections is crucial for the prompt initiation of appropriate antimicrobial therapy to decrease the related morbidity and mortality rates. The aim of this study was to evaluate the performance of a newly developed PCR-reverse blot hybridization assay (REBA) for the rapid detection of Gram-negative bacteria (GNB) and their extended-spectrum β-lactamase (ESBL), AmpC β-lactamase, and carbapenemase resistance genes directly from the blood culture bottles. The REBA-EAC (ESBL, AmpC β-lactamase, carbapenemase) assay was performed on 327 isolates that were confirmed to have an ESBL producer phenotype, 200 positive blood culture (PBCs) specimens, and 200 negative blood culture specimens. The concordance rate between the results of REBA-EAC assay and ESBL phenotypic test was 94.2%. The sensitivity, specificity, positive predictive value, and negative predictive value of the REBA-EAC assay for GNB identification in blood culture specimens were 100% (95% CI 0.938–1.000, P < 0.001), 100% (95% CI 0.986–1.000, P < 0.001), 100% (95% CI 0.938–1.000, P < 0.001), and 100% (95% CI 0.986–1.000, P < 0.001), respectively. All 17 EAC-producing GNB isolates from the 73 PBCs were detected by the REBA-EAC assay. The REBA-EAC assay allowed easy differentiation between EAC and non-EAC genes in all isolates. Moreover, the REBA-EAC assay was a rapid and reliable method for identifying GNB and their β-lactamase resistance genes in PBCs. Thus, this assay may provide essential information for accelerating therapeutic decisions to achieve earlier appropriate antibiotic treatment during the acute phase of bloodstream infection.

A model for developing job rotation schedules that eliminate sequential high workloads and minimize between-worker variability in cumulative daily workloads: Application to automotive assembly lines

The aim of study is to suggest a job rotation schedule by developing a mathematical model in order to reduce cumulative workload from the successive use of the same body region. Workload assessment using rapid entire body assessment (REBA) was performed for the model in three automotive assembly lines of chassis, trim, and finishing to identify which body part exposed to relatively high workloads at workstations. The workloads were incorporated to the model to develop a job rotation schedule. The proposed schedules prevent the exposure to high workloads successively on the same body region and minimized between-worker variance in cumulative daily workload. Whereas some of workers were successively assigned to high workload workstation under no job rotation and serial job rotation. This model would help to reduce the potential for work-related musculoskeletal disorders (WMSDs) without additional cost for engineering work, although it may need more computational time and relative complex job rotation sequences.

Working posture and its predictors in hospital operating room nurses

BACKGROUND

This study was conducted to evaluate working posture of operating room nurses and its relationship with demographic and job details of this group.

METHODS

This cross-sectional study was conducted among 147 operating room nurses in Tabriz, Iran using a questionnaire and the Rapid Entire Body Assessment (REBA) checklist. The data were analyzed with SPSS.16 using t test, Pearson correlation coefficient and analysis of variance (ANOVA) tests for univariate analysis and the linear regression test for multivariate analysis.

RESULTS

The mean (SD) of REBA score was 7.7 (1.9), which means a high risk level and highlights an urgent need to change the working postures of the studied nurses. There was significant relationship between working posture and age (P = 0.003), gender (P = 0.003), regular daily exercise (P = 0.048), work experience (P = 0.003), number of shifts per month (P = 0.006) and type of operating rooms (P < 0.001) in univariate analyses. Gender and type of operating room were the predictors of working posture of nurses in multivariate analysis.

CONCLUSION

The findings highlight the need for ergonomic interventions and educational programs to improve working posture of this study population, which can consequently lead to promotion of health and well-being of this group.

Ergonomic assessment for the task of repairing computers in a manufacturing company: A case study

BACKGROUND

Manufacturing industry workers who repair computers may be exposed to ergonomic risk factors.

OBJECTIVES

This project analyzes the tasks involved in the computer repair process to (1) find the risk level for musculoskeletal disorders (MSDs) and (2) propose ergonomic interventions to address any ergonomic issues.

METHODS

Work procedures and main body postures were video recorded and analyzed using task analysis, the Rapid Entire Body Assessment (REBA) postural method, and biomechanical analysis.

RESULTS

High risk for MSDs was found on every subtask using REBA. Although biomechanical analysis found an acceptable mass center displacement during tasks, a hazardous level of compression on the lower back during computer's transportation was detected.

CONCLUSIONS

This assessment found ergonomic risks mainly in the trunk, arm/forearm, and legs; the neck and hand/wrist were also compromised. Opportunities for ergonomic analyses and interventions in the design and execution of computer repair tasks are discussed.

Computer-aided human factors analysis of the industrial vehicle driver cabin to improve occupational health

Industrial vehicle operator's solace and safety have gained significant consideration because of the increment in occupational health issues and accidents. The purpose of this work was to amend the design of the excavator driver cabin through human factor analysis. Thirty operators of excavators who were serving as subjects, were interviewed and identified that their wrist, upper arm and trunk were at a higher risk level while operating. Photograph of the operators was taken and the work environment was simulated. RULA (Rapid Upper Limb Assessment) and REBA (Rapid Entire Body Assessment) scoring was made on different simulated work posture of operators using CATIA V5 and UEAT1.8 softwares. Based on overall RULA and REBA scoring, it was found nearly 46% of the operators were operating at a high hazard level and needed investigation immediately, whereas 35% of operators were at a medium risk level and only 19% of operators were operating safely. The individual RULA and REBA scoring proved prevalence of discomfort in wrist, upper arm and trunk while operating. Identifying the optimized conditions to hold the control levers will help to reduce the operator strain. From the design optimization in excavators, the optimal conditions to hold the control lever is found to be 40cm for popliteal height, 60.51 cm for distance from elbow to ground and 15.07º for reach angle from the seat reference point.