Comparing the Effectiveness of Three Ergonomic Risk Assessment Methods-RULA, LUBA, and NERPA-to Predict the Upper Extremity Musculoskeletal Disorders

Improving Workers' Musculoskeletal Health During Human-Robot Collaboration Through Reinforcement Learning

OBJECTIVE

This study aims to improve workers' postures and thus reduce the risk of musculoskeletal disorders in human-robot collaboration by developing a novel model-free reinforcement learning method.

BACKGROUND

Human-robot collaboration has been a flourishing work configuration in recent years. Yet, it could lead to work-related musculoskeletal disorders if the collaborative tasks result in awkward postures for workers.

METHODS

The proposed approach follows two steps: first, a 3D human skeleton reconstruction method was adopted to calculate workers' continuous awkward posture (CAP) score; second, an online gradient-based reinforcement learning algorithm was designed to dynamically improve workers' CAP score by adjusting the positions and orientations of the robot end effector.

RESULTS

In an empirical experiment, the proposed approach can significantly improve the CAP scores of the participants during a human-robot collaboration task when compared with the scenarios where robot and participants worked together at a fixed position or at the individual elbow height. The questionnaire outcomes also showed that the working posture resulted from the proposed approach was preferred by the participants.

CONCLUSION

The proposed model-free reinforcement learning method can learn the optimal worker postures without the need for specific biomechanical models. The data-driven nature of this method can make it adaptive to provide personalized optimal work posture.

APPLICATION

The proposed method can be applied to improve the occupational safety in robot-implemented factories. Specifically, the personalized robot working positions and orientations can proactively reduce exposure to awkward postures that increase the risk of musculoskeletal disorders. The algorithm can also reactively protect workers by reducing the workload in specific joints.

Ergonomic Analysis of Dental Work in Different Oral Quadrants: A Motion Capture Preliminary Study among Endodontists

BACKGROUND

Dentists, including endodontists, frequently experience musculoskeletal disorders due to unfavourable working postures. Several measures are known to reduce the ergonomic risk; however, there are still gaps in the research, particularly in relation to dental work in the different oral regions (Quadrants 1-4).

METHODS

In this study (of a pilot character), a total of 15 dentists (8 male and 7 female) specialising in endodontics were measured while performing root canal treatments on a phantom head. These measurements took place in a laboratory setting using an inertial motion capture system. A slightly modified Rapid Upper Limb Assessment (RULA) coding system was employed for the analysis of kinematic data. The significance level was set at p = 0.05.

RESULTS

The ergonomic risk for the entire body was higher in the fourth quadrant than in the first quadrant for 80% of the endodontists and higher than in the second quadrant for 87%. For 87% of the endodontists, the ergonomic risk for the right side of the body was significantly higher in the fourth quadrant compared to the first and second quadrant. The right arm was stressed more in the lower jaw than in the upper jaw, and the neck also showed a greater ergonomic risk in the fourth quadrant compared to the first quadrant.

CONCLUSION

In summary, both the total RULA score and scores for the right- and lefthand sides of the body ranged between 5 and 6 out of a possible 7 points. Considering this considerable burden, heightened attention, especially to the fourth quadrant with a significantly higher ergonomic risk compared to Quadrants 1 and 2, may be warranted.

Ergonomic investigations on novel dynamic postural estimator using blaze pose and transfer learning

The aim is to develop a computer-based assessment model for novel dynamic postural evaluation using RULA. The present study proposed a camera-based, three-dimensional (3D) dynamic human pose estimation model using 'BlazePose' with a data set of 50,000 action-level-based images. The model was investigated using the Deep Neural Network (DNN) and Transfer Learning (TL) approach. The model has been trained to evaluate the posture with high accuracy, precision, and recall for each output prediction class. The model can quickly analyse the ergonomics of dynamic posture online and offline with a promising accuracy of 94.12%. A novel dynamic postural estimator using blaze pose and transfer learning is proposed and assessed for accuracy. The model is subjected to a constant muscle loading factor and foot support score that could evaluate one person with good image clarity at a time.Practitioner summary: A detailed investigation of dynamic work postures is largely missing in the literature. Experimental analysis has been performed using transfer learning, BlazePose, and RULA action levels. An overall accuracy of 94.12% is achieved for dynamic postural assessment.

Development of a novel ergonomic index assessment in the workplace based on physical, cognitive, and environmental components

BACKGROUND

Currently, proper assessment of the existing ergonomic hazards, focusing on improving the health of individuals, is of great importance.

OBJECTIVE

This study aims to develop a new model for ergonomic index assessment in the workplace, focusing on physical, cognitive, and environmental components.

METHODS

To determine the parameters to be measured for each group of occupations, the most critical indicators in each ergonomic dimension were identified using a review of scientific texts and obtaining expert opinions. The opinions of 30 experts were studied in three stages Delphi study. Cronbach's alpha was used to calculate model reliability in SPSS version 25. An analytical hierarchy process was used to determine the weight values of each component and parameter. The weights were calculated in Expert Choice version 11.

RESULTS

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. Physical components and parameters of physical condition during work, mental workload, lighting, and thermal stress in the workplace were among the most important parameters in the three groups of office, operational, and services jobs.

CONCLUSION

The model can be a practical step toward properly evaluating the ergonomic components and planning to implement control measures to reduce physical, cognitive, and environmental risk factors. Considering the study of different variables in occupational ergonomic risk assessment, this model can be a helpful tool in ergonomic management systems used in different occupational environments.

Influence of task decision autonomy on physical ergonomics and robot performances in an industrial human–robot collaboration scenario

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.

Translation, cross-cultural adaptation and psychometric properties of Urdu version of upper limb functional index; a validity and reliability study

BACKGROUND

The upper limb functional index is broadly used outcome measure for musculoskeletal disorders of the upper limb. The main objective of the study was to translate and validate the upper limb functional index (ULFI) outcome measure in the Urdu language.

METHODS

Upper limb functional index was translated into Urdu language using Beaton et al. guidelines through forward and backward translation along with the expert committee reviews. Two fifty (n = 250) Urdu-speaking patients with sub-acute or chronic conditions of upper limb musculoskeletal disorders were included in the study. The mean age was 32.33 ± 4.67 years. The data were collected from the physical therapy department of The University of Lahore Teaching hospital. All participants completed the upper limb functional index-Urdu (ULFI-U), Numeric pain rating scale (NPRS), Quick Disability of arm, shoulder, and hand (QuickDash), and (health survey) SF-12 at baseline while only ULFI-U at day three. Reliability was assessed through internal consistency by Cronbach's alpha and test-retest reliability by intra-class correlation (ICC). Content validity was measured by Lynn and Lawshee method. Spearman's correlation has been used to measure criterion validity. The construct validity was measured through hypothesis testing. The structural validity has been explained through factor analysis by exploratory factor analysis (EFA) using Maximum likelihood extraction (MLE) with Promax rotation.

RESULTS

The English version of ULFI was translated into the Urdu language with minor alterations. The Urdu version ULFI has demonstrated high levels of reliability with intra-class correlation (ICC2,1= 0.91) and Cronbach's alpha (α = 0.94). The content validity index found as 0.808, the criterion validity for ULFI-U correlating with quick Dash was found excellent (r = 0.845) and ULFI-U established strong correlation with 6 domains of SF-12(r = 0.697 to 0.767) and weak correlation with its 2 domains and NPRS(r = 0.520). A two-factor structure was obtained using EFA.

CONCLUSIONS

The ULFI-U is a valid and reliable patient-reported outcome (PRO) that can be used to assess upper limb musculoskeletal disorders in Urdu-speaking patients.

TRIAL REGISTRATION

This study was registered in the U. S National Library on clinicaltrial.gov under registration no. NCT05088096 . (Date: 21/10/2021).

Evaluation of musculoskeletal disorders risks in forestry

BACKGROUND: The development of musculoskeletal disorders (MSDs) associated with forestry operations is an alarming issue. OBJECTIVE: In the present paper, an attempt was made to assess the location and the prevalence of the MSDs in timber harvesting tasks. METHODS: The analysis of logging-related risk factors was carried out by observing working postures with the use of the assessment tool RULA (Rapid Upper Limb Assessment) during harvesting jobs. In addition, the standardised Nordic Musculoskeletal Questionnaire (NMQ) was used in order to record self-reported MSDs symptoms. RESULTS: Results revealed that, in all work stages, risk levels were extremely high. According to the results of the RULA analysis, 77.5% of the working postures adopted by the left side of the body and 61.25% of postures involving the right side belong to the very high-risk level. According to the results of the questionnaire, a high percentage of loggers (34%) reported that they were facing problems in their backs and knees. CONCLUSIONS: Training and informing operators about the correct positions and the manual movement techniques, as well as increasing the mechanisation level of harvesting operations could reduce physiological work hardship.

A predictive model to quantify joint torques and support reaction forces when using a smartphone while standing with support

The present study had a dual objective: (1) to present and validate a predictive model of standing posture in the sagittal plane, joint torques and support forces for a smartphone user built from biomechanical principles; (2) propose risk scales for joint torques and reaction forces based on simulations in order to use them into the musculoskeletal disorders prevention. Comparison of the modelled data with experimental measurements (400 tested postures with sample size verification) for calling and texting tasks highlights the model's ability to correctly estimate posture and reaction forces on the ground. The model was able to provide estimates of the range of variation of each parameter for a wide range of environmental conditions as a function of the user body mass index (setting between 12.5 and 50). Joint torques risk scales have been constructed, especially for shoulder and elbow, to characterise the risks incurred by the users. Practitioner summary: The proposed model enables the postures, joint torques and reaction forces to be estimated from subject's body mass index and environmental configuration without resorting to experimentation, which is relevant in industry. This approach allows the proposition of new scales based on joint torques to reinforce the recommendations for MSDs prevention. Abbreviations: BMI: body mass index; LUBA: postural loading on the upper body assessment; MSDs: musculoskeletal disorders; RULA: rapid upper limb assessment; WHO: World Health Organization.

Comparison of LEBA and RULA Based on Postural Load Criteria and Epidemiological Data on Musculoskeletal Disorders

Various observational methods have been developed and applied in industrial settings with the aim of preventing musculoskeletal disorders (MSDs). This study aimed to compare the Rapid Upper Limb Assessment (RULA), a representative observational method, and the Loading on the Entire Body Assessment (LEBA), a newly developed tool for assessing postural loads and their association with MSDs. The two methods were compared in various categories, including general characteristics, risk levels, postural load criteria, association with MSDs, influencing factors, and inter- and intra-rater reliabilities based on relevant previous studies. The results showed that compared to the RULA, the LEBA was better at evaluating various factors affecting postural loads and assessing musculoskeletal loadings, was better correlated with various postural load criteria, could predict the association with MSDs more accurately, and had higher inter- and intra-rater reliabilities. Based on these comparisons, it seems that the LEBA may be better than the RULA for estimating postural stress and predicting the association with MSDs.

Application of the rapid upper limb assessment tool to assess the level of ergonomic risk among health care professionals: A systematic review

BACKGROUND: Work-related musculoskeletal disorders (WMSDs) and ergonomic risk factors are widespread problems in the healthcare sector. OBJECTIVE: The primary objective of this review is to evaluate the application of the Rapid Upper Limb Assessment (RULA) tool in various healthcare professionals and to assess the level of ergonomic risk among them. METHODS: The databases MEDLINE, EMBASE, CINAHL, LILACS, SCIELO, DOAJ, PubMed, and PEDro were searched with terms associated with ergonomics, assessment, health care providers, risk factors, workplace, and RULA. We reviewed the literature from 2000 to 2020, including studies assessing RULA’s effectiveness for evaluating the WMSD’s and ergonomic risk in health care practitioners. We excluded the studies which were not open access and freely available. RESULTS: Overall, 757 records were screened; of these 40 potential studies, 13 different healthcare professionals were identified as eligible for inclusion. In most studies, the RULA tool was established as an effective tool in application and evaluating the level of the ergonomic risk among them. CONCLUSIONS: The RULA tool assessed the high ergonomic risk levels in dental professionals and low ergonomic risk levels in professionals working in the pharmacy department, clearly suggesting potential changes in work postures were necessary to prevent or reduce these risk factors.

Evaluating the Ergonomics of Surgical Residents During Laparoscopic Simulation: A Novel Computerized Approach

BACKGROUND

Assessment of residents' body positioning during laparoscopy has not been adequately investigated. This study presents a novel computer vision technique to automate ergonomic evaluation and demonstrates this approach through simulated laparoscopy.

METHODS

Surgical residents at a single academic institution were video recorded performing tasks from the Fundamentals of Laparoscopic Surgery (FLS). Ergonomics were assessed by 2 raters using the Rapid Upper Limb Assessment (RULA) tool. Additionally, a novel computer software program was used to measure ergonomics from the video recordings. All participants completed a survey on musculoskeletal complaints, which was graded by severity.

RESULTS

Ten residents participated; all performed FLS in postures that exceeded acceptable ergonomic risks as determined by both the human and computerized RULA scores (P < .001). Lower-level residents scored worse than upper-level residents on the human-graded RULA assessment (P = .04). There was no difference in computer-graded RULA scores by resident level (P = .39) and computer-graded scores did not correlate with human scores (P = .75). Shoulder and wrist position were the greatest contributors to higher computer-graded scores (P < .001). Self-reported musculoskeletal complaints did not differ at resident level (P = .74); however, all residents reported having at least 1 form of musculoskeletal complaint occurring "often."

CONCLUSIONS

Surgery residents demonstrated suboptimal ergonomics while performing simulated laparoscopic tasks. A novel computer program to measure ergonomics did not agree with the scores generated by the human raters, although it concluded that resident ergonomics remain a concern, especially regarding shoulder and wrist positioning.

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.

The ergonomic impact of patient body mass index on surgeon posture during simulated laparoscopy

Laparoscopy is a cornerstone of modern surgical care, with clear advantages for the patients. However, it has also been associated with inducing upper body musculoskeletal disorders amongst surgeons due to their propensity to assume non-neutral postures. Further, there is a perception that patients with high body mass indexes (BMI) exacerbate these factors. Therefore, surgeon upper body postures were objectively quantified using inertial measurement units and the LUBA ergonomic framework was used to assess posture during laparoscopic training on patient models that simulated BMIs of 20, 30, 40 and 50 kg/m². In all surgeons the posture of the upper body significantly worsened during simulated laparoscopic surgery on the BMI 50 kg/m² model as compared to the baseline BMI model of 20 kg/m². These findings suggest that performing laparoscopic surgery on patients with high BMIs increases the prevalence of non-neutral posture and may further increase the risk of musculoskeletal disorders in surgeons.

Investigation of psychosocial factors on upper limb musculoskeletal disorders and the prevalence of its musculoskeletal disorders among nurses: a systematic review and meta-analysis

OBJECTIVE

Musculoskeletal disorders are one of the most important occupational problems especially among nurses. The aim of this study was to investigate the prevalence of musculoskeletal disorders in upper limbs and its associated psychosocial factors in the workplace.

METHODS

A systematic review was conducted by searching the Medline/PubMed, EMBASE, Scopus, ISI/web of knowledge and Google Scholar databases. The authors classified studies into categories of psychological work stressors and musculoskeletal problems. The statistical analysis was performed using Stata software.

RESULTS

We found 1742 articles in our initial search. After reviewing the titles, abstracts and full texts, 66 articles were finally analyzed. Psychosocial factors affecting the prevalence of upper limb musculoskeletal disorders among nurses were identified which included boring work, inadequate staffing, job demands, insufficient support, time pressure, decision latitude, job dissatisfaction, and job stress. There was a significant relationship between these factors and prevalence of musculoskeletal disorders in the wrists, shoulders, neck and shoulders, and wrists and hands.

CONCLUSION

Collectively, the results of this study provide strong evidence of some psychosocial factors affecting the prevalence of upper limb musculoskeletal disorders among nurses. Thus, organizational interventions to minimize these stressors may be promising in reducing one risk factor for the development of nurses' musculoskeletal disorders. These interventions should not only consider the factors of physical ergonomics but also seek to improve the organizational aspects of the workplace.

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.

Musculoskeletal Risks: RULA Bibliometric Review

The objective of this study was to reveal RULA method applications in terms of the knowledge, country, year and journal categories. The search was performed using the "Web of Science Core Collection". The period from 1993 to April 2019 was selected. Eight hundred nine results were obtained, of which 226 were used. The largest number of publications was determined to be in the fields of industry and health and social assistance, which coincides with the OWAS and Standardized Nordic Questionnaire methods. By country, the USA stands out for its greater number of research studies and categories that are encompassed. By date, 2016 was the year when more studies were carried out, again coinciding with the Standardized Nordic Questionnaire. By journal, "Work-A Journal of Prevention Assessment and Rehabilitation" is highlighted, as it is for the REBA method as well. It was concluded that RULA can be applied to workers in different fields, usually in combination with other methods, while technological advancement provides benefits for its application.

Intelligent Decision-Making Approaches for Agricultural Sectors of Odisha in India

Agriculture lacks organizational frameworks which are needed for OHS management techniques to operate effectively. Thus, it becomes essential to analyze the magnitude of OHS problems within the agricultural sector. Hence, an attempt was made in this study to explore the prevalence of OHS disorders and discomforts among the farmers of Odisha in India. There are three contributions in this study. At first, OHS issues of farmers were analyzed based on the literature review and the data was collected by personal interaction and questionnaires. In the second part, the “Best Worst Method (BWM)” was used to rank the different rice farming processes, and the different occupational disorders and discomforts, respectively. Furthermore, the RULA tool was used to assess the ergonomics involved in various postures taken by farmers in different rice farming processes, and based on the obtained RULA scores the necessary actions were recommended accordingly. The findings in this study may have positive implications for extension programs and policy formulation in agricultural sectors.

Mechanical Energy Expenditure-based Comfort Evaluation Model for Gesture Interaction

As an advanced interaction mode, the gesture has been widely used for the human-computer interaction (HCI). The paper proposes a comfort evaluation model based on the mechanical energy expenditure (MEE) and the mechanical efficiency (ME) to predict the comfort of gestures. The proposed comfort evaluation model takes nineteen muscles and seven degrees of freedom into consideration based on the data of muscles and joints and is capable of simulating the MEE and the ME of both static and dynamic gestures. The comfort scores (CSs) can be therefore calculated by normalizing and assigning different decision weights to the MEE and the ME. Compared with the traditional comfort prediction methods based on measurement, on the one hand, the proposed comfort evaluation model makes it possible for providing a quantitative value for the comfort of gestures without using electromyography (EMG) or other measuring devices; on the other hand, from the ergonomic perspective, the results provide an intuitive indicator to predict which act has the higher risk of fatigue or injury for joints and muscles. Experiments are conducted to validate the effectiveness of the proposed model. According to the comparison result among the proposed comfort evaluation model, the model based on the range of motion (ROM) and the model based on the method for movement and gesture assessment (MMGA), a slight difference can be found due to the ignorance of dynamic gestures and the relative kinematic characteristics during the movements of dynamic gestures. Therefore, considering the feedback of perceived effects and gesture recognition rate in HCI, designers can achieve a better optimization for the gesture design by making use of the proposed comfort evaluation model.