Postural Risk Research Articles

An Empirical and Deep Learning Investigation of Working Conditions and Musculoskeletal Outcomes in Wheat Farmers

Background: In developing countries, various farming activities are performed manually with the help of traditional hand tools. Therefore, agriculture is recognized as one of the risky occupations Objective: This research study aims to identify the critical working conditions of wheat farmers in Rajasthan state, India. Method: Data were collected through the survey conducted on 75 randomly selected wheat farmers of Rajasthan. The survey questionnaire gathered information related to demographic, occupational, and musculoskeletal discomfort faced by the farmers. In addition, a deep learning-based posture detection study of the workers was performed to assess the postural risks through a rapid upper limb assessment score. Result: The collected data were analyzed further for fruitful insights. The survey outcomes showed that awkward posture (41%) and repetitive movement (35%) were the most reported reasons for the severe risks of musculoskeletal disorders among farmers. The posture evaluationbased study outcomes showed that approximately 51% of subjects lie in the action category 4, which shows the higher level of risks in the activities performed by farmers. Conclusion: It is suggested to apply the principles of physical ergonomics in the agriculture sector and spread awareness among the farmers about the agriculture risks associated with farming activities.

Postural Risks in Dental Practice: An Assessment of Musculoskeletal Health.

In recent years, Romania's stomatology private practice sector has seen substantial growth, with many dentists fully committing to building and expanding their own practices, often funded by their personal income. This study aimed to explore how various postures affect the muscle groups of dentists (380), particularly focusing on identifying positions that may jeopardize their musculoskeletal health. A group of dentists effectively participated in this study (10), adhering to their regular work routines while wearing wearable sensors on their backs to monitor posture and activity. The data gathered from these sensors were analyzed using the RULA (rapid upper-limb assessment) and REBA (rapid entire-body assessment) tools. The findings indicated that the head and shoulder movements during dental procedures involved considerable and repetitive angular shifts, which could strain the neck and back muscles and heighten the risk of musculoskeletal problems. Additionally, the standing postures adopted by the dentists were associated with an increased risk of postural issues and greater overall fatigue. Extended periods of trunk and head tilting were also identified as contributing factors to posture-related challenges.

Investigating basics and principles of ergonomics in the sheet

The development of work-related musculoskeletal disorders depends on the pattern of work and does not belong to a particular industry or occupation. One way to assess the amount of stress and tension on the body is to evaluate posture. The aim of this study was to determine the risk factors for musculoskeletal disorders in cellulose industry workers. Study, 22 stations were examined using RULA method, of which 7 stations were at level 2, 14 stations were at level 3 and one station was at level 4. 14 stations were surveyed using REBA method, among which, 2 stations were at level 1 and 12 stations were at level 2. Also, 38 stations were surveyed using the KIM-LHC method, of which 26 stations were at level 2 and 12 stations were at level 3. Statistical studies showed that there was a significant relationship between low back pain and work experience at the level of 0.01. The prevalence of shoulder, arm, back and leg pain was significantly different between men and women at the level of 0.01. There was also a significant relationship between the prevalence of musculoskeletal disorders in the lumbar and shoulder area over a period of time and the level of risk of work postures. The results of the study showed that the prevalence of musculoskeletal disorders and risk levels calculated by RULA and KIM methods were high in the subjects, but the risk level calculated by REBA method was low and moderate. Therefore, any program to prevent the occurrence of these disorders in the workplace and control the relevant ergonomic risk factors and take corrective measures to improve working conditions at all stages of production, is necessary.

Measuring the Effect of an Ergonomic Lecture on the Rapid Upper Limb Assessment Scores of Dental Assistant Students Using Inertial Sensor-Based Motion Capture-A Randomized Controlled Study.

Individuals working in the field of dentistry have a high prevalence of musculoskeletal disorders (MSDs) owing to monotonous and one-sided physical exertion. Inertial measurement units (IMU) are increasingly shifting into focus for assessing postural risk at work. Therefore, the present study aimed to evaluate the effects of an ergonomic lecture and training intervention on postural risk and MSDs in dental assistant students using inertial sensor-based motion capture (MoCap). Eighteen female dental assistant students (age: 19.44 ± 6.83 years; height: 164.59 ± 5.32 cm; weight: 64.88 ± 16.52 kg; BMI: 19.70 ± 4.89 kg/m2), randomly divided into intervention (n = 9) and control (n = 9) groups, participated in the present study. The participants completed the Nordic Questionnaire on MSD prevalence, after which a 90 s MoCap with Xsens IMU was performed. A lecture on ergonomics was provided, followed by a five-week intervention for the intervention group. Follow-up assessments were performed, and 5- and 18-week follow-up MSD questionnaires were administered. Mixed analysis of variance (MANOVA) showed a significant difference in the Rapid Upper Limb Assessment (RULA) and part-scores of the upper arm and wrist. Despite a reduction in MSDs, no significant differences in the time of measurement and groups were detected after the five-week training intervention and the 18-week follow-up questionnaire. A targeted ergonomics lecture was effective for dental assistant students, and technologies such as IMU improved workplace ergonomics in dentists. Further studies with a longer measurement periods, follow-up, and larger sample sizes are recommended.

A Postural Risk Assessment of Steamer Production Workers Using RULA and REBA

A Postural Risk Assessment of Steamer Production Workers Using RULA and REBA

Work Posture analysis Using the Rapid Entire Body Method Assessment (REBA) to Reduce the Risk of Injury in Line I Employees Upper Production PT. XYZ

This research aim to solve the problem of ergonomic standart in the process of making an upper shoes by implementing Rapid Entire Body Assessment (REBA). This method is suitable to solve job body posture problem of the worker of PT XYZ based in Sidoarjo. PT XYZ is an international company and one of the expantion company from Denmark, they produce high quality shoes with more than 7000 workers. There are several plaint from the worker that they had a featigue in some part of te body. REBA assess the score from the top of the body to the bottom of the body and giving report are report of the posture risk. By using this method, the solution can be found with giving the right posture of the worker body while working their duty. The result of the research are confirmed to reduce the risk of musculoskeletal disorders (MSDs) the posture need an improvement by changing the moves of trunk, upper arm, and wrist. Reba score are known in 6 and it’s increasing to 3 after the improvement.

Assessment of postural risks in adolescents aged 12-19 during smartphone use

Assessment of postural risks in adolescents aged 12-19 during smartphone use

Comparative Ergonomic Posture Analysis of CNC Milling Machine Workers through Digital Human Modeling and Artificial Neural Networks

Objectives: To analyze the critical postures of the CNC milling machine operators by RULA (Rapid Upper Limb Assessment) scores and develop an ANN (Artificial Neural Network) prediction model. Methods: The methodology includes a postural analysis of 40 male CNC milling machine operators across Bangladesh, employing both manual (using manual RULA assessment worksheet) and digital (using CATIA V5R21 software) RULA methods complemented by an ANN prediction model. Finally, Digital RULA scores through DHM (Digital Human Modeling) and ANN predicted RULA scores would be compared. Findings: Digital RULA analysis reveals that lifting, carrying, and positioning are the most crucial ergonomic postures, and the most prominent high-risk category limbs are wrist and arm. The overall initial RULA score for lifting, carrying, and positioning are 7, 6, and 7, respectively, and reduced to 3, 3 and 4 respectively for ergonomically designed posture. The ANN model, structured with input, hidden, and output layers of 7, 10, and 1 nodes, significantly refines ergonomic risk prediction by aligning predicted scores closely with actual outcomes during the first stage, emphasized for training. It demonstrates a perfect correlation (R=1) in training, testing, validation, and overall performance for using manual RULA scores. The model's accuracy is further evidenced by minimal prediction offsets across all datasets for digital RULA score in the second stage, with correlation coefficients of 0.87003 (training), 0.93676 (validation), 0.89113 (testing), and (0.88395) for overall. This study contributes significant advancements in ergonomic risk assessment, highlighting the adoption of improved postures to reduce musculoskeletal disorders. Novelty: Employing both manual and DHM methods for RULA score calculation combined with ANN model, which can predict postural risk as floating number and fit a wider range of parameters. Keywords: ANN, CNC, Digital Human Modeling (DHM), Ergonomics, RULA

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.

Evaluation of Ergonomic Risks for Construction Workers based on Multicriteria Decision Framework with the Integration of Spherical Fuzzy Set and Alternative Queuing Method

Ergonomic risks critically impact workers’ occupational health, safety, and productivity, and thereby the sustainability of a workforce. In the construction industry, the physical demands and dynamic environment exposes workers to various ergonomic hazards. While previous research has mainly focused on postural risks, there is a need to broaden the scope to include more relevant factors and assess them systematically. This study introduces a multi-criteria decision framework integrating the Spherical Fuzzy Sets (SFSs) and Alternative Queuing Method (AQM) to evaluate and prioritize ergonomic hazards. First, SFSs are employed to quantify the linguistic expressions of experts, addressing the inherent vagueness and uncertainty. Then, an entropy-based objective weighting method is adopted to determine the criteria weights. Finally, AQM is utilized to generate the risk priority. The proposed method has been implemented in a real-life construction project, where “overexertion due to unreasonable task organization”, “hypertension and heart diseases”, and “existing WMSD record” are identified as the top three ergonomic hazards. Then, a thorough discussion of intervention strategies regarding different risk categories is presented to facilitate ergonomic interventions. This proposed decision support system can promote effective ergonomic risk management, benefiting workers’ health and well-being and contributing to the sustainable workforce development of the construction industry.

Study of musculoskeletal disorders risk factors and discomfort in sculptors in the north of Mexico

BACKGROUND: The sculpting craft must adopt awkward postures that lead to musculoskeletal disorders (MSDs). OBJECTIVE: This study investigated the prevalence of musculoskeletal discomfort (MD) and its associations with postural risk factors, demographics, and work characteristics among sculptors. They were determined the differences between MDs during the weeks of the study. METHODS: A longitudinal study was conducted; MD was investigated using the Cornell Musculoskeletal Discomfort Questionnaire (CMDQ). Posture was assessed using the Rapid Upper Limb Assessment method (RULA). Multivariate logistic regression (MLR) models analyzed associations with different factors. ANOVA was used to test for differences in MD prevalence. RESULTS: The analysis included 585 responses by body region. The prevalence of MD was high in the lower and upper limbs among sculptors (67.6%), with the lower back, upper arm, neck, and knees being the four most affected regions. Gender (female) (OR = 2.15), marital status (married) (OR = 1.80), health risk (obesity), the dual of a secondary job (OR = 1.94), job stress (OR = 2.10), duration of work (OR = 2.01), and difficulty keeping up with work (OR = 2.00) were significant predictors contributing to the occurrence of MD in different body regions. Only shoulder MD prevalence showed significant differences between study weeks. CONCLUSIONS: Sculptors suffer from MD. Demographic and work characteristic factors influence MD prevalence. Postural training, improved adaptation of work organization, and intervention guidance on ergonomic risks may reduce the prevalence of MD and the risk of MSDs in this population.

Work posture risk comparison of RULA and REBA based on measures of assessment-score variability: A case study of the metal coating industry in Thailand

This study examines the work posture risk comparison of RULA and REBA based on measures of assessment-score variability. During the metal coating process, chemicals were frequently employed, necessitating a heightened level of caution among the employees. The Cornell Musculoskeletal Discomfort Questionnaires (CMDQ) revealed the manifestation of physical discomfort among employees. In this study, the rapid upper limb assessment (RULA) and the rapid entire body assessment (REBA) were used to identify ergonomic concerns related to the work of employees in the black oxide coating department of a metal coating firm. The sensitivity of risk assessment between the two methods was investigated, considering the mean and variability of the assessment scores. Consideration was given to the diverse and crucial work positions of employees at each station, focusing exclusively on the standing working posture. In the black oxide coating section, there were 12 steps that 20 workers had to complete. Under the same working postures, the overall average RULA score was determined to be at a high-risk level, whereas the overall average REBA score was at a moderate-risk level. As a result, the RULA method had a greater capacity for risk warning than the REBA method. Levene's test was also applied to determine whether the variances of the risk scores computed using the two techniques were equal. The results of the analysis showed that the variances in the scores using the two methods were not significantly different.

Combining inertial-based ergonomic assessment with biofeedback for posture correction: A narrative review

Work-related musculoskeletal disorders (WRMSDs) are the most reported work-related health problem in the European Union, representing an economic burden equivalent to 2% of its gross domestic product. Awkward postures are one of the main risk factors. Several postural assessment tools try to identify ergonomic exposure factors for evaluating WRMSD risk, yet these are commonly based on observation. Replacing observations with objective measurements can bring more accuracy and reproducibility to this analysis; hence, a direct measurement approach for the assessment is desired. This review looks for two-fold solutions, able to not only monitor workers’ posture using inertial sensors but also to return that information to the user, in a biofeedback loop. It presents systems for posture risk assessment, regarding ergonomic methods, sensors’ and actuators’ characteristics, and validation protocols. In particular, this review advances previous manuscripts by exploring the literature regarding different biofeedback strategies and ways to encode meaningful information in the cues, i.e., able to deliver intuitive ergonomic guidance so that the user becomes aware and changes into a more neutral posture. The combination of inertial sensors and vibrotactile motors stood out, due to its effectiveness in reducing postural risk. Directional feedback to guide users’ segments individually was found to be a promising strategy, although its validation is still limited. The results of the reviewed manuscripts pointed out the relevant practices, potentialities, and limitations of the existing solutions, allowing the identification of future challenges.

A holistic methodology for mitigating awkward postural risks: Evidence from South Indian small-scale industries.

Small-scale industries (SSI) are the global economy's backbone since most industrial workers are connected. Most of these workers are contractual and temporary without appropriate training. Also, the SSI does not have a standard workplace with an appropriate layout and infrastructure, as they manage with minimum resources. Therefore, the work hazards, i.e., musculoskeletal disorders and fatigue, often go unnoticed as holistic postural risk methodology is still scarce for identifying the awkward postures in SSI. The present study proposes a novel holistic methodology to track and mitigate awkward postural risks in human-physical activities in SSI. To determine the effectiveness of the proposed methodology, a case study is presented in the South Indian Pump industry, wherein a critical workstation with a complex ergonomic work environment is employed. An ergonomic evaluation was conducted empirically and numerically in the workplaces using Digital Human Models. In numerical evaluation, three virtual workspaces have been created to redesign the identified crucial workstation, focusing on ergonomics and workflow. The results obtained from the case study are encouraging for to use of the novel methodology in SSI. The case study reports that the proposed design significantly reduced the REBA score and WISHA lifting index by 6 and 1.20, respectively, without significant investment. The proposed methodology could encourage research to identify awkward posture in SSI.

Impact of physical exercise (strength and stretching) on repairing craniovertebral and reducing neck pain: A systematic review and meta-analysis.

The craniovertebral (CV) junction is crucial for head support, mobility, and protecting the upper spinal cord and vital nerve structures. Disorders in this area can cause severe symptoms such as neck pain, restricted movement, and neurological issues such as headaches and balance problems. Exercise and physical activity improves muscle strength, flexibility, joint stability, reducing pain, and enhancing joint function, while specifically for the CV junction, exercise can relieve muscle tension, boost blood flow, and improve posture, although the specific impact on CV junction health remains underexplored. A comprehensive literature search was conducted using databases MEDLINE, Cochrane, Lilacs, and ScienceDirect, alongside manual searches through reference lists. The review focuses on exercise and CV junction issues and includes randomized controlled trials, cohort or case-control studies, and systematic reviews. Primary outcomes include pain levels, joint mobility, function, and quality of life. Results yield four meta-analyses with corrective exercise and conventional exercise in improving forward head posture risk difference 0.00 (-0.09, 0.09) 95% confidence interval (CI), between cervical and thoracic exercises odds ratio 1.04 (0.59, 1.84) 95% CI. Comparing exercise treatment and physiotherapy showed risk difference 0.11 (-0.10, 0.32) 95% CI and the comparative analysis between training and no treatment showed risk difference 0.09 (-0.01, 0.20) 95% CI. Exercise-based rehabilitation programs tailored to patients with CV junction problems offer robust evidence, benefiting clinical management, and prevention efforts.

Exploring Risk of Posture and Musculoskeletal Disorders among Smartphone Addicted Youth: a Protocol Paper

Introduction: Smartphones with rapid advancement in telecommunication technology causing high usage leads to addiction, especially among youth. Concerning health, smartphone addiction influences posture causing neck-shoulder pain. However, the mechanism of how smartphone addiction causes pain related to posture control is still doubtful. Anticipatory feed-forward motor control mechanism has proposed that smartphone usage is a static low-level activity influenced by muscle fatigue and discomfort. Therefore, this study aimed to explore neck-shoulder muscle fatigue, particularly at the upper trapezius about smartphone addiction behaviors and adopted posture while using smartphones among youth. This study aims to investigate the relationship between smartphone addiction, risk of posture and the relationship between trapezius muscle fatigue, and neck-shoulder pain among youth. Methods: A cross-sectional study design will be conducted through convenient sampling among students at secondary schools in Malaysia. The Smartphone Addiction Scale, Rapid Assessment Upper Limb, Nordic Musculoskeletal Questionnaire and Electromyogram will be used as outcomes tools. Discussion: This study investigates the risk of smartphones in terms of duration usage among adults. Fatigue over the upper trapezius muscle has not yet been investigated among youth which will provide fundamental findings on how faulty posture during smartphone usage might cause neck pain.

E-Airs: Interactive Ergonomic Monitoring System for Work Posture

Work posture and/or position of work is a crucial problem in work system. Unnatural posture will lead to discomfort when doing the task such as pain at part of body such that it will cause accident in the end. This accident will affect level of work performance of the worker so as the work productivity fails achieve a target determined. The failure mode, of course, results in a big loss for a company. This state should be avoided by use of the natural posture by worker in completing a job. However, many workers do not still understand what kind of a natural and unnatural work posture directly. So, this condition has high risk for being occurred the discomfort. Thus, it is important to develop a tool for helping them to identify a certain posture of work. Objective of this study is to design a monitoring system devices to capture and to determine an natural posture of the worker based on ergonomic principles. Rapid Upper Limb Assessment method is applied to determine a risk of work posture. Machine Learning concept is implemented to support in designing a system by also applying python programming language. Result of this study shows that monitoring system devices developed is usable in informing an unnatural posture of worker in completing a job. Thus, this result will beneficial for worker to improve work posture to be natural position so as discomfort can be prevented.

Postural Ergonomic Risk Assesment of Augmented Reality User Interface on Smarthpones in Cosmetic Industry Advertising

Augmented reality (AR) technology is widely used in marketing activities and promotional strategies so that many users or customers use it, including beauty products, which already offer many applications that are used as promotional tools. Augmented reality technology is accompanied by technological developments and the COVID-19 pandemic, especially among female customers in various groups, including teenage girls who use many cosmetic products daily. The use of this technology requires an evaluation regarding its use, where in this evaluation, an evaluation can be used in terms of ergonomics for the user using the ergonomics concept PERA (Postural Ergonomic Risk Assessment). This research aims to evaluate the postural risk regarding the level of use of augmented reality technology for beauty product applications used by female students when using AR applications on smartphones when accessing cosmetics industry advertising. This research was conducted on female teenage respondents among vocational school students who focused on skill competencies, namely the Skin and Hair Beauty Department at one of the private vocational schools in the Cilamaya-Karawang area. The sample for data collection in this study was by taking 30 respondents using a saturated sample. The results of this research indicate that there must be an evaluation regarding the level of ergonomics with the PERA measurement results ranging between 7.4 - 11.8, indicating that the AR user interface in the cosmetic industry advertising is in the high-risk category so that further improvements are needed in the future so as not to pose a risk of musculoskeletal disorders in teenagers. Thus, AR developers in the advertising industry must pay attention to the comfort of the user’s posture in terms of duration, smartphone weight, and grip strength when using AR applications.

The Effect Of Automated Component Impaction On The Surgeon’s Ergonomics, Fatigue And Stress Levels In Total Hip Arthroplasty

Background Total Hip Arthroplasty (THA) surgery is physically and cognitively challenging. Sub-optimal posture during component impaction may influence surgeon’s ergonomics and fatigue. Methods Thirty THA procedures were executed for 3 days. Only during the first day, manual impaction (MI) was performed. Postural risk was evaluated with Rapid Upper Limb Assessment (RULA) and Rapid Entire Body Assessment (REBA) score. Three cognitive tasks (Simon, pattern comparison and pursuit rotor test) and five physical tests (isometric wall-sit, plank-to-fatigue, handgrip, supra-postural task, and shoulder endurance) assessed surgeon’s psycho-physiological load in the morning, midday, and afternoon. Surgeon’s cortisol concentration and sound level of the broaching process was also recorded. Results RULA and REBA scores were 1.7 to 3 times lower with automated impaction (AI). Physical exhaustion was lower with AI: isometric wall-sit test (10.6% vs. 22.9%), plank-to-fatigue (2.2% vs. 43.8%), supra-postural task (-0.7% vs. -7.7%), handgrip force production (dominant hand -6.7% vs. -12.7%; contralateral +4.7% vs. +7.7%), and in shoulder endurance (-15s vs. -56s). After AI, the cognitive performance showed faster response times and lower error rates for all cognitive tests compared to MI. The salivary cortisol level decreased during the AI-days by 51% in comparison to a 38% increase following the MI-day. Mean broaching time with AI was 7’3’’ compared to 6’20’’ with MI. The mean sound level with the AI-device was 64.3 dBA compared to 68.2 dBA with manual impaction. Conclusions Automated THA component impaction improved the surgeon’s ergonomics which resulted in reduced hormonal stress levels and lower physical and cognitive exhaustion.

Influences of Weight and Weight Balance of Head-Mounted Displays on Subjective Physical Burden and Postural Risk

Influences of Weight and Weight Balance of Head-Mounted Displays on Subjective Physical Burden and Postural Risk