Work Postures Research Articles

Decision Support System (DSS) for Improving Production Ergonomics in the Construction Sector

Ergonomics is essential to improving workplace safety and efficiency by reducing the risks associated with physical tasks. This study presents a decision support system (DSS) aimed at enhancing production ergonomics in the construction sector through an analysis of high-risk postures. Using the Ovako Work Posture Analysis System (OWAS), the Revised NIOSH Lifting Equation (NIOSH equation) and Rapid Entire Body Assessment (REBA), the DSS identifies ergonomic risks by assessing body postures across common construction tasks. Three specific postures—X, Y and Z—were selected to represent typical construction activities, including lifting, squatting and repetitive tool use. Posture X, involving a forward-leaning stance with arms above the shoulders and a 25 kg load, was identified as critical, yielding the highest OWAS and NIOSH values, thus indicating an immediate need for corrective action to mitigate risks of musculoskeletal injuries. The DSS provides recommendations for workplace adjustments and posture improvements, demonstrating a robust framework that can be adapted to other postures and industries. Future developments may include application to other postures and sectors, as well as the use of artificial intelligence to support ongoing ergonomic assessments, offering a promising solution to enhance Occupational Safety and Health policies.

Research on fall prevention and safety protection for electric power tower climbing operations based on the longhorn whisker algorithm

Abstract With the continuous development of the power industry, the safety of power tower climbing operations is increasingly valued. This study focuses on the anti-fall safety protection of electric power tower climbing operations and proposes a study on the anti-fall safety protection of electric power tower climbing operations based on the Longhorn whisker algorithm. Firstly, real-time image acquisition of the climbing operation site is carried out through the camera equipment carried by the drone, ensuring clear and comprehensive information on the working environment is obtained. Secondly, extract hazardous features in climbing operations, such as abnormal worker posture, tool detachment, etc. These features are important indicators of potential fall risks. Finally, a fall hazard detection model is constructed and optimized using the Longhorn Whisker algorithm to identify and warn of impending fall events, thereby providing timely safety protection for climbing operators. The experimental results show that this method has shown significant effectiveness in improving job safety, providing strong technical support for the safety protection of power tower climbing operations.

Risk Evaluation of Musculoskeletal Disorders (MSDs) at the Outpatient Registration Centre: A Review of Work Postures with the Rapid Office Strain Assessment (ROSA) Method

Risk Evaluation of Musculoskeletal Disorders (MSDs) at the Outpatient Registration Centre: A Review of Work Postures with the Rapid Office Strain Assessment (ROSA) Method

Research progress on working posture standards, evaluation, and influencing factors for dental professionals

The correct working posture of dentists is not only the premise of clinical diagnosis, treatment quality and safety but also an important guarantee for the occupational health of dentists. Presently, research on the working posture of dental professionals and related influencing factors is relatively mature internationally. Still, the dental curriculums in our country have not systematically introduced theoretical knowledge and standards related to working posture. This review analyzes and summarizes previous literature on the importance of dental working posture, criteria, assessment methods, and influencing factors, in hopes of providing references and theoretical supports for future guidelines and standards.

Prevalence of Non-specific Low Back Pain Among Chinese Healthcare Workers (Surgeons and Surgical Nurses): A Multi-Center Survey Study

Background: Low Back Pain (LBP) is one of the most common diseases affecting many persons including Healthcare Professionals (HCPs). LBP affects the quality of work and daily activities in HCPs. However, many factors contribute to LBP including age, Body Mass Index (BMI) and working experience. Purpose: The objective of this study was to assess the prevalence of LBP and examine the potential risk factors associated with LBP in Chinese HCPs (surgeons and surgical nurses). Method: A cross-sectional survey performed from October 2023 to January 2024. Quebec Back Pain Disability Scale (QBPDS) was used to assess the rating of LBP impairment. As well as Ovako Working Posture Assessment System (OWAS) is used to assess the working postures of HCPs. In addition to five more questions with yes/no answers. Results: A total of 250 surgeons and surgical nurses were collected from six hospitals with a mean age of 45.8 ± 11.0 years old, 47 females and 203 males. The BMI was 25.07 ± 1.49 kg, and working experience was 20.30 ± 10.0 years. Working hours in a week range from < 50 to > 55 hours. However, the OWAS action category was 1 in 109, 2 in 107, 3 in 30, and 4 in 4 participants. The majority of participants with mild LBP (90.4%), half of them had neck pain, and 26% with knee pain. The QBPDS scores of HCPs with LBP were 10.88 ± 4.78. Moreover, the risk factors associated with LBP include long working hours and incorrect postures of the trunk and lower extremities. As well as notice the orthopedic surgeon was the highest risk among HCPs (p = 0.046, 0.005). Conclusion: LBP is a common disorder in surgeons and surgical nurses and is associated with different factors including age, work experience, BMI, and abnormal working posture.

Risk Analysis Of Musculoskeletal Disorders (MSDs) Of The Material Handling Process In Waste Processing Operators Using The Rapid Whole Body Assessment Method

: Businesses should never stop trying to include every employee in their operations and never skimp on safety precautions. One of the safety methods in the worker-centered approach implementation is the significance of ergonomics. Typically, material handling phases in production processes include physical labor that demands a lot of operator effort. Handling objects by hand raises the possibility of workplace mishaps, which can lead to musculoskeletal injuries. This study focuses on the different labor postures used for gathering, transferring, and positioning waste as well as the manual handling of waste items up to the shredding area. This study evaluates work postures that may result in symptoms of musculoskeletal diseases using the Rapid Entire Body Assessment (REBA) technique. There are three steps in this process. Prior to lowering the waste bucket to the designated place, gather the trash first, then hoist and carry it till it reaches the mechanical area. Three grades 9, 2, and 6 were obtained from the analysis utilizing the REBA (Rapid Entire Body Assessment) approach. Based on these findings, the first stage has to be improved right away. Thus, in order to meet the improvement objective, we created a telescopic reach that enables employees to change the height a device that aids in bettering workers' posture while picking up trash.

Analisis Postur Kerja Pada Bagian Packing Menggunakan Metode ManTRA Dan REBA

PT. Indonesia Plafon Semesta is a company engaged in manufacturing, this company produces various kinds of PVC ceilings. Problems faced by PT. Indonesia Plafon Semesta is the activity of making PVC ceilings in the packing section, where the activity conditions or workers' posture is not good. When packing by squatting and bending, the position is less ergonomic, resulting in excessive force exertion and the risk of injury. This research aims to determine the level of complaints felt by workers in body parts by identifying them using the Nordic Body Map (NBM), Manual Task Risk Assessment (ManTRA) to determine the level of risk experienced by workers and knowing how many angles are formed. Rapid Entire Body Assessment (REBA) is used to calculate worker posture and provide a score of the worker's proposed posture using Anthropometry. Data processing was carried out using NBM calculations for workers who had the highest score of 51 and the lowest 44. Knowing the level of risk experienced by workers with Mantra protection with the back, forearms, neck and wrists > 15 and the angle formed in the REBA calculation using score 10. Improvement of the proposed posture with Anthropomerti with a TPO calculation of 32.5 cm and JTD cm of 69 by paying attention to the object being worked on with REBA calculation results having a score of 7.

INVESTIGATION OF THE RELATIONSHIP BETWEEN WORKING POSTURES OF PHYSIOTHERAPISTS WORKING IN SPECIAL EDUCATION AND REHABILITATION CENTERS AND HOSPITALS WITH PAIN, BODY AWARENESS LEVEL, CHRONIC FATIGUE AND DEPRESSION

This study aims to examine the relationship between physiotherapists' working posture and pain, body awareness level, chronic fatigue, and depression levels and to determine whether these parameters depend on the institution where they work. 93 randomly selected physiotherapists between the ages of 24-52 were divided into two groups according to their institutions: Rehabilitation centers/hospitals. Working posture was evaluated with the Ovako Working Posture Analysing System (OWAS), pain was evaluated with the Extended Nordic Musculoskeletal Questionnaire (NMQ-E) and Visual Analogue Scale (VAS), body awareness level was evaluated with the Body Awareness Questionnaire (BAQ), chronic fatigue was evaluated with the Chronic Fatigue Syndrome/Self Assessment Form (CFS), depression level was evaluated with the Beck Depression Inventory (BDI). A relationship was found between OWAS-leg posture and NMQ-E-ankle pain (r=-0.238), between OWAS-back posture-arm posture-action class and VAS (r1=0.25; r2=-0.27; r3=0.23), and between OWAS-back posture-action class and BDI (r1=0.25; r2=0.26) (p

Research on the Hydrodynamic Characteristics of a Rectangular Otter Board in Different Work Postures Based on a Dynamic Model

This paper investigates the hydrodynamic characteristics of a rectangular otter board in different working postures by using a dynamic model. Dynamic models are mainly based on dynamic mesh techniques. The results of the dynamic model are, compared to the model test, carried out in a flume tank. Furthermore, different rotation speeds of dynamic model were analyzed. The research results are as follows: compared to flume tank results, the maximum error of the dynamic model is 23.77%. Moreover, the influence of rotation speed on the hydrodynamic board is not obvious, and 2 deg./s was chosen as the rotation speed. When the board is tilted slightly (including four working postures), its lift-to-drag ratio first increases slightly and then gradually decreases. Compared with the other three working postures, the pressure center coefficient of the board does not change significantly when it is tilted inward. When studying different working angles (including AOA and tilt angle) of the otter board, the numerical dynamic model significantly reduces repetitive setup work, making simulations more efficient. Its ability to provide continuous curves and a large volume of results offers researchers a more detailed and comprehensive understanding of the board’s hydrodynamics. Additionally, the dynamic model supports innovative fishery equipment development by allowing more accurate and continuous numerical simulations.

Reverse Engineering to Design an Ergonomic Bio Briquette Packaging Machine

Briquettes are solids that are produced through the process of compression and pressure applicationand if burned will produce a small amount of smoke. Briquette production is carried out using ahammer mill where the raw material for briquettes is charcoal which is then crushed into charcoalgranules. The packaging process is still done manually using a shovel to fill the 50kg sack and thentake it to the sewing machine. The worker's posture when using a shovel has a Rapid Entire BodyAssessment (REBA) score of 12 so it has a high work risk of musculoskeletal disorders (MSDs) andrequires immediate improvement. The working environment at the company produces pollutants,meaning that there is no capture container for the fall of charcoal grains from the hammer mill. Basedon the existing problems, a redesign of the existing machine is needed. The proposed machine wasdesigned using the Reverse Engineering method because the existing condition already uses themachine then the existing machine is decomposed to find out the components and functions of theexisting machine to find alternative concepts. The ergonomic approach uses REBA and LBA todetermine changes in worker posture and the forces acting in the human spine. The DEM approachwas chosen to find out if the charcoal grains dropped from the hammer mill were successfully capturedand to find out the flow of the charcoal grains. The results of the proposed machine design have agood impact on workers in the packaging process.

Leveraging wearable sensors and machine learning for posture-based detection of carpal tunnel syndrome

Abstract Carpal tunnel is associated with long-term use of the wrist and hand for various activities such as typing, welding, or poor working postures. Carpal Tunnel Syndrome (CTS) may cause severe pain and discomfort in the hand and wrist, and in some circumstances, surgery becomes inevitable. The objective of this study is to prevent typing postures, which can be ascertained as predisposing subjects to CTS development. The data used in this study is an array of wrist wearable sensors to capture flexion, extension, and bending of fingers while using a keyboard or mouse. Machine learning is employed on the data in order to identify risk factors indicative of a high probability of CTS. The analyzed models are linear regression, Support Vector Machine, Random Forest, Multilayer Perceptron, Convolution Neural Network, and Long Short Term Memory. The conditions for assessing the performance of the data models include RMS error, coefficients of determination, and mean absolute percentage error. In this research, I conducted an exploratory data analysis (EDA) to gain an initial understanding of the dataset. Following the exploratory phase, I applied feature extraction techniques, specifically Principal Component Analysis (PCA). As put forward for the proposed research, the strategies to prevent risky occupations have broad potential at the present time, especially in the case of CTS when preventing repetitive wrist movements.

Analysis of poor work postures during morning care operations of intensive care unit nurses: a field research

BackgroundPoor working postures in morning care operations contribute significantly to work-related muscle fatigue and low back pain among ICU (Intensive Care Unit, ICU) nurses. However,there are few field studies on the relationship between Poor working postures and work-related muscle fatigue, low back pain among ICU nurses.ObjectiveThis study aims to assess the frequency and degree of posture hazards associated with poor working postures during morning care operations of ICU nurses.MethodsTwo ICUs in a Grade-A tertiary hospital in Hunan Province were randomly selected for the field study in May–June 2021 research. The image data of the participating nurses’ morning care work postures were collected by observation method and image recording method, and the postural hazard level was assessed by the two-person interpretation method of the work posture analysis system. The mean and standard deviation, frequency and percentage were used for the basic statistical description, and the general linear model multivariate Hotelling’s T2 test was used to calculate the Hotelling’s T2 and F statistics to explore the pattern of change in the postural hazard score curves.ResultsA total of 45 nurses were observed during morning care operations, resulting in 47.8 h of video data and 34,428 effective static operation posture pictures. Among these pictures, 21,166 (61.5%) depicted poor working postures. Nurses spent up to 7 min and 30 s maintaining a challenging posture during oral care, with the highest postural hazard score (M = 2.2, SD = 0.3) observed during defecation care. Each patient requires a total of 25–30 min of oral care per day.The Hotelling’s T2 test indicated that the change curve of the postural hazard score in each step revealed the largest second-order F value, F = 52.931, P < 0.001.DiscussionICU nurses frequently adopt poor working postures during morning care operations. Further research should focus on optimizing safe working postures to prevent or minimise detrimental occupational hazards resulting from poor working postures.Research on occupational low back pain among ICU nurses can help them work more efficiently, and thereby improving their nursing level.

View Selection of Safety Managers Affects Their Ability to Evaluate Safety Level of Workers

Evaluating the safety level of work behaviors is an important means of safety management through safety managers’ manual visual or video surveillance. This paper aims to grasp the view selection rules of safety managers in correctly observing and analyzing work behavior, which are conducive to safety behavior assessment. Firstly, based on a similarity simulation experiment, the work process of the operators was simulated, and the process was simultaneously monitored from multiple views to obtain surveillance videos. Then, safety managers with different experience levels watched the videos and answered the questionnaire in a questionnaire survey experiment. The authors found the following: (1) Prior experience does not affect the view selection during the observation stage, but it does affect the view selection during the analysis stage. Experienced safety managers perform better in view selection when dealing with complex tasks. (2) The work postures have a significant effect on the view type and their combination order. (3) The view selection of experienced safety managers in the behavior observation and analysis stages is non-constant except for sitting posture operations, while the view selection of amateur managers is always constant. (4) Sitting posture work takes the front view as the main view and the left–right–upper views as auxiliary views; standing posture uses the left and right views as the main views and the front–back–upper views as auxiliary views; and mixed posture takes the left and right views as the main views and the upper–front–back views as auxiliary views. These view selection rules can achieve the highest evaluation performance. These findings can help train or select high-quality safety managers and provide a scientific basis for arranging views during video surveillance.

Systematic Literature Review: The Effect of Work Posture on Musculoskeletal Disorders in Goods Loading and Unloading Workers

In lifting and transporting activities, many are still done manually, so in this activity, it is necessary to have the correct work posture when carrying out lifting and transporting goods. Lifting activities with the wrong working posture can increase the risk of occupational diseases, namely musculoskeletal disorders. This study aims to find out whether there is an influence of work posture on musculoskeletal disorders. The research method used is a literature review of seven journals that have been selected based on inclusion criteria. The results of this study showed that in lifting and transporting activities, work posture affects musculoskeletal disorders, so there is a need to improve the abnormal working posture in lifting activities.

Work Posture Analysis in The Chips Frying Section Using Workplace Ergonomic Risk Assessment Method

U.D. Keripik Mustika is a small and medium enterprise (SME) that processes yam raw materials into special snacks in great demand for consumption and souvenirs. According to observations, the worker experienced pain complaints during frying in the shoulder area, arms, back, waist, hands, and feet. The complaint experienced by this worker was due to the worker's posture that had to stand and bend slightly with the position of the hands continuously mixing for 7 hours a day and done manually repeatedly over long periods. This is if left, then the worker will suffer musculoskeletal disorders (MSDs). The research was conducted using the WERA method (Workplace Ergonomic Risk Assessment), which explains the development of ergonomic risk assessment at the workplace to detect physical risk factors associated with musculoskeletal disorders (MSDs). The spread of the Nordic Body Map questionnaire on frying workers showed pain complaints from an unergonomic working posture. The study results were obtained from Employee 1, with a physical indicator score of 39 (Medium), and Employee 2, with a physical indicator score of 37 (Medium). Therefore, there is a need for improvement of the work facilities or the worker's posture. Based on the assessment results, the researchers suggested additional facilities for workers to design standing aids that reduce pain in the leg muscles and complaints of Musculoskeletal Disorders (MSDs).

Work-related musculoskeletal disorder and health risk behaviors in market-vendors: a mixed-methods study.

Work-related musculoskeletal disorders (WRMDs) are frequently observed among market vendors, and engaging in health risk behaviors can exacerbate these issues, leading to various health problems. Common health risk behaviors among market vendors include alcohol consumption and insufficient physical activity. However, there is currently a lack of research examining the prevalence of WRMDs and health risk behaviors among market vendors in Bangkok. Furthermore, the emerging trend of drug misuse within this group remains poorly understood. This study aims to explore the prevalence of muscle pain and flexibility issues and assess health risk behaviors, including alcohol consumption, inadequate exercise, and drug misuse, among market vendors. A mixed-method study was undertaken among 213 market vendors in Bangkok. Data collection utilized direct observation techniques, questionnaires, and muscle flexibility tests. Qualitative data were elucidated and showcased through textual descriptions and quotations. Quantitative data were analyzed using descriptive statistics to present numerical and percentage values. Qualitative findings revealed that market vendors often engage in static muscular work and maintain awkward postures due to their job characteristics and workstation setups. Quantitatively, the right arm was the most common pain region (34.7%), followed by the left leg (31.0%), right leg (30.0%), and left arm (28.6%). Additionally, 64.3% of participants showed poor muscle flexibility. The study also found that 35% of market vendors resorted to alcohol and 11.7% to drug misuse to cope with fatigue and prevent adverse symptoms. Moreover, 68.5% of participants reported no regular exercise due to lack of time. The study highlights the prevalence of musculoskeletal issues among market vendors, largely attributed to static muscular work and awkward postures dictated by their job roles and workstation arrangements. The right arm emerged as the most commonly affected area, followed by the left leg, right leg, and left arm, with significant rates of reported pain. The research also points to a notable lack of muscle flexibility in a majority of vendors and a concerning tendency towards alcohol and drug misuse as coping mechanisms for fatigue and symptom management. Furthermore, a significant portion of the vendors do not participate in regular exercise, primarily due to time constraints. These findings can be used to implement health prevention programs within the market vendor group.

The Effect of Workload and Work Posture through Musculoskeletal Disorders on Work Achievement of Nurses Hermina Hospital Makassar

The Effect of Workload and Work Posture through Musculoskeletal Disorders on Work Achievement of Nurses Hermina Hospital Makassar

The Effect of Working Posture on Musculoskeletal Disorders Complaints Moderated By Smoking Copra Workers in Tanjung Balai, Asahan Regency

&lt;div&gt;&lt;table cellspacing="0" cellpadding="0" align="left"&gt;&lt;tbody&gt;&lt;tr&gt;&lt;td align="left" valign="top"&gt;&lt;p&gt;&lt;em&gt;Musculoskeletal complaints refer to discomfort or pain in the musculoskeletal system, ranging from mild to severe. One type of job that is particularly prone to musculoskeletal disorders is copra work, primarily due to poor working posture. This study aims to analyze the effect of working posture on musculoskeletal disorder complaints among copra workers in Tanjung Balai, Asahan Regency. The study is an analytical survey with a cross-sectional design, conducted in Bandar Jawa Village, Tanjung Balai Subdistrict, Asahan Regency, from December 2023 to February 2024. The study population consisted of all 139 copra workers in Bandar Jawa Village, and a sample of 104 workers was selected using the Slovin formula. The sampling technique employed was simple random sampling. Data were collected through surveys and questionnaires administered to respondents. The research instruments used were the Nordic Body Map and the Rapid Entire Body Assessment (REBA) evaluation sheet. Data analysis was performed using SPSS version 24, with three stages: univariate analysis using frequency, bivariate analysis using simple linear regression, and multivariate analysis using Moderated Regression Analysis (MRA) with a significance level of 95% (α=0.05). The results showed that working posture significantly affected musculoskeletal disorder complaints, moderated by smoking habits, with a p-value of 0.001. It can be concluded that smoking exacerbates the negative effects of poor working posture on musculoskeletal health, increasing the risk of injury and slowing recovery. It is recommended that copra workers take preventive measures against musculoskeletal disorder complaints by improving their work environment, paying attention to rest periods, engaging in light relaxation exercises, and that employers provide education on worker safety and health to copra workers.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt; &lt;/em&gt;&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt;&lt;/div&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Keywords: &lt;/em&gt;&lt;/strong&gt; &lt;strong&gt;&lt;em&gt;Musculoskeletal disorders, Smoking, Work posture&lt;/em&gt;&lt;/strong&gt;&lt;/p&gt;

Postural analysis and ergonomic intervention of unorganized workers in indian construction sectors.

In India's fast-growing economy, the construction sector offers significant developments with huge employment opportunities but poses risks due to poor working environments and uncomfortable postures. Traditional methods, such as manual material handling, can lead to health hazards and musculoskeletal disorders such as overexertion, low back pain, etc. The purpose of this study was to analyze the working postures of unorganized employees engaged in residential buildings using Ergofellow software and to recommend changes in their unsafe working postures. Participants' working positions were video recorded and the postures were analyzed using Rapid Upper Limb Assessment (RULA), Rapid Entire Body Assessment (REBA) and Ovako Working Posture Analysis (OWAS). Paired sample t-tests were used to analyze significant differences between the RULA and REBA scores after the ergonomic interventions were implemented. From the analysis of RULA, REBA and OWAS, the working postures showed a high risk of potential injury and required an immediate change in employees' working postures. The RULA and REBA scores were subsequently lower after the ergonomic interventions, which were based on ergonomic and safety principles. The paired sample t-tests with p-values of less than 0.05 demonstrated decreased risks after ergonomic interventions. Working postures of the construction workers exposed to musculoskeletal disorders were examined and the ergonomic interventions were implemented. According to the recommendations, working positions were changed, and employee well-being was enhanced by reduced operational risks.

ERG-AI: enhancing occupational ergonomics with uncertainty-aware ML and LLM feedback

Workers, especially those involved in jobs requiring extended standing or repetitive movements, often face significant health challenges due to Musculoskeletal Disorders (MSDs). To mitigate MSD risks, enhancing workplace ergonomics is vital, which includes forecasting long-term employee postures, educating workers about related occupational health risks, and offering relevant recommendations. However, research gaps remain, such as the lack of a sustainable AI/ML pipeline that combines sensor-based, uncertainty-aware posture prediction with large language models for natural language communication of occupational health risks and recommendations. We introduce ERG-AI, a machine learning pipeline designed to predict extended worker postures using data from multiple wearable sensors. Alongside providing posture prediction and uncertainty estimates, ERG-AI also provides personalized health risk assessments and recommendations by generating prompts based on its performance and prompting Large Language Model (LLM) APIs, like GPT-4, to obtain user-friendly output. We used the Digital Worker Goldicare dataset to assess ERG-AI, which includes data from 114 home care workers who wore five tri-axial accelerometers in various bodily positions for a cumulative 2913 hours. The evaluation focused on the quality of posture prediction under uncertainty, energy consumption and carbon footprint of ERG-AI and the effectiveness of personalized recommendations rendered in easy-to-understand language.