Janitor ergonomics and injuries in the safe workload ergonomic exposure project (SWEEP) study

Schwartz, Adam; Gerberich, Susan Goodwin; Kim, Hyun; Ryan, Andrew D.; Albin, Thomas; McGovern, Patricia M.; Erdman, Arthur; Green, Deirdre R.; Arauz, Rony F.

doi:10.1016/j.apergo.2019.102874

Cited by 20 publications

(9 citation statements)

References 73 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Back injuries are common in jobs involving prolonged standing and long hours (Kamani and Kalwar2021). Likewise, it is monotonous manual jobs that have a high rate of injury potential (Schwartz et al 2019). As long as there is a high-frequency task that demands a lot of effort in an inadequate posture, the probability of occurrence of this disorder will be higher (Caroly et al 2010).…”

Section: Literature Reviewmentioning

confidence: 99%

Ergonomic improvement in a roll-forming station for a metal-mechanical company

Camet,

Tweddle,

Taquía Gutiérrez

2022

Proceedings of the International Conference on Industrial Engineering and Operations Management

View full text Add to dashboard Cite

The present research seeks to design and implement an ergonomic improvement in the roll-forming station of a metalmechanical company, where the incidence rate for low back pain is 29.4%. The methodology used to evaluate the situation prior to the improvement was the NIOSH equation, where the risk of injury was found to be 3.30 at the origin and 3.57 at the destination. According to NIOSH benchmarks, these factors constitute a high risk of injury and urgent intervention. Following the design and implementation of the improvement, the NIOSH equation was again used to demonstrate the decrease in risk presented by the operation. An improvement of 81.5% in the rate of lifting at the origin and 73.4% at the destination was achieved. The research presented validity in the NIOSH equation, helping to corroborate the effectiveness obtained by the design and implementation of an ergonomic improvement, thus reducing the probability of injury,and increasing job satisfaction.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Ergonomic improvement in a roll-forming station for a metal-mechanical company

Camet,

Tweddle,

Taquía Gutiérrez

2022

Proceedings of the International Conference on Industrial Engineering and Operations Management

View full text Add to dashboard Cite

show abstract

“…According to the Bureau of Labor Statistics, as of May 2020, there were nearly two million people employed as janitors and cleaners in the US, and the growing speed of the industry was estimated to be as fast as the average for all occupations (Bureau of Labor Statistics, 2021). Given its labor-intensive nature, cleaning job exposes workers to significant occupational hazards, including both physical and mental work-related injuries (Schwartz et al, 2019). While typical cleaning tasks may have relatively low force requirements, they are usually repetitive, demand awkward postures, and have a strict time limit, making the job have one of the highest workplace incident rates (Bureau of Labor Statistics, 2016).…”

Section: Introductionmentioning

confidence: 99%

Human Acceptance of the Cleaning Robot in Grocery Environments During the COVID-19 Pandemic

Chen

Luo

Yerebakan

et al. 2022

Proceedings of the Human Factors and Ergonomics Society Annual

View full text Add to dashboard Cite

Cleaning work is a labor-intensive job that frequently exposes workers to substantial occupational hazards. Unfortunately, the outbreak of coronavirus disease 2019 (COVID-19) has increased the pressure on janitors and cleaners to meet the rising need for a safe and hygienic environment, particularly in grocery stores, where the majority of people get their daily necessities. To reduce the occupational hazards and fulfill the new challenges of COVID-19, autonomous cleaning robots, have been designed to complement human workers. However, a lack of understanding of the new generation of cleaning tools’ acceptance may raise safety concerns when they’re deployed. Therefore, a video-based survey was developed and distributed to 32 participants, aiming to assess human acceptance of the cleaning robot in grocery environments during the COVID-19 pandemic. Moreover, the effects of four factors (gender, work experience, knowledge, and pet) that may influence human acceptance of the cleaning robot were also examined. In general, our findings revealed a non-negative human acceptance of the cleaning robot, which is a positive sign of deploying cleaning robots in grocery stores to reduce the workload of employees and decrease COIVID-related anxiety and safety concerns of customers. Furthermore, prior knowledge of robotics was observed to have a significant effect on participants’ acceptance of the cleaning robot ( p = 0.039).

show abstract

“…Hignett and McAtamney [ 16 ] evaluated the precision of REBA and found that 62–85% of expert users scored similarly for all the selected postures, except for the upper arm [ 20 ]. Schwartz et al [ 23 ] studied eight janitorial tasks and found that the average REBA scores for all tasks were in high-risk categories. Eight observers used the REBA method to evaluate their tasks and verified the reliability of REBA in practice (ICC = 0.925).…”

Section: Introductionmentioning

confidence: 99%

“…Eight observers used the REBA method to evaluate their tasks and verified the reliability of REBA in practice (ICC = 0.925). The observers were highly confident in using the REBA method after standardized training [ 23 ]. Thus, the REBA method has high accuracy, can thoroughly evaluate the risk of factory workers’ working posture, and can perform automatic evaluation through algorithms.…”

Section: Introductionmentioning

confidence: 99%

An Evaluation of Posture Recognition Based on Intelligent Rapid Entire Body Assessment System for Determining Musculoskeletal Disorders

Zhang

Lee

et al. 2020

Sensors

View full text Add to dashboard Cite

Determining the potential risks of musculoskeletal disorders through working postures in a workplace is expensive and time-consuming. A novel intelligent rapid entire body assessment (REBA) system based on convolutional pose machines (CPM), entitled the Quick Capture system, was applied to determine the risk levels. The aim of the study was to validate the feasibility and reliability of the CPM-based REBA system through a simulation experiment. The reliability was calculated from the differences of motion angles between the CPM-based REBA and a motion capture system. Results show the data collected by the Quick Capture system were consistent with those of the motion capture system; the average of root mean squared error (RMSE) was 4.77 and the average of Spearman’s rho (ρ) correlation coefficient in the different 12 postures was 0.915. For feasibility evaluation, the linear weighted Cohen’s kappa between the REBA score obtained by the Quick Capture system and those from the three experts were used. The result shows good agreement, with an average proportion agreement index (P0) of 0.952 and kappa of 0.738. The Quick Capture system does not only accurately analyze working posture, but also accurately determines risk level of musculoskeletal disorders. This study suggested that the Quick Capture system could be applied for a rapid and real-time on-site assessment.

show abstract

Janitor ergonomics and injuries in the safe workload ergonomic exposure project (SWEEP) study

Cited by 20 publications

References 73 publications

Ergonomic improvement in a roll-forming station for a metal-mechanical company

Ergonomic improvement in a roll-forming station for a metal-mechanical company

Human Acceptance of the Cleaning Robot in Grocery Environments During the COVID-19 Pandemic

An Evaluation of Posture Recognition Based on Intelligent Rapid Entire Body Assessment System for Determining Musculoskeletal Disorders

Contact Info

Product

Resources

About