scholarly journals Assessing the effect of back exoskeletons on injury risk during material handling

2021 ◽  
Author(s):  
Karl E Zelik ◽  
Cameron A Nurse ◽  
Mark C Schall ◽  
Richard F Sesek ◽  
Matthew C Marino ◽  
...  
Keyword(s):  
Occupational Health ◽  
Fatigue Failure ◽  
Real World ◽  
Injury Risk ◽  
Material Handling ◽  
Health Program ◽  
Assessment Tool ◽  
Assessment Tools ◽  
Low Back ◽  
Low Back Disorders

Low back disorders (LBDs) are a leading injury in the workplace. Back exoskeletons (exos) are wearable assist devices that complement traditional ergonomic controls and reduce LBD risks by alleviating musculoskeletal overexertion. However, there are currently no ergonomic assessment tools to evaluate risk for workers wearing back exos. Exo-LiFFT, an extension of the Lifting Fatigue Failure Tool, is introduced as a means to unify the etiology of LBDs with the biomechanical function of exos. We present multiple examples demonstrating how Exo-LiFFT can assess or predict the effect of exos on LBD risk without costly, time-consuming electromyography studies. For instance, using simulated and real-world material handling data we show an exo providing a 30 Nm lumbar moment is projected to reduce cumulative back damage by about 70% and LBD risk by about 20%. Exo-LiFFT provides a practical, efficient ergonomic assessment tool to assist safety professionals exploring back exos as part of a comprehensive occupational health program.

scholarly journals A Promising Wearable Solution for the Practical and Accurate Monitoring of Low Back Loading in Manual Material Handling

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 340
Author(s):  
Emily S. Matijevich ◽  
Peter Volgyesi ◽  
Karl E. Zelik
Keyword(s):  
Injury Risk ◽  
Material Handling ◽  
Wearable Sensors ◽  
Measurement Unit ◽  
Low Back ◽  
Distributed Sensors ◽  
Manual Material Handling ◽  
Low Back Disorders ◽  
Boosted Decision Tree ◽  
Alternative Solutions

(1) Background: Low back disorders are a leading cause of missed work and physical disability in manual material handling due to repetitive lumbar loading and overexertion. Ergonomic assessments are often performed to understand and mitigate the risk of musculoskeletal overexertion injuries. Wearable sensor solutions for monitoring low back loading have the potential to improve the quality, quantity, and efficiency of ergonomic assessments and to expand opportunities for the personalized, continuous monitoring of overexertion injury risk. However, existing wearable solutions using a single inertial measurement unit (IMU) are limited in how accurately they can estimate back loading when objects of varying mass are handled, and alternative solutions in the scientific literature require so many distributed sensors that they are impractical for widespread workplace implementation. We therefore explored new ways to accurately monitor low back loading using a small number of wearable sensors. (2) Methods: We synchronously collected data from laboratory instrumentation and wearable sensors to analyze 10 individuals each performing about 400 different material handling tasks. We explored dozens of candidate solutions that used IMUs on various body locations and/or pressure insoles. (3) Results: We found that the two key sensors for accurately monitoring low back loading are a trunk IMU and pressure insoles. Using signals from these two sensors together with a Gradient Boosted Decision Tree algorithm has the potential to provide a practical (relatively few sensors), accurate (up to r2 = 0.89), and automated way (using wearables) to monitor time series lumbar moments across a broad range of material handling tasks. The trunk IMU could be replaced by thigh IMUs, or a pelvis IMU, without sacrificing much accuracy, but there was no practical substitute for the pressure insoles. The key to realizing accurate lumbar load estimates with this approach in the real world will be optimizing force estimates from pressure insoles. (4) Conclusions: Here, we present a promising wearable solution for the practical, automated, and accurate monitoring of low back loading during manual material handling.

Relationship Between Lumbar Disc Injury and Manual Lifting: A Finite Element Model Study

2007 ◽  
Author(s):  
Raghu N. Natarajan ◽  
Jamie R. Williams ◽  
Steven A. Lavender ◽  
Gunnar B. J. Andersson
Keyword(s):  
Material Handling ◽  
Lumbar Disc ◽  
Element Model ◽  
Economic Loss ◽  
The United States ◽  
Physical Work ◽  
Low Back ◽  
Back Disorders ◽  
Manual Material Handling ◽  
Low Back Disorders

Back pain has been described as one of the most common and significant musculoskeletal problems in the United States leading to substantial amounts of morbidity, disability and economic loss. Among people under 45 years of age, low back disorders (LBDs) are the leading cause of activity limitation and affects up to 47% of workers with physically demanding jobs. Low back disorders are associated with occupational lifting. Retrospective studies of industrial injuries have identified manual material handling (MMH) as the most common cause of LBD. Disc degeneration has also been associated with physical work. Thus, loading due to lifting and manual material handling is believed to be a significant factor in the development of occupationally related LBDs.

Job Rotation as a Technique for the Control of MSDs: A Fatigue Failure Perspective

2017 ◽  
Vol 61 (1) ◽  
pp. 993-994 ◽  
Author(s):  
Sean Gallagher ◽  
Mark C. Schall ◽  
Richard F. Sesek ◽  
Rong Huangfu
Keyword(s):  
Risk Assessment ◽  
High Risk ◽  
Musculoskeletal Disorders ◽  
Fatigue Failure ◽  
Assessment Tool ◽  
Low Back ◽  
Current Analysis ◽  
Job Rotation ◽  
Rotation Scheme ◽  
Medium Risk

Job rotation is a common method employed by industry to reduce the risk of musculoskeletal disorders (MSDs). However, the efficacy of this technique has been open to question and methods of quantifying job rotation strategies have been scarce. The current analysis uses the LiFFT low back risk assessment tool to assess cumulative loading for a job rotation scheme. Results of this analysis suggest that attempting to “balance” a high risk, medium risk, and low risk lifting job ends up creating three jobs that are all high risk.

Identifying Safe Load Moment Exposures for the Back

2009 ◽  
Vol 53 (14) ◽  
pp. 883-883
Author(s):  
Steven A. Lavender ◽  
William S. Marras ◽  
Sue A. Ferguson ◽  
Riley E. Splittstoesser ◽  
Gang Yang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Injury Risk ◽  
Physical Workload ◽  
Back Injury ◽  
Low Back ◽  
Distribution Centers ◽  
Back Disorders ◽  
Low Back Injury ◽  
Low Back Disorders ◽  
Back Disorder

Low back disorders continue to be the most common and significant work-related musculoskeletal disorders in the US. Identifying what constitutes a “safe” physical workload has been the biggest challenge facing injury prevention efforts. Prior low back injury risk models have focused on manufacturing activities where there is limited variability in the parameters used to describe the exposures to low back disorder risk factors. Lifting tasks in distribution centers can have considerably more variability in load and physical layout. The goal of this project was to identify and quantify measures that characterize the biomechanical risk factors, including measures of the load moment exposure, and measures that characterize the duty cycle that are predictive of low back disorders in distribution centers. Thus, our hypothesis was that we could define a relationship between moment exposure parameters and the low back disorder incidence rates. A cross-sectional study was designed to examine the mechanical risk factors responsible for reported low back injury in distributions centers. The physical exposure was measured on 195 workers on 50 jobs in 21 distribution centers using a sonic-based Moment Exposure Tracking System (METS). The METS measures load, force, load moment, torso kinematics, and temporal parameters of the job simultaneously. For each job, low back injury rates were collected retrospectively from the company's records over the prior 3-year period. The data were used to develop a risk model designed to predict back injury risk based upon direct measures of load and load moment exposure. The model incorporates biomechanical variables which include the load moment and horizontal sliding forces, as well as a temporal variable indicating the opportunity for micro-breaks during the work process. Overall, the presented model has very good sensitivity (87%) and specificity (73%).

Validation of Fatigue Failure Risk Assessment Tools Against Physician-Diagnosed Outcomes

2021 ◽  
Vol 65 (1) ◽  
pp. 710-714
Author(s):  
AJ Bandekar ◽  
Richard Sesek ◽  
Mark Schall ◽  
Rong Huangfu ◽  
Dania Bani Hani ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Fatigue Failure ◽  
Failure Process ◽  
Assessment Tools ◽  
Musculoskeletal Tissues ◽  
Failure Risk ◽  
Low Back Disorders ◽  
Risk Assessment Tools ◽  
Tunnel Syndrome ◽  
Shoulder Disorders

Evidence suggests that musculoskeletal disorders (MSDs) may be the result of a fatigue failure process in musculoskeletal tissues. Recently risk assessment tools using fatigue failure principles have been developed to evaluate risk of low back disorders (LiFFT), distal upper extremity disorders (DUET), and shoulder disorders (The Shoulder Tool). All have been validated against multiple musculoskeletal disorder outcomes such as joint pain and clinic visits for MSD complaints. This paper provides validation of DUET against occupational physician diagnosed carpal tunnel syndrome (CTS) and The Shoulder Tool against diagnosed bicipital tendinosis. Results demonstrated that in both cases the fatigue failure risk assessment tools were significantly associated with physician-diagnosed outcomes in both crude and adjusted analyses (p < 0.01).

scholarly journals Development of an observation-based tool for ergonomic exposure assessment in informal electronic waste recycling and other unregulated non-repetitive work

2020 ◽  
Vol 64 (1) ◽  
pp. 905-909
Author(s):  
Augustine A. Acquah ◽  
Clive D’Souza ◽  
Bernard Martin ◽  
John Arko-Mensah ◽  
Afua Asabea Nti ◽  
...  
Keyword(s):  
Material Handling ◽  
Assessment Tool ◽  
Electronic Waste ◽  
Waste Recycling ◽  
Assessment Tools ◽  
Observer Agreement ◽  
Cost Efficient ◽  
Vibration Time ◽  
Ergonomic Exposure ◽  
Ergonomic Exposures

Most existing ergonomic assessment tools are intended for routine work. Time- and cost- efficient observational tools for ergonomic assessment of unregulated work are lacking. This paper presents the development of an observation-based tool designed to investigate ergonomic exposures among informal electronic waste workers that could be applied to other unregulated jobs/tasks. Real-time coding of observation is used to estimate the relative duration and intensity of exposure to key work postures, forceful exertions, movements, contact stress and vibration. Time spent in manual material handling activities such as carrying, lifting and pushing/pulling of working carts are also estimated. A preliminary study conducted with 6 e-waste workers showed that the tool can easily be used with minimal training and good inter- observer agreement (i.e., 89% to 100%) for most risk factors assessed. This new assessment tool provides effective and flexible options for quantifying ergonomic exposures among workers engaged in unregulated, highly variable work.

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