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Kinematic and Electromyographic Assessment of Manual Handling on a Supermarket Green- Grocery Shelf

Overview
Journal Work
Publisher Sage Publications
Date 2014 Jun 26
PMID 24962301
Citations 10
Authors
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Abstract

Background: There are few epidemiological data regarding musculoskeletal disorders (MSDs) in retail industry. Biomechanical risk assessment in ergonomics is commonly performed in retail sector using standardized protocols. However, such protocols have numerous limitations, such as the lack of objectivity or applicability and restrictive conditions.

Objective: The aim of this study was to analyze one of the most commonly used shelves in vegetable and fruit departments in order to investigate the effect of different shelf levels (i.e. with variations in height and horizontal distance) and load weights on the workers' biomechanical load.

Methods: We investigated trunk, shoulder, elbow, hip, knee and ankle joint ROMs, as well as the mean and peak EMG values of the upper limb, trunk and lower limb muscles.

Results: We found that shelf level has a significant effect on most of the parameters examined, whereas within this limited range of 6 and 8 kg, weight does not affect the biomechanical load. We also identified the shelf levels that place the least and most strain on the musculoskeletal system.

Conclusions: We therefore recommend that the height and horizontal distance be carefully considered when shelves are being designed. Kinematic and EMG approach may help to objectively assess shelf-related risks. Our findings are in agreement with RNLE LI values and therefore support RNLE.

Citing Articles

Assessment of Load Manual Lifting among Shelf-Stoking Workers in Chain Stores: A Cross-Sectional Study.

Choobineh A, Dortaj E, Razeghi M, Ghaem H, Daneshmandi H Appl Bionics Biomech. 2024; 2024:2324416.

PMID: 39144397 PMC: 11324367. DOI: 10.1155/2024/2324416.


Regression-Based Machine Learning for Predicting Lifting Movement Pattern Change in People with Low Back Pain.

Phan T, Pranata A, Farragher J, Bryant A, Nguyen H, Chai R Sensors (Basel). 2024; 24(4).

PMID: 38400495 PMC: 10891548. DOI: 10.3390/s24041337.


Impaired Lumbar Extensor Force Control Is Associated with Increased Lifting Knee Velocity in People with Chronic Low-Back Pain.

Pranata A, Farragher J, Perraton L, El-Ansary D, Clark R, Meyer D Sensors (Basel). 2023; 23(21).

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Biomechanical Assessments of the Upper Limb for Determining Fatigue, Strain and Effort from the Laboratory to the Industrial Working Place: A Systematic Review.

Brambilla C, Lavit Nicora M, Storm F, Reni G, Malosio M, Scano A Bioengineering (Basel). 2023; 10(4).

PMID: 37106632 PMC: 10135542. DOI: 10.3390/bioengineering10040445.


Machine Learning Derived Lifting Techniques and Pain Self-Efficacy in People with Chronic Low Back Pain.

Phan T, Pranata A, Farragher J, Bryant A, Nguyen H, Chai R Sensors (Basel). 2022; 22(17).

PMID: 36081153 PMC: 9460822. DOI: 10.3390/s22176694.