While there is wide evidence that the occupational use of hand tools increases the risk of musculoskeletal disorder, evidence is limited regarding manual scissors, commonly used by custom tailors for bespoke garment production. We assessed whether scissor design impacts physical demands (muscle activity, perceived discomfort, and wrist posture) and task performance (quality and perceived efficiency). Twenty-four novice volunteers each completed simulated cutting tasks in 24 conditions involving the factorial combinations of four scissor designs (SD), three workstation heights, and two fabric types. SD significantly affected all outcome measures, and differences between SDs were consistent across workstation heights and fabric types. Two wide-handles scissors appeared superior overall, which may be related to the distinct grip type employed with this type of design. These results suggest that careful scissor selection has the potential to both reduce injury risk and enhance performance during fabric cutting tasks, though future testing is needed under more realistic conditions.
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http://dx.doi.org/10.1016/j.apergo.2020.103219 | DOI Listing |
Orthop J Sports Med
January 2025
School of Sport, Rehabilitation, and Exercise Sciences, University of Essex, Wivenhoe Park, Colchester, Essex, United Kingdom.
Background: Athletes with decreased baseline neurocognitive function may experience noncontact anterior cruciate ligament (ACL) injury in unanticipated athletic situations. Many ACL injury prevention programs (IPPs) focus on improving closed-skill movements (eg, planned landing). However, the more open-skill movements (eg, unplanned reactive movements) required in unpredictable sports scenarios are commonly absent from ACL IPPs, and the acute effects of open-skill training on neurocognitive function remain unclear.
View Article and Find Full Text PDFJ Chem Inf Model
January 2025
College of Information Science and Engineering, Huaqiao University, Xiamen 361021, China.
Machine learning methods for fitting potential energy surfaces and molecular dynamics simulations are becoming increasingly popular due to their potentially high accuracy and savings in computational resources. However, existing application models often rely on basic architectures like artificial neural networks (ANNs) and multilayer perceptron (MLP), lagging behind cutting-edge technologies in the machine learning domain. Furthermore, the complexity of current machine learning frameworks leads to reduced interpretability and challenges for improvement.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Institute of Mechanical Engineering and Energy Technology, Lucerne University of Applied Sciences and Arts, CH-6048 Horw, Switzerland.
Automated agricultural robots are becoming more common with the decreased cost of sensor devices and increased computational capabilities of single-board computers. Weeding is one of the mundane and repetitive tasks that robots could be used to perform. The detection of weeds in crops is now common, and commercial solutions are entering the market rapidly.
View Article and Find Full Text PDFInt J Environ Res Public Health
December 2024
Incheon Disaster Prevention Research Center, Incheon National University, 119 Academy-ro, Yeonsu-gu, Incheon 22012, Republic of Korea.
This study addresses occupational safety in reinforced concrete construction, an area marked by high accident rates and significant worker injury risks. By focusing on activity-body part (A-BP) combinations, this research introduces a novel framework for quantifying injury risks across construction activities. Reinforced concrete construction tasks are categorized into ten specific activities within three major work types: rebar work, formwork, and concrete placement.
View Article and Find Full Text PDFHeliyon
December 2024
Department of Pediatric and Adolescent surgery, University Hospital of Rouen, 76000, Rouen, France.
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