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Occupational Diseases

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Experimental evaluation of a novel robotic hospital bed mover with omni-directional mobility.

Applied ergonomics
Bed pushing during patient transfer is one of the most physically demanding and yet common tasks in the hospital setting. Powered bed movers have been increasingly introduced to hospitals to reduce physiological strains on the users. This study intro...

Prediction Effects of Personal, Psychosocial, and Occupational Risk Factors on Low Back Pain Severity Using Artificial Neural Networks Approach in Industrial Workers.

Journal of manipulative and physiological therapeutics
OBJECTIVES: This study aimed to provide an empirical model of predicting low back pain (LBP) by considering the occupational, personal, and psychological risk factor interactions in workers population employed in industrial units using an artificial ...

Applying Machine Learning to Workers' Compensation Data to Identify Industry-Specific Ergonomic and Safety Prevention Priorities: Ohio, 2001 to 2011.

Journal of occupational and environmental medicine
OBJECTIVE: This study leveraged a state workers' compensation claims database and machine learning techniques to target prevention efforts by injury causation and industry.

A machine learning approach to detect changes in gait parameters following a fatiguing occupational task.

Ergonomics
The purpose of this study is to provide a method for classifying non-fatigued vs. fatigued states following manual material handling. A method of template matching pattern recognition for feature extraction ($1 Recognizer) along with the support vect...

Ergonomic intervention on a packing workstation with robotic aid -case study at a furniture manufacturing industry.

Work (Reading, Mass.)
BACKGROUND: Several risk factors among packing lines workers can lead to Work-related Musculoskeletal Disorders (WRMSD) occurrence. Foreseeing WRMSD prevention and productivity increase, some furniture manufacturing industries have been investing in ...

Measuring Biomechanical Risk in Lifting Load Tasks Through Wearable System and Machine-Learning Approach.

Sensors (Basel, Switzerland)
Ergonomics evaluation through measurements of biomechanical parameters in real time has a great potential in reducing non-fatal occupational injuries, such as work-related musculoskeletal disorders. Assuming a correct posture guarantees the avoidance...

A novel vision-based real-time method for evaluating postural risk factors associated with musculoskeletal disorders.

Applied ergonomics
Real-time risk assessment for work-related musculoskeletal disorders (MSD) has been a challenging research problem. Previous methods such as using depth cameras suffered from limited visual range and wearable sensors could cause intrusiveness to the ...

PEDF, a pleiotropic WTC-LI biomarker: Machine learning biomarker identification and validation.

PLoS computational biology
Biomarkers predict World Trade Center-Lung Injury (WTC-LI); however, there remains unaddressed multicollinearity in our serum cytokines, chemokines, and high-throughput platform datasets used to phenotype WTC-disease. To address this concern, we used...

A Deep-Learning Based Posture Detection System for Preventing Telework-Related Musculoskeletal Disorders.

Sensors (Basel, Switzerland)
The change from face-to-face work to teleworking caused by the pandemic has induced multiple workers to spend more time than usual in front of a computer; in addition, the sudden installation of workstations in homes means that not all of them meet t...

Evolution of the biomechanical dimension of the professional gestures of grinders when using a collaborative robot.

International journal of occupational safety and ergonomics : JOSE
Using a cobot could relieve workers of strenuous and repetitive tasks while preserving their expertise. To understand the consequences of using a cobot on the occurrence of musculoskeletal disorders (MSDs), within a theoretical framework based on act...