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Prediction of Work-Related Risk Factors among Bus Drivers Using Machine Learning.

Pradeep Kumar Hanumegowda¹, Sakthivel Gnanasekaran²

¹School of Mechanical Engineering, Vellore Institute of Technology, Chennai 600127, India.

International Journal of Environmental Research and Public Health

|November 26, 2022

Summary

This summary is machine-generated.

Machine learning accurately identified key risk factors for work-related musculoskeletal diseases (WMSDs) in bus drivers. Interventions focusing on physical activity, posture, and ergonomic cabin design are recommended for injury prevention.

Keywords:

BMTC decision tree machine learning naïve Bayes random forest

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Area of Science:

Ergonomics and Occupational Health
Machine Learning in Healthcare
Musculoskeletal Disorder Research

Background:

Bus drivers face high risks of work-related musculoskeletal diseases (WMSDs) due to job demands and working conditions.
Ergonomics research increasingly utilizes machine learning for risk assessment and injury prevention in occupational settings.

Purpose of the Study:

To forecast critical work-related risk variables associated with WMSDs in bus drivers using machine learning.
To identify significant health and work-related factors contributing to WMSDs among this population.

Main Methods:

A questionnaire survey using the Modified Nordic Musculoskeletal Questionnaire (MNMQ) was administered to 400 bus drivers.
Machine learning algorithms including decision tree, random forest, and naïve Bayes were employed for risk factor prediction.
Statistical analysis was performed to determine the significance of WMSDs and work-related characteristics.

Main Results:

66.75% of bus drivers reported experiencing WMSDs in the past 12 months.
Decision tree and random forest algorithms achieved 100% accuracy in predicting pain frequency, while Naïve Bayes achieved 93.28%.
Key risk factors identified include physical activity, posture changes, vibration exposure, ingress/egress, breaks, and seat adaptability.

Conclusions:

Machine learning effectively identifies significant risk factors for WMSDs in bus drivers.
Recommendations include promoting physical activity, healthy lifestyles, proper posture, and ergonomic cabin design for transport organizations.
Targeted interventions can mitigate WMSDs and improve the well-being of bus drivers.