Date of Award
Industrial and Manufacturing Systems Engineering
Computer Vision, Dentist, Ergonomic, Media pipe, Pose estimation, Posture
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
ABSTRACT Utilizing ergonomic designs is crucial to prevent musculoskeletal disorders (MSDs), which affect a range from 64% to 93% of dentists. However, limited studies have explored dentists' posture and its musculoskeletal impacts. Previous research has neglected the impact of dental units on dentists' posture. Therefore, this study aims to identify which dental units (front or side delivery) provide the most optimal ergonomic conditions for dentists during their work. In addition, it aims to evaluate whether computer vision technology can accurately extract dentists' pose graphs performing dental procedures. Two dentists and four patients were involved in an experiment examining how Front and Side Delivery systems impact dentists' postures during tooth preparation. Video data were collected and analyzed utilizing the RULA metric for precise posture assessment. Additionally, a computer vision algorithm analyzed the captured posture, and the results of calculated angles were compared with expert evaluations to determine the accuracy of posture assessment in dentists. The study results indicate a pressing need for ergonomic interventions, as over 87.3% of the collected data yielded final RULA scores exceeding 6, indicating a high risk of MSDs. RULA scores for the neck and trunk during dental tasks surpassed those for other body parts. The use of computer vision to detect key points produced body angles comparable to expert assessments, underscoring the technology's potential for accurate ergonomic measurements. The results illustrate a range of differences, ranging from 2° to 7.75° for front delivery and from 1.5° to 8° for the side delivery system in each body angle measurement. Ongoing advancements in posture capture methods, particularly with motion capture systems, provide detailed insights into ergonomic challenges, enabling targeted interventions to enhance the well-being of dental professionals.
Sadeghi, Seyedehfatemeh, "Computer Vision-based Ergonomic Assessment of Dentists Using Different Dental Units" (2024). Electronic Theses and Dissertations. 9173.
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