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A system for predicting musculoskeletal disorders among dental students
Bhornsawan Thanathornwong1, Siriwan Suebnukarn2, Kan Ouivirach3
1Faculty of Dentistry, Srinakarinwirot University, Bangkok, Thailand.
International Journal of Occupational Safety and Ergonomics : JOSE
|September 6, 2014
Summary
A new system using sensors and Hidden Markov Models (HMMs) helps predict work-related musculoskeletal disorders (WMSD) in dental students. Feedback reduced neck and upper back extension, aiding posture correction.
Area of Science:
- Biomedical Engineering
- Occupational Health
- Ergonomics
Background:
- Dental students are at high risk for work-related musculoskeletal disorders (WMSD) due to prolonged awkward postures.
- Early detection and prevention of WMSD are crucial for dental professionals' long-term health.
Purpose of the Study:
- To develop and evaluate a novel system for predicting WMSD in dental students.
- To assess the system's effectiveness in correcting neck and upper back postures.
Main Methods:
- Utilized accelerometer sensors to capture neck and upper back kinematics.
- Developed software integrating Hidden Markov Models (HMMs) for WMSD prediction.
- Conducted a 2x2 crossover trial with 16 participants to evaluate system feedback efficacy.
Main Results:
- The feedback group demonstrated a significant reduction in neck and upper back extension (y-axis) post-intervention (p < .05).
- The system accurately classified movement patterns associated with WMSD risk.
Conclusions:
- The developed system effectively aids in correcting detrimental neck and upper back postures.
- This predictive system shows promise for WMSD prevention in dental education and practice.
