Postural Assessment in Dentistry Based on Multiple Markers Tracking

Abstract

Postural assessment is a fundamental aspect to prevent long-term Musculoskeletal disorders (MSDs) due to fatiguing jobs. Operative dentistry also belongs to this category and we developed a Computer Vision approach to automatically analyze the dentist posture during operations obtaining an evaluation of MSD risk according to some well-established criteria like RULA and NERPA. In particular we analyze three different set-ups where the dentist operates with naked eyes, medical loupes or using a surgical microscope and we compared the postural effects of these three different configurations. The results present a significant improvement in posture using the microscope and validated our approach as a feasible and effective method to assess posture in fatiguing jobs. The proposed approach allows a continuous monitoring of job activity evaluating accurately posture criticalities. Furthermore the risk of MSD based on international criteria is evaluated in an objective and accurate way. The whole proposed system follows a non-invasive approach based on Augmented Reality markers tracked from a distant camera and can be applied to effective monitoring different working activities providing an accurate and objective estimation of MSD according to modern posture assessment criteria.

Cite

Text

Marcon et al. "Postural Assessment in Dentistry Based on Multiple Markers Tracking." IEEE/CVF International Conference on Computer Vision Workshops, 2017. doi:10.1109/ICCVW.2017.167

Markdown

[Marcon et al. "Postural Assessment in Dentistry Based on Multiple Markers Tracking." IEEE/CVF International Conference on Computer Vision Workshops, 2017.](https://mlanthology.org/iccvw/2017/marcon2017iccvw-postural/) doi:10.1109/ICCVW.2017.167

BibTeX

@inproceedings{marcon2017iccvw-postural,
  title     = {{Postural Assessment in Dentistry Based on Multiple Markers Tracking}},
  author    = {Marcon, Marco and Pispero, Alberto and Pignatelli, Nicola and Lodi, Giovanni and Tubaro, Stefano},
  booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
  year      = {2017},
  pages     = {1408-1415},
  doi       = {10.1109/ICCVW.2017.167},
  url       = {https://mlanthology.org/iccvw/2017/marcon2017iccvw-postural/}
}