Surgical Suturing Skill Assessment Using Estimated Hand Roll Angle from a Deep-learning Computer Vision Algorithm

Authors

• Jianxin Gao, Clemson University
• Amir Mehdi Shayan, Clemson UniversityFollow
• Simar P. Singh, Clemson University
• Joe Bible, Clemson UniversityFollow
• Ravikiran Singapogu, Clemson UniversityFollow
• Richard E. Groff, Clemson UniversityFollow

Document Type

Article

Publication Date

12-2024

Publication Title

2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

Publisher

IEEE XPlore

DOI

https://doi.org/10.1109/EMBC53108.2024.10782514

Abstract

This paper proposes a deep-learning computer vision algorithm to estimate hand roll angles for metric-based assessment of surgical suturing skills. The number of rolls metric, previously calculated directly from IMU data, counts the number of hand roll reversals during a single suture. To calculate this metric using computer vision, we apply a deep-learning algorithm that can reliably estimate hand roll angles after training on suturing videos collected on the SutureCoach simulator. Results show that the estimation accuracy of the deep-learning algorithm is robust to different video backgrounds. The number of rolls metrics were used to analyze suturing performance in the SutureCoach dataset, which includes attending and resident surgeons and novices. The means of number of rolls based on computer vision differs between most skill levels at both surface and depth conditions, a pattern which holds for number of rolls based on the IMU as well. The proposed algorithm provides a solution for non-contact hand roll angle estimation, which opens up the possibility of inter-operative surgical skill assessment. The code is available at https://github.com/axin233/hand_roll_estimation

Comments

https://pubmed.ncbi.nlm.nih.gov/40039188

Recommended Citation

J. Gao, A. M. Shayan, S. P. Singh, J. Bible, R. Singapogu and R. E. Groff, "Surgical Suturing Skill Assessment Using Estimated Hand Roll Angle from a Deep-learning Computer Vision Algorithm," 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Orlando, FL, USA, 2024, pp. 1-6, doi: 10.1109/EMBC53108.2024.10782514. keywords: {Measurement;Training;Computer vision;Visualization;Tracking;Surgery;Estimation;Cameras;Motion analysis;Videos;Deep-learning computer vision;orientation estimation;suturing simulator;surgical skill assessment}, J. Gao, A. M. Shayan, S. P. Singh, J. Bible, R. Singapogu and R. E. Groff, "Surgical Suturing Skill Assessment Using Estimated Hand Roll Angle from a Deep-learning Computer Vision Algorithm," , Orlando, FL, USA, 2024, pp. 1-6, doi: 10.1109/EMBC53108.2024.10782514.