Development of an Automated Smartphone-Based Suture Evaluation System

Objective: Quantification of skill level in surgical training is necessary for effective skill development. In this study, we report the development of a smartphone application that automatically and objectively evaluates training in stitching goldfish scoop poi, a fragile material currently used for practice by young surgeons in Japan. Methods: The application, named “e-Suture,” enables the automatic evaluation of surgical technique quality by evaluating the gap between the mark printed on the poi and the insertion/extraction point of the needle (Accuracy), analyzing suture placement (Deflection), detecting tears in the poi material/tissue (Tears), and the time taken to perform the exercise (Time). The algorithm for scoring used a sigmoid function, and the coefficients were adjusted so that the scores of a sample of 20 cases ranged between 20 and 100 points. Results: The e-Suture prototype was completed. The e-Suture-derived ranking for 20 poi after training was significantly correlated with the mean of the rankings evaluated by 9 experts (correlation coefficient: 0.728; p = 0.000). We also tested which items the experts rated as the most important. The overall ratings obtained from the experts correlated with the e-Suture accuracy scoring results with a correlation coefficient of 0.836 (p = 0.000) for Accuracy, 0.31 (p = 0.173) for Deflection, and 0.518 (p = 0.019) for Tear. Conclusion: The e-Suture application can easily and accurately quantify and evaluate the suturing skills of novie surgeons. Further studies should improve the accuracy of data to be analyzed by collecting more surgical data and applying it to other surgical techniques.