Published 2024-12-15
Keywords
- Artificial intelligence, support vector machines, wearable device, surgical suture, surgical simulation, medical training, clinical skills assessment.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Abstract
Surgical suturing is a fundamental procedure in clinical practice, used for tissue approximation and wound healing. Although its teaching is a routine part of medical education, it faces challenges such as the limited availability of controlled scenarios, the risks of practicing on real patients, and the subjective evaluation of skills. These limitations emphasize the need for technological tools that enable safe and objective training.
This article presents the development of an artificial intelligence-based prototype for surgical suturing training, integrating kinematic sensors for data acquisition and a supervised classification model using support vector machines (SVM) to distinguish between expert and novice users. The system provides a realistic and safe practice environment, enhancing the teaching-learning process in surgery, reducing clinical risks, and strengthening the objective evaluation of surgical skills.