I-Corps: Laparotomy simulator with mechanical feedback for surgical training

Texas Tech University, Lubbock TX

Investigators

Abstract

The broader impact/commercial potential of this I-Corps project is the development of a platform for training surgical residents to practice and improve critical suturing techniques for laparotomy. This is expected to enhance resident learning during simulation training, which may translate to improved knowledge and muscle memory. The learning experience may improve knowledge, skills, and readiness for surgical residents, which may result in improved clinical outcomes. Expected outcomes include the minimization of complications following abdominal closing and better patient well-being and satisfaction as more well-prepared physicians enter practice. Effective development and deployment of this technology may significantly lower the barrier required to train surgeons for advanced surgical procedures, and result in an improvement in healthcare training and practices. This I-Corps project is based on the development of a simulation software platform for surgical training. The proposed human-in-the-loop learning approach is a surgical laparotomy simulation with mechanical feedback additionally supported with instruction by an experienced surgeon suitable to effective surgical training. The device may lead to a better understanding of how human errors in suturing affects force distributions in sutured biomaterials, and which strategies for suturing are the most optimal mechanically. In addition, it may be used to match the learning approach to the capabilities of the trainees that are at different training stages. The proposed technology also may be used to simulate patients from diverse backgrounds, which may lead to knowledge of how variances of mechanics and geometry presents challenges in determining the best techniques for surgical operations. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.