Timely and widespread access to medical care has become one of the greatest societal concerns today, pushed to the forefront by the Covid-19 outbreak. Exacerbating the problem is that there is a growing shortage of general surgeons in the US, and hundreds of rural hospitals are projected to close in the coming years. This Faculty Early Career Development (CAREER) project produces much-needed research towards realizing autonomous surgery in the future to address these broad societal issues of healthcare access and equity challenges. Specifically, the project involves taking a big step of realizing autonomous surgical robots is imbuing them with knowledge of human anatomy and physiology in a transcribed form that can be leveraged by artificial intelligence for performing procedures autonomously. As part of the project, an educational plan that integrates closely with the research plan is planned. An interactive lesson-game for high school students is to be developed, and an experience in a classroom setting is planned in which they will explore programming and biology in a video game.
To achieve the overall goal of this project, dense and reduced-order models for representing multimodal, deformable tissue environments with semantic attributes will be investigated and neural networks to approximate the forward and inverse problem. An anatomical roadmap is defined that presents the human body as a semantic navigation problem, and local context can be leveraged to perform semantic localization and environment mapping. For semantic localization, theory and strategies for leveraging semantic labels in deformable scenes and methods will be defined, utilizing geometric priors and active manipulation to identify features and classify scene objects. Finally, given contextually informed observation models, anatomical context may be used to evaluate and optimize safe plans and robust trajectories as well as higher-level decision making such as behavior trees. The educational activity involving teaching students about programming and biology will focus on teaching anatomical context from a biological perspective and basic sequential logic from a block-programming perspective. As part of an interactive lesson, the activity includes a hands-on programming portion that involves building an autonomous agent to solve an educational surgical simulator videogame. Following the interactive lesson, survey data on their perceptions regarding STEM and the potential interdisciplinary nature of biology and computer science will be collected and parsed. Then, by making the activities open-sourced and incorporating our lessons learned, we aim for our videogame to reach underrepresented minorities and provide them an opportunity to experience the broader, multi-disciplinary opportunities that computer science, engineering, and biology have to offer.
This project is supported by the cross-directorate Foundational Research in Robotics program, jointly managed and funded by the Directorates for Engineering (ENG) and Computer and Information Science and Engineering (CISE).
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.
