Situated Ultrasound Training

We want to make US intuitive through spatial computing and build a system based on MagicLeap to create (1) AR visual aids and (2) AR training metrics that tackle education and give students feedback on their performance. (1) By using AR, instead of a 2D image on a flat monitor, we will show medical students a virtual US image aligned with the real US probe. Students will also see a virtual needle representing the real (hidden) needle inside the body – or a gel block during training. This type of contextualized visual confirmation is not available in any existing system, and students have to rely on expert guidance. By showing these visual aids at moments of struggle, we expect students to create a better mental model of what is happening inside the patient body. (2) Learning is a matter of repeated trials with proper supervision. However, our system will not need experts to train a novice. Through customizable training scenarios, novices will practice when they want and improve their performance based on established metrics. Our system will make learning US a game where students can play with or without supervision. This will facilitate training students in a medical school and deploying the system in remote locations.

Danilo Gasques
Danilo Gasques
Computer Science Ph.D. Candidate

Doctoral Candidate (Ph.D.) in Computer Science and Engineering with a depth in Human-Computer Interaction. My research focuses on improving remote / automated task-guidance through eXtended Reality (XR) technology.