skip to main content


Search for: All records

Creators/Authors contains: "Eom, S."

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. Augmented Reality (AR) is increasingly used in medical applications for visualizing medical information. In this paper, we present an AR-assisted surgical guidance system that aims to improve the accuracy of catheter placement in ventriculostomy, a common neurosurgical procedure. We build upon previous work on neurosurgical AR, which has focused on enabling the surgeon to visualize a patient’s ventricular anatomy, to additionally integrate surgical tool tracking and contextual guidance. Specifically, using accurate tracking of optical markers via an external multi-camera OptiTrack system, we enable Microsoft HoloLens 2-based visualizations of ventricular anatomy, catheter placement, and the information on how far the catheter tip is from its target. We describe the system we developed, present initial hologram registration results, and comment on the next steps that will prepare our system for clinical evaluations. 
    more » « less
  2. Robust pervasive context-aware augmented reality (AR) has the potential to enable a range of applications that support users in reaching their personal and professional goals. In such applications, AR can be used to deliver richer, more immersive, and more timely just in time adaptive interventions (JITAI) than conventional mobile solutions, leading to more effective support of the user. This position paper defines a research agenda centered on improving AR applications' environmental, user, and social context awareness. Specifically, we argue for two key architectural approaches that will allow pushing AR context awareness to the next level: use of wearable and Internet of Things (IoT) devices as additional data streams that complement the data captured by the AR devices, and the development of edge computing-based mechanisms for enriching existing scene understanding and simultaneous localization and mapping (SLAM) algorithms. The paper outlines a collection of specific research directions in the development of such architectures and in the design of next-generation environmental, user, and social context awareness algorithms. 
    more » « less