Mixed Reality for Training

 

The Augmented Anesthesia Machine

 

Video Overview: AAM


Overview :

The Augmented Anesthesia Machine (AAM) is a Mixed Reality system that augments an anesthesia machine with an abstract simulation of the machine’s internal workings.

The AAM gives students the ability to:

1.Interact with a real anesthesia machine – i.e. turn knobs, press buttons etc.

2.Visualize an abstract simulation of the machine’s internal workings – i.e. invisible gas flow.

The combination of 1 and 2 helps students to better understand how their interactions affect the internal workings of the machine.

 

Motivation

Eighty percent of anesthesia related operating room accidents are due to human error. These accidents occur because the anesthesiologist does not properly check the machine before a procedure. Then, when a fault in the machine occurs, the anesthesiologist cannot troubleshoot the problem quickly enough to save the patient. In order to pre-check the machine and to fix machine faults, the anesthesiologist must have a good understanding the internal gas flows and the relationships of the internal components of the machine.

To address this problem, anesthesiology educators created the now widely used Virtual Anesthesia Machine (VAM) (figure 1 left). The VAM is an interactive, abstract 2D simulation of the internal components and invisible gas flows of an anesthesia machine. However, as anesthesiology experts have noted, 20% of students still have difficulty understanding the internals in the context of the real machine.

The Augmented Anesthesia Machine (AAM) is a potential solution to this problem. The AAM uses Mixed Reality (MR) technology such as optical tracking systems and a magic lens to combine the VAM and the real anesthesia machine. Then students can interact with the real anesthesia machine and visualize how these interactions affect the internal components and invisible gas flow. The AAM facilitates new strides in the traditionally disparate fields of simulation, psychology, and anesthesiology education by using MR to effectively combine an anesthesia machine with its corresponding abstract simulation.


The Augmented Apollo:

Presented at the American Society of Anesthesiologists Conference 2008
















Publications

Quarles, J., S. Lampotang, I. Fischler, P. Fishwick, B.Lok "Scaffolded Learning with Mixed Reality" (accepted 2008) Journal of Computers and Graphics: Special Issue on VR


Quarles, J., S. Lampotang, I. Fischler, P. Fishwick, B.Lok (2008) "Tangible User Interfaces Compensate for Low Spatial Cognition" IEEE 3D User Interfaces 2008, March 8-9, Reno,NV, 11-18. 


Quarles, J., S. Lampotang, I. Fischler, P. Fishwick, B.Lok (2008) "A Mixed Reality Approach for Merging Abstract and Concrete Knowledge" IEEE Virtual Reality 2008, March 8-12, Reno, NV, 27-34..

 

Team Members        

The AAM project is multidisciplinary project including researchers from the following fields:

HCI / Mixed Reality

            John Quarles, Ph.D. Student, UF CISE

Benjamin Lok, Assistant Professor,UF CISE

Modeling and Simulation

Paul Fishwick, Professor, UF CISE

Anesthesiology

Samsun Lampotang, Professor, UF Dept of Anesthesiology

Psychology

Ira Fischler, Professor, UF Dept of Psychology

 

For more information, contact: John Quarles - jpq@cise.ufl.edu

Left: the Virtual Anesthesia Machine – a widely used abstract simulation of an anesthesia machine. middle: the Augmented Anesthesia Machine Simulation right: A student uses the magic lens to visualize the simulation from a first person perspective.

We live in a world full of black boxes. That is, we understand how to interact with objects around us (e.g. an ATM machine, a car), but most people do not understand how these objects operate internally. However, in many cases this understanding is vital, such as in medical training and practice (e.g. understanding medical devices or the human body).  For my Ph.D. work, I engineered a novel approach that can render these black boxes transparent and improve overall understanding of the world around us. To enable this, I used mixed reality to combine abstract simulations with the corresponding physical objects.