Related Experiment Video
Updated: Mar 10, 2026

The use of Biofeedback in Clinical Virtual Reality: The INTREPID Project
Published on: November 12, 2009
Utilizing virtual reality to improve ICU visual displays
Nathan Zhang1, Joy Zou2, Sungmin Kwon3
1Department of Biomedical Engineering, Vanderbilt University, 2301 Vanderbilt Place, Nashville, TN 37235, USA; Vanderbilt University School of Medicine, 1161 21st Ave S, Nashville, TN 37232, USA.
Objective:
Intensive care unit (ICU) clinicians respond to over 900 alarms per day, resulting in sensory overload that leads to delayed and inaccurate clinician responses. Integrating vital signs into object-based visual displays has been shown to yield quicker and more accurate responses than standard ICU alarm displays. We designed a ring-based visual alarm system that integrates heart rate (HR), blood pressure (BP), and peripheral oxygen sat-uration (SpO2) and evaluated its effectiveness using a virtual reality (VR) testing environment. VR offers significant advantages over traditional setups, notably by providing highly controlled, immersive, and replicable testing en-vironments.
Methods:
This display was compared against an existing graph-based dis-play that had been previously proven more effective than standard numerical ICU alarms. Using an HTC VIVE Pro Eye headset, we created controlled virtual environments to test participant speed and accuracy in identifying simulated clinical events. Tests were conducted with the graph-based, ring-based, and both displays shown, using head orientation software to determine which display participants viewed.
Results:
When shown individually, the ring-based display had 33% higher accuracy and a 1.00 s faster mean response time than the graph-based dis-play. When both displays were present, subjects viewed the ring-based dis-play 82.2% of the time. Display location in the visual field had no significant impact on performance.
Conclusion:
The ring-based display yielded improved alarm identification accuracy and response time compared to the graph-based alarm display. VR provided a robust, controlled method for testing medical interfaces. Future work should implement eye-tracking into alarm evaluation. This work's end goal is to combine our visual alarm with auditory alarms to create a multi-sensory alarm system.

