Avatar-Based Patient Monitoring With Peripheral Vision: A Multicenter Comparative Eye-Tracking Study

Abstract

Background: Continuous patient monitoring has been described by the World Health Organization as extremely important and is widely used in anesthesia, intensive care medicine, and emergency medicine. However, current state-of-the-art number- and waveform-based monitoring does not ideally support human users in acquiring quick, confident interpretations with low cognitive effort, and there are additional problematic aspects such as alarm fatigue. We developed a visualization technology (Visual Patient), specifically designed to help caregivers gain situation awareness quickly, which presents vital sign information in the form of an animated avatar of the monitored patient. We suspected that because of the way it displays the information as large, colorful, moving graphic objects, caregivers might be able to perform patient monitoring using their peripheral vision, which may facilitate quicker detection of anomalies, independently of acoustic alarms.

Objective: In this study, we tested the hypothesis that avatar-based monitoring, when observed with peripheral vision only, increases the number of perceptible changes in patient status as well as caregivers' perceived diagnostic confidence compared with a high-fidelity simulation of conventional monitoring, when observed with peripheral vision only.

Methods: We conducted a multicenter comparative study with a within-participant design in which anesthesiologists with their peripheral field of vision looked at 2 patient-monitoring scenarios and tried to identify changes in patient status. To ensure the best possible experimental conditions, we used an eye tracker, which recorded the eye movements of the participants and confirmed that they only looked at the monitoring scenarios with their peripheral vision.

Results: Overall, 30 participants evaluated 18 different patient status changes with each technology (avatar and conventional patient monitoring). With conventional patient monitoring, participants could only detect those 3 changes in patient status that are associated with a change in the auditory pulse tone display, that is, tachycardia (faster beeping), bradycardia (slower beeping), and desaturation (lower pitch of beeping). With the avatar, the median number of detected vital sign changes quadrupled from 3 to 12 (P<.001) in scenario 1, and more than doubled from 3 to 8 (P<.001) in scenario 2. Median perceived diagnostic confidence was confident for both scenarios with the avatar and unconfident in scenario 1 (P<.001), and very unconfident in scenario 2 (P=.024) with conventional monitoring.

Conclusions: This study introduces the concept of peripheral vision monitoring. The test performed showed clearly that an avatar-based display is superior to a standard numeric display for peripheral vision. Avatar-based monitoring could potentially make much more of the patient monitoring information available to caregivers for longer time periods per case. Our results indicate that the optimal information transmission would consist of a combination of auditory and avatar-based monitoring.

Keywords: anesthesia; computers; critical care; diagnosis; patient monitoring; perception; situation awareness; vision.

Figure 1

An example of a possible future application of peripheral vision monitoring in the form of an augmented reality application for patient monitoring, as Philips (Koninklijke Philips NV, Amsterdam, Netherlands) has tested on a Google (Alphabet Inc) Glass headset. If the reader looks at the center of the operating field in this photo, they can no longer read the numerical monitoring information, for example, saturation: 88%, however, they can still see that the avatar is purple and thus desaturated.

Figure 2

(A and B) Study setup: A study participant sits in front of 2 computer monitors. An eye tracker records the participant’s eye movements, which we used to confirm that the monitor on which the changes in patient condition were displayed was located in the peripheral field of view of the participant. The green funnel shows where the participant is looking and confirms that the monitor to the left remains in the peripheral visual field of the participant as long as they do not look away from the laptop screen in front. The base of the green cone corresponds to a radius of approximately 30° around the participant’s point of sharpest vision. Everything outside the funnel lies in the participant’s peripheral field of view. (C and D) The gaze plot data for 1 participant. Each point indicates a gaze fixation. A line links successive fixations.

Figure 3

The results enabled 30 direct intraparticipant comparisons. All except 2 participants achieved a better performance with the avatar. The number of perceived changes in the patient’s condition quadrupled in scenario 1 and more than doubled in scenario 2. Median perceived confidence: 0=very unconfident, 1=unconfident, 2=confident, and 3=very confident. Paired Student t tests showed statistical significance for all results.