Abstract

In local and global disaster scenes, rapid recognition of victims’ breathing is vital. It is unclear whether the footage transmitted from small drones can enable medical providers to detect breathing. This study investigated the ability of small drones to evaluate breathing correctly after landing on victims’ bodies and hovering over them. We enrolled 46 medical workers in this prospective, randomized, crossover study. The participants were provided with envelopes, from which they were asked to pull four notes sequentially and follow the written instructions (“breathing” and “no breathing”). After they lied on the ground in the supine position, a drone was landed on their abdomen, subsequently hovering over them. Two evaluators were asked to determine whether the participant had followed the “breathing” or “no breathing” instruction based on the real-time footage transmitted from the drone camera. The same experiment was performed while the participant was in the prone position. If both evaluators were able to determine the participant’s breathing status correctly, the results were tagged as “correct.” All experiments were successfully performed. Breathing was correctly determined in all 46 participants (100%) when the drone was landed on the abdomen and in 19 participants when the drone hovered over them while they were in the supine position (p < 0.01). In the prone position, breathing was correctly determined in 44 participants when the drone was landed on the abdomen and in 10 participants when it was kept hovering over them (p < 0.01). Notably, breathing status was misinterpreted as “no breathing” in 8 out of 27 (29.6%) participants lying in the supine position and 13 out of 36 (36.1%) participants lying in the prone position when the drone was kept hovering over them. The landing points seemed wider laterally when the participants were in the supine position than when they were in the prone position. Breathing status was more reliably determined when a small drone was landed on an individual’s body than when it hovered over them.

Highlights

  • In local and global disaster scenes, rapid recognition of victims’ breathing is vital

  • This study investigates the ability of a small cost-effective drone to evaluate breathing status correctly when it lands on a victim’s body and when it hovers over them

  • We enrolled 46 participants consisting of 23 men and 23 women

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Summary

Methods

The evaluators correctly judged the breathing status in 8 and 5 participants when the drone was landed on their bodies and when it hovered over them, respectively. The pilot flew the drone off the launch pad in the room and landed it on the participants’ umbilicus, relying on the footage the smartphone transmitted from the camera in real-time. The pilot kept the drone hovering over the participants’ body, and the participants’ breathing status was determined. After landing the drone on the participants’ bodies positioned in the supine and prone positions, we took a photograph of each participant with the drone and a scaler placed on them. The primary goal was to determine the accuracy of evaluating breathing status when the drone was landed and kept hovering. Categorical data were analyzed using the chi-square test, and accuracy was analyzed using McNemar’s analysis

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