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Real-time breath recognition by movies from a small drone landing on victim’s bodies

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 o...

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Autores principales: Saitoh, Takeji, Takahashi, Yoshiaki, Minami, Hisae, Nakashima, Yukako, Aramaki, Shuhei, Mihara, Yuki, Iwakura, Takamasa, Odagiri, Keiichi, Maekawa, Yuichiro, Yoshino, Atsuto
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7930045/
https://www.ncbi.nlm.nih.gov/pubmed/33658612
http://dx.doi.org/10.1038/s41598-021-84575-1
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author Saitoh, Takeji
Takahashi, Yoshiaki
Minami, Hisae
Nakashima, Yukako
Aramaki, Shuhei
Mihara, Yuki
Iwakura, Takamasa
Odagiri, Keiichi
Maekawa, Yuichiro
Yoshino, Atsuto
author_facet Saitoh, Takeji
Takahashi, Yoshiaki
Minami, Hisae
Nakashima, Yukako
Aramaki, Shuhei
Mihara, Yuki
Iwakura, Takamasa
Odagiri, Keiichi
Maekawa, Yuichiro
Yoshino, Atsuto
author_sort Saitoh, Takeji
collection PubMed
description 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.
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spelling pubmed-79300452021-03-04 Real-time breath recognition by movies from a small drone landing on victim’s bodies Saitoh, Takeji Takahashi, Yoshiaki Minami, Hisae Nakashima, Yukako Aramaki, Shuhei Mihara, Yuki Iwakura, Takamasa Odagiri, Keiichi Maekawa, Yuichiro Yoshino, Atsuto Sci Rep Article 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. Nature Publishing Group UK 2021-03-03 /pmc/articles/PMC7930045/ /pubmed/33658612 http://dx.doi.org/10.1038/s41598-021-84575-1 Text en © The Author(s) 2021, corrected publication 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Saitoh, Takeji
Takahashi, Yoshiaki
Minami, Hisae
Nakashima, Yukako
Aramaki, Shuhei
Mihara, Yuki
Iwakura, Takamasa
Odagiri, Keiichi
Maekawa, Yuichiro
Yoshino, Atsuto
Real-time breath recognition by movies from a small drone landing on victim’s bodies
title Real-time breath recognition by movies from a small drone landing on victim’s bodies
title_full Real-time breath recognition by movies from a small drone landing on victim’s bodies
title_fullStr Real-time breath recognition by movies from a small drone landing on victim’s bodies
title_full_unstemmed Real-time breath recognition by movies from a small drone landing on victim’s bodies
title_short Real-time breath recognition by movies from a small drone landing on victim’s bodies
title_sort real-time breath recognition by movies from a small drone landing on victim’s bodies
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7930045/
https://www.ncbi.nlm.nih.gov/pubmed/33658612
http://dx.doi.org/10.1038/s41598-021-84575-1
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