For Heart Rate Assessments from Drone Footage in Disaster Scenarios
The ability to use drones to obtain important vital signs could be very valuable for emergency personnel during mass-casualty incidents. The rapid and robust remote assessment of heart rates could serve as a life-saving decision aid for first-responders. With the flight sensor data of a specialized...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-03-01
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| Series: | Bioengineering |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2306-5354/10/3/336 |
| _version_ | 1827751270218203136 |
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| author | Lucas Mösch Isabelle Barz Anna Müller Carina B. Pereira Dieter Moormann Michael Czaplik Andreas Follmann |
| author_facet | Lucas Mösch Isabelle Barz Anna Müller Carina B. Pereira Dieter Moormann Michael Czaplik Andreas Follmann |
| author_sort | Lucas Mösch |
| collection | DOAJ |
| description | The ability to use drones to obtain important vital signs could be very valuable for emergency personnel during mass-casualty incidents. The rapid and robust remote assessment of heart rates could serve as a life-saving decision aid for first-responders. With the flight sensor data of a specialized drone, a pipeline was developed to achieve a robust, non-contact assessment of heart rates through remote photoplethysmography (rPPG). This robust assessment was achieved through adaptive face-aware exposure and comprehensive de-noising of a large number of predicted noise sources. In addition, we performed a proof-of-concept study that involved 18 stationary subjects with clean skin and 36 recordings of their vital signs, using the developed pipeline in outdoor conditions. In this study, we could achieve a single-value heart-rate assessment with an overall root-mean-squared error of 14.3 beats-per-minute, demonstrating the basic feasibility of our approach. However, further research is needed to verify the applicability of our approach in actual disaster situations, where remote photoplethysmography readings could be impacted by other factors, such as blood, dirt, and body positioning. |
| first_indexed | 2024-03-11T06:55:53Z |
| format | Article |
| id | doaj.art-ced1a56e584c436db16797051f14415d |
| institution | Directory Open Access Journal |
| issn | 2306-5354 |
| language | English |
| last_indexed | 2024-03-11T06:55:53Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Bioengineering |
| spelling | doaj.art-ced1a56e584c436db16797051f14415d2023-11-17T09:39:51ZengMDPI AGBioengineering2306-53542023-03-0110333610.3390/bioengineering10030336For Heart Rate Assessments from Drone Footage in Disaster ScenariosLucas Mösch0Isabelle Barz1Anna Müller2Carina B. Pereira3Dieter Moormann4Michael Czaplik5Andreas Follmann6Department of Anesthesiology, Faculty of Medicine, RWTH Aachen University, 52074 Aachen, GermanyInstitute of Flight System Dynamics, RWTH Aachen University, 52062 Aachen, GermanyDepartment of Anesthesiology, Faculty of Medicine, RWTH Aachen University, 52074 Aachen, GermanyDepartment of Anesthesiology, Faculty of Medicine, RWTH Aachen University, 52074 Aachen, GermanyInstitute of Flight System Dynamics, RWTH Aachen University, 52062 Aachen, GermanyDepartment of Anesthesiology, Faculty of Medicine, RWTH Aachen University, 52074 Aachen, GermanyDepartment of Anesthesiology, Faculty of Medicine, RWTH Aachen University, 52074 Aachen, GermanyThe ability to use drones to obtain important vital signs could be very valuable for emergency personnel during mass-casualty incidents. The rapid and robust remote assessment of heart rates could serve as a life-saving decision aid for first-responders. With the flight sensor data of a specialized drone, a pipeline was developed to achieve a robust, non-contact assessment of heart rates through remote photoplethysmography (rPPG). This robust assessment was achieved through adaptive face-aware exposure and comprehensive de-noising of a large number of predicted noise sources. In addition, we performed a proof-of-concept study that involved 18 stationary subjects with clean skin and 36 recordings of their vital signs, using the developed pipeline in outdoor conditions. In this study, we could achieve a single-value heart-rate assessment with an overall root-mean-squared error of 14.3 beats-per-minute, demonstrating the basic feasibility of our approach. However, further research is needed to verify the applicability of our approach in actual disaster situations, where remote photoplethysmography readings could be impacted by other factors, such as blood, dirt, and body positioning.https://www.mdpi.com/2306-5354/10/3/336contactlessmass-casualty incidentdronesRGB videosignalextraction |
| spellingShingle | Lucas Mösch Isabelle Barz Anna Müller Carina B. Pereira Dieter Moormann Michael Czaplik Andreas Follmann For Heart Rate Assessments from Drone Footage in Disaster Scenarios Bioengineering contactless mass-casualty incident drones RGB video signal extraction |
| title | For Heart Rate Assessments from Drone Footage in Disaster Scenarios |
| title_full | For Heart Rate Assessments from Drone Footage in Disaster Scenarios |
| title_fullStr | For Heart Rate Assessments from Drone Footage in Disaster Scenarios |
| title_full_unstemmed | For Heart Rate Assessments from Drone Footage in Disaster Scenarios |
| title_short | For Heart Rate Assessments from Drone Footage in Disaster Scenarios |
| title_sort | for heart rate assessments from drone footage in disaster scenarios |
| topic | contactless mass-casualty incident drones RGB video signal extraction |
| url | https://www.mdpi.com/2306-5354/10/3/336 |
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