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Touchless Heart Rate Monitoring from an Unmanned Aerial Vehicle Using Videoplethysmography

Motivation: The advancement of preventive medicine and, subsequently, telemedicine drives the need for noninvasive and remote measurements in patients’ natural environments. Heart rate (HR) measurements are particularly promising and extensively researched due to their quick assessment and comprehen...

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Autores principales: Pająk, Anna, Przybyło, Jaromir, Augustyniak, Piotr
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10459503/
https://www.ncbi.nlm.nih.gov/pubmed/37631834
http://dx.doi.org/10.3390/s23167297
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author Pająk, Anna
Przybyło, Jaromir
Augustyniak, Piotr
author_facet Pająk, Anna
Przybyło, Jaromir
Augustyniak, Piotr
author_sort Pająk, Anna
collection PubMed
description Motivation: The advancement of preventive medicine and, subsequently, telemedicine drives the need for noninvasive and remote measurements in patients’ natural environments. Heart rate (HR) measurements are particularly promising and extensively researched due to their quick assessment and comprehensive representation of patients’ conditions. However, in scenarios such as endurance training or emergencies, where HR measurement was not anticipated and direct access to victims is limited, no method enables obtaining HR results that are suitable even for triage. Methods: This paper presents the possibility of remotely measuring of human HR from a series of in-flight videos using videoplethysmography (VPG) along with skin detection, human pose estimation and image stabilization methods. An unmanned aerial vehicle (UAV) equipped with a camera captured ten segments of video footage featuring volunteers engaged in free walking and running activities in natural sunlight. The human pose was determined using the OpenPose algorithm, and subsequently, skin areas on the face and forearms were identified and tracked in consecutive frames. Ultimately, HR was estimated using several VPG methods: the green channel (G), green-red difference (GR), excess green (ExG), independent component analysis (ICA), and a plane orthogonal to the skin (POS). Results: When compared to simultaneous readings from a reference ECG-based wearable recorder, the root-mean-squared error ranged from 17.7 (G) to 27.7 (POS), with errors of less than 3.5 bpm achieved for the G and GR methods. Conclusions: These results demonstrate the acceptable accuracy of touchless human pulse measurement with the accompanying UAV-mounted camera. The method bridges the gap between HR-transmitting wearables and emergency HR recorders, and it has the potential to be advantageous in training or rescue scenarios in mountain, water, disaster, or battlefield settings.
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spelling pubmed-104595032023-08-27 Touchless Heart Rate Monitoring from an Unmanned Aerial Vehicle Using Videoplethysmography Pająk, Anna Przybyło, Jaromir Augustyniak, Piotr Sensors (Basel) Article Motivation: The advancement of preventive medicine and, subsequently, telemedicine drives the need for noninvasive and remote measurements in patients’ natural environments. Heart rate (HR) measurements are particularly promising and extensively researched due to their quick assessment and comprehensive representation of patients’ conditions. However, in scenarios such as endurance training or emergencies, where HR measurement was not anticipated and direct access to victims is limited, no method enables obtaining HR results that are suitable even for triage. Methods: This paper presents the possibility of remotely measuring of human HR from a series of in-flight videos using videoplethysmography (VPG) along with skin detection, human pose estimation and image stabilization methods. An unmanned aerial vehicle (UAV) equipped with a camera captured ten segments of video footage featuring volunteers engaged in free walking and running activities in natural sunlight. The human pose was determined using the OpenPose algorithm, and subsequently, skin areas on the face and forearms were identified and tracked in consecutive frames. Ultimately, HR was estimated using several VPG methods: the green channel (G), green-red difference (GR), excess green (ExG), independent component analysis (ICA), and a plane orthogonal to the skin (POS). Results: When compared to simultaneous readings from a reference ECG-based wearable recorder, the root-mean-squared error ranged from 17.7 (G) to 27.7 (POS), with errors of less than 3.5 bpm achieved for the G and GR methods. Conclusions: These results demonstrate the acceptable accuracy of touchless human pulse measurement with the accompanying UAV-mounted camera. The method bridges the gap between HR-transmitting wearables and emergency HR recorders, and it has the potential to be advantageous in training or rescue scenarios in mountain, water, disaster, or battlefield settings. MDPI 2023-08-21 /pmc/articles/PMC10459503/ /pubmed/37631834 http://dx.doi.org/10.3390/s23167297 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Pająk, Anna
Przybyło, Jaromir
Augustyniak, Piotr
Touchless Heart Rate Monitoring from an Unmanned Aerial Vehicle Using Videoplethysmography
title Touchless Heart Rate Monitoring from an Unmanned Aerial Vehicle Using Videoplethysmography
title_full Touchless Heart Rate Monitoring from an Unmanned Aerial Vehicle Using Videoplethysmography
title_fullStr Touchless Heart Rate Monitoring from an Unmanned Aerial Vehicle Using Videoplethysmography
title_full_unstemmed Touchless Heart Rate Monitoring from an Unmanned Aerial Vehicle Using Videoplethysmography
title_short Touchless Heart Rate Monitoring from an Unmanned Aerial Vehicle Using Videoplethysmography
title_sort touchless heart rate monitoring from an unmanned aerial vehicle using videoplethysmography
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10459503/
https://www.ncbi.nlm.nih.gov/pubmed/37631834
http://dx.doi.org/10.3390/s23167297
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