Contactless analysis of heart rate variability during cold pressor test using radar interferometry and bidirectional LSTM networks

Abstract Contactless measurement of heart rate variability (HRV), which reflects changes of the autonomic nervous system (ANS) and provides crucial information on the health status of a person, would provide great benefits for both patients and doctors during prevention and aftercare. However, gold...

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Autores principales:	Kilin Shi, Tobias Steigleder, Sven Schellenberger, Fabian Michler, Anke Malessa, Fabian Lurz, Nicolas Rohleder, Christoph Ostgathe, Robert Weigel, Alexander Koelpin
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/9b34ec364a13450daab3c8fd95e3ccf8
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spelling	oai:doaj.org-article:9b34ec364a13450daab3c8fd95e3ccf82021-12-02T14:06:19ZContactless analysis of heart rate variability during cold pressor test using radar interferometry and bidirectional LSTM networks10.1038/s41598-021-81101-12045-2322https://doaj.org/article/9b34ec364a13450daab3c8fd95e3ccf82021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-81101-1https://doaj.org/toc/2045-2322Abstract Contactless measurement of heart rate variability (HRV), which reflects changes of the autonomic nervous system (ANS) and provides crucial information on the health status of a person, would provide great benefits for both patients and doctors during prevention and aftercare. However, gold standard devices to record the HRV, such as the electrocardiograph, have the common disadvantage that they need permanent skin contact with the patient. Being connected to a monitoring device by cable reduces the mobility, comfort, and compliance by patients. Here, we present a contactless approach using a 24 GHz Six-Port-based radar system and an LSTM network for radar heart sound segmentation. The best scores are obtained using a two-layer bidirectional LSTM architecture. To verify the performance of the proposed system not only in a static measurement scenario but also during a dynamic change of HRV parameters, a stimulation of the ANS through a cold pressor test is integrated in the study design. A total of 638 minutes of data is gathered from 25 test subjects and is analysed extensively. High F-scores of over 95% are achieved for heartbeat detection. HRV indices such as HF norm are extracted with relative errors around 5%. Our proposed approach is capable to perform contactless and convenient HRV monitoring and is therefore suitable for long-term recordings in clinical environments and home-care scenarios.Kilin ShiTobias SteiglederSven SchellenbergerFabian MichlerAnke MalessaFabian LurzNicolas RohlederChristoph OstgatheRobert WeigelAlexander KoelpinNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Kilin Shi Tobias Steigleder Sven Schellenberger Fabian Michler Anke Malessa Fabian Lurz Nicolas Rohleder Christoph Ostgathe Robert Weigel Alexander Koelpin Contactless analysis of heart rate variability during cold pressor test using radar interferometry and bidirectional LSTM networks
description	Abstract Contactless measurement of heart rate variability (HRV), which reflects changes of the autonomic nervous system (ANS) and provides crucial information on the health status of a person, would provide great benefits for both patients and doctors during prevention and aftercare. However, gold standard devices to record the HRV, such as the electrocardiograph, have the common disadvantage that they need permanent skin contact with the patient. Being connected to a monitoring device by cable reduces the mobility, comfort, and compliance by patients. Here, we present a contactless approach using a 24 GHz Six-Port-based radar system and an LSTM network for radar heart sound segmentation. The best scores are obtained using a two-layer bidirectional LSTM architecture. To verify the performance of the proposed system not only in a static measurement scenario but also during a dynamic change of HRV parameters, a stimulation of the ANS through a cold pressor test is integrated in the study design. A total of 638 minutes of data is gathered from 25 test subjects and is analysed extensively. High F-scores of over 95% are achieved for heartbeat detection. HRV indices such as HF norm are extracted with relative errors around 5%. Our proposed approach is capable to perform contactless and convenient HRV monitoring and is therefore suitable for long-term recordings in clinical environments and home-care scenarios.
format	article
author	Kilin Shi Tobias Steigleder Sven Schellenberger Fabian Michler Anke Malessa Fabian Lurz Nicolas Rohleder Christoph Ostgathe Robert Weigel Alexander Koelpin
author_facet	Kilin Shi Tobias Steigleder Sven Schellenberger Fabian Michler Anke Malessa Fabian Lurz Nicolas Rohleder Christoph Ostgathe Robert Weigel Alexander Koelpin
author_sort	Kilin Shi
title	Contactless analysis of heart rate variability during cold pressor test using radar interferometry and bidirectional LSTM networks
title_short	Contactless analysis of heart rate variability during cold pressor test using radar interferometry and bidirectional LSTM networks
title_full	Contactless analysis of heart rate variability during cold pressor test using radar interferometry and bidirectional LSTM networks
title_fullStr	Contactless analysis of heart rate variability during cold pressor test using radar interferometry and bidirectional LSTM networks
title_full_unstemmed	Contactless analysis of heart rate variability during cold pressor test using radar interferometry and bidirectional LSTM networks
title_sort	contactless analysis of heart rate variability during cold pressor test using radar interferometry and bidirectional lstm networks
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/9b34ec364a13450daab3c8fd95e3ccf8
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Contactless analysis of heart rate variability during cold pressor test using radar interferometry and bidirectional LSTM networks

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