Progressive Dynamic Time Warping for Noninvasive Blood Pressure Estimation

Arterial blood pressure is one of the most important cardiovascular parameters. Yet, current-generation devices for continuous, noninvasive acquisition are few, expensive and bulky. Novel signal processing applied to easily acquired unimodal signals can alleviate this issue, reducing size, cost and...

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Autores principales:	Pielmus Alexandru-Gabriel, Klum Michael, Tigges Timo, Orglmeister Reinhold, Urban Mike
Formato:	article
Lenguaje:	EN
Publicado:	De Gruyter 2020
Materias:	progressive dynamic time warping arterial blood pressure impedance photo plethysmography noninvasive continuous unobtrusive dtw ppg ipg Medicine R
Acceso en línea:	https://doaj.org/article/b1398ff3e9444ff49756409152c8292d
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spelling	oai:doaj.org-article:b1398ff3e9444ff49756409152c8292d2021-12-05T14:10:43ZProgressive Dynamic Time Warping for Noninvasive Blood Pressure Estimation2364-550410.1515/cdbme-2020-3148https://doaj.org/article/b1398ff3e9444ff49756409152c8292d2020-09-01T00:00:00Zhttps://doi.org/10.1515/cdbme-2020-3148https://doaj.org/toc/2364-5504Arterial blood pressure is one of the most important cardiovascular parameters. Yet, current-generation devices for continuous, noninvasive acquisition are few, expensive and bulky. Novel signal processing applied to easily acquired unimodal signals can alleviate this issue, reducing size, cost and expanding the use of such devices to ambulatory, everyday settings. The features of pulse waves acquired by photo- or impedance-plethysmography can be used to estimate the underlying blood pressure. We present a progressive dynamic time warping algorithm, which implicitly parametrizes the morphological changes in these waves. This warping method is universally applicable to most pulse wave shapes, as it is largely independent of fiducial point detection or explicit parametrization. The algorithm performance is validated in a feature selection and regression framework against a continuous, noninvasive Finapres NOVA monitor, regarding systolic, mean and diastolic pressures during a light physical strain test protocol on four clinically healthy subjects (age18- 33, one female). The obtained mean error is 2.13 mmHg, the mean absolute error is 5.4 mmHg and the standard deviation is 5.6 mmHg. These results improve on our previous work on dynamic time warping. Using single-sensor, peripherally acquired pulse waves, progressive dynamic time warping can thus improve the flexibility of noninvasive, continuous blood pressure estimation.Pielmus Alexandru-GabrielKlum MichaelTigges TimoOrglmeister ReinholdUrban MikeDe Gruyterarticleprogressive dynamic time warpingarterial blood pressureimpedancephoto plethysmographynoninvasivecontinuousunobtrusivedtwppgipgMedicineRENCurrent Directions in Biomedical Engineering, Vol 6, Iss 3, Pp 579-582 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	progressive dynamic time warping arterial blood pressure impedance photo plethysmography noninvasive continuous unobtrusive dtw ppg ipg Medicine R
spellingShingle	progressive dynamic time warping arterial blood pressure impedance photo plethysmography noninvasive continuous unobtrusive dtw ppg ipg Medicine R Pielmus Alexandru-Gabriel Klum Michael Tigges Timo Orglmeister Reinhold Urban Mike Progressive Dynamic Time Warping for Noninvasive Blood Pressure Estimation
description	Arterial blood pressure is one of the most important cardiovascular parameters. Yet, current-generation devices for continuous, noninvasive acquisition are few, expensive and bulky. Novel signal processing applied to easily acquired unimodal signals can alleviate this issue, reducing size, cost and expanding the use of such devices to ambulatory, everyday settings. The features of pulse waves acquired by photo- or impedance-plethysmography can be used to estimate the underlying blood pressure. We present a progressive dynamic time warping algorithm, which implicitly parametrizes the morphological changes in these waves. This warping method is universally applicable to most pulse wave shapes, as it is largely independent of fiducial point detection or explicit parametrization. The algorithm performance is validated in a feature selection and regression framework against a continuous, noninvasive Finapres NOVA monitor, regarding systolic, mean and diastolic pressures during a light physical strain test protocol on four clinically healthy subjects (age18- 33, one female). The obtained mean error is 2.13 mmHg, the mean absolute error is 5.4 mmHg and the standard deviation is 5.6 mmHg. These results improve on our previous work on dynamic time warping. Using single-sensor, peripherally acquired pulse waves, progressive dynamic time warping can thus improve the flexibility of noninvasive, continuous blood pressure estimation.
format	article
author	Pielmus Alexandru-Gabriel Klum Michael Tigges Timo Orglmeister Reinhold Urban Mike
author_facet	Pielmus Alexandru-Gabriel Klum Michael Tigges Timo Orglmeister Reinhold Urban Mike
author_sort	Pielmus Alexandru-Gabriel
title	Progressive Dynamic Time Warping for Noninvasive Blood Pressure Estimation
title_short	Progressive Dynamic Time Warping for Noninvasive Blood Pressure Estimation
title_full	Progressive Dynamic Time Warping for Noninvasive Blood Pressure Estimation
title_fullStr	Progressive Dynamic Time Warping for Noninvasive Blood Pressure Estimation
title_full_unstemmed	Progressive Dynamic Time Warping for Noninvasive Blood Pressure Estimation
title_sort	progressive dynamic time warping for noninvasive blood pressure estimation
publisher	De Gruyter
publishDate	2020
url	https://doaj.org/article/b1398ff3e9444ff49756409152c8292d
work_keys_str_mv	AT pielmusalexandrugabriel progressivedynamictimewarpingfornoninvasivebloodpressureestimation AT klummichael progressivedynamictimewarpingfornoninvasivebloodpressureestimation AT tiggestimo progressivedynamictimewarpingfornoninvasivebloodpressureestimation AT orglmeisterreinhold progressivedynamictimewarpingfornoninvasivebloodpressureestimation AT urbanmike progressivedynamictimewarpingfornoninvasivebloodpressureestimation
_version_	1718371804240674816

Progressive Dynamic Time Warping for Noninvasive Blood Pressure Estimation

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