Assessment of cardiovascular function from multi-Gaussian fitting of a finger photoplethysmogram

Standard

Assessment of cardiovascular function from multi-Gaussian fitting of a finger photoplethysmogram. / Couceiro, Ricardo; Carvalho, P; Paiva, R P; Henriques, J; Quintal, I; Antunes, M; Muehlsteff, J; Eickholt, C; Brinkmeyer, C; Kelm, M; Meyer, C.

In: PHYSIOL MEAS, Vol. 36, No. 9, 09.2015, p. 1801-1825.

Research output: SCORING: Contribution to journalSCORING: Journal articleResearchpeer-review

Harvard

Couceiro, R, Carvalho, P, Paiva, RP, Henriques, J, Quintal, I, Antunes, M, Muehlsteff, J, Eickholt, C, Brinkmeyer, C, Kelm, M & Meyer, C 2015, 'Assessment of cardiovascular function from multi-Gaussian fitting of a finger photoplethysmogram', PHYSIOL MEAS, vol. 36, no. 9, pp. 1801-1825. https://doi.org/10.1088/0967-3334/36/9/1801

APA

Couceiro, R., Carvalho, P., Paiva, R. P., Henriques, J., Quintal, I., Antunes, M., Muehlsteff, J., Eickholt, C., Brinkmeyer, C., Kelm, M., & Meyer, C. (2015). Assessment of cardiovascular function from multi-Gaussian fitting of a finger photoplethysmogram. PHYSIOL MEAS, 36(9), 1801-1825. https://doi.org/10.1088/0967-3334/36/9/1801

Vancouver

Couceiro R, Carvalho P, Paiva RP, Henriques J, Quintal I, Antunes M et al. Assessment of cardiovascular function from multi-Gaussian fitting of a finger photoplethysmogram. PHYSIOL MEAS. 2015 Sep;36(9):1801-1825. https://doi.org/10.1088/0967-3334/36/9/1801

Bibtex

@article{1005f3370d22405e90ce73c2e0893508,
title = "Assessment of cardiovascular function from multi-Gaussian fitting of a finger photoplethysmogram",
abstract = "Monitoring of cardiovascular function on a beat-to-beat basis is fundamental for protecting patients in different settings including emergency medicine and interventional cardiology, but still faces technical challenges and several limitations. In the present study, we propose a new method for the extraction of cardiovascular performance surrogates from analysis of the photoplethysmographic (PPG) signal alone.We propose using a multi-Gaussian (MG) model consisting of five Gaussian functions to decompose the PPG pulses into its main physiological components. From the analysis of these components, we aim to extract estimators of the left ventricular ejection time, blood pressure and vascular tone changes. Using a multi-derivative analysis of the components related with the systolic ejection, we investigate which are the characteristic points that best define the left ventricular ejection time (LVET). Six LVET estimates were compared with the echocardiographic LVET in a database comprising 68 healthy and cardiovascular diseased volunteers. The best LVET estimate achieved a low absolute error (15.41   ±   13.66 ms), and a high correlation (ρ = 0.78) with the echocardiographic reference.To assess the potential use of the temporal and morphological characteristics of the proposed MG model components as surrogates for blood pressure and vascular tone, six parameters have been investigated: the stiffness index (SI), the T1_d and T1_2 (defined as the time span between the MG model forward and reflected waves), the reflection index (RI), the R1_d and the R1_2 (defined as their amplitude ratio). Their association to reference values of blood pressure and total peripheral resistance was investigated in 43 volunteers exhibiting hemodynamic instability. A good correlation was found between the majority of the extracted and reference parameters, with an exception to R1_2 (amplitude ratio between the main forward wave and the first reflection wave), which correlated low with all the reference parameters. The highest correlation ([Formula: see text] = 0.45) was found between T1_2 and the total peripheral resistance index (TPRI); while in the patients that experienced syncope, the highest agreement ([Formula: see text] = 0.57) was found between SI and systolic blood pressure (SBP) and mean blood pressure (MBP).In conclusion, the presented method for the extraction of surrogates of cardiovascular performance might improve patient monitoring and warrants further investigation. ",
keywords = "Adult, Algorithms, Blood Pressure/physiology, Cardiovascular Diseases/diagnosis, Databases, Factual, Echocardiography, Doppler, Female, Fingers/blood supply, Heart Function Tests/methods, Hemodynamics/physiology, Humans, Linear Models, Male, Middle Aged, Normal Distribution, Photoplethysmography/methods",
author = "Ricardo Couceiro and P Carvalho and Paiva, {R P} and J Henriques and I Quintal and M Antunes and J Muehlsteff and C Eickholt and C Brinkmeyer and M Kelm and C Meyer",
year = "2015",
month = sep,
doi = "10.1088/0967-3334/36/9/1801",
language = "English",
volume = "36",
pages = "1801--1825",
journal = "PHYSIOL MEAS",
issn = "0967-3334",
publisher = "IOP Publishing Ltd.",
number = "9",

}

RIS

TY - JOUR

T1 - Assessment of cardiovascular function from multi-Gaussian fitting of a finger photoplethysmogram

AU - Couceiro, Ricardo

AU - Carvalho, P

AU - Paiva, R P

AU - Henriques, J

AU - Quintal, I

AU - Antunes, M

AU - Muehlsteff, J

AU - Eickholt, C

AU - Brinkmeyer, C

AU - Kelm, M

AU - Meyer, C

PY - 2015/9

Y1 - 2015/9

N2 - Monitoring of cardiovascular function on a beat-to-beat basis is fundamental for protecting patients in different settings including emergency medicine and interventional cardiology, but still faces technical challenges and several limitations. In the present study, we propose a new method for the extraction of cardiovascular performance surrogates from analysis of the photoplethysmographic (PPG) signal alone.We propose using a multi-Gaussian (MG) model consisting of five Gaussian functions to decompose the PPG pulses into its main physiological components. From the analysis of these components, we aim to extract estimators of the left ventricular ejection time, blood pressure and vascular tone changes. Using a multi-derivative analysis of the components related with the systolic ejection, we investigate which are the characteristic points that best define the left ventricular ejection time (LVET). Six LVET estimates were compared with the echocardiographic LVET in a database comprising 68 healthy and cardiovascular diseased volunteers. The best LVET estimate achieved a low absolute error (15.41   ±   13.66 ms), and a high correlation (ρ = 0.78) with the echocardiographic reference.To assess the potential use of the temporal and morphological characteristics of the proposed MG model components as surrogates for blood pressure and vascular tone, six parameters have been investigated: the stiffness index (SI), the T1_d and T1_2 (defined as the time span between the MG model forward and reflected waves), the reflection index (RI), the R1_d and the R1_2 (defined as their amplitude ratio). Their association to reference values of blood pressure and total peripheral resistance was investigated in 43 volunteers exhibiting hemodynamic instability. A good correlation was found between the majority of the extracted and reference parameters, with an exception to R1_2 (amplitude ratio between the main forward wave and the first reflection wave), which correlated low with all the reference parameters. The highest correlation ([Formula: see text] = 0.45) was found between T1_2 and the total peripheral resistance index (TPRI); while in the patients that experienced syncope, the highest agreement ([Formula: see text] = 0.57) was found between SI and systolic blood pressure (SBP) and mean blood pressure (MBP).In conclusion, the presented method for the extraction of surrogates of cardiovascular performance might improve patient monitoring and warrants further investigation.

AB - Monitoring of cardiovascular function on a beat-to-beat basis is fundamental for protecting patients in different settings including emergency medicine and interventional cardiology, but still faces technical challenges and several limitations. In the present study, we propose a new method for the extraction of cardiovascular performance surrogates from analysis of the photoplethysmographic (PPG) signal alone.We propose using a multi-Gaussian (MG) model consisting of five Gaussian functions to decompose the PPG pulses into its main physiological components. From the analysis of these components, we aim to extract estimators of the left ventricular ejection time, blood pressure and vascular tone changes. Using a multi-derivative analysis of the components related with the systolic ejection, we investigate which are the characteristic points that best define the left ventricular ejection time (LVET). Six LVET estimates were compared with the echocardiographic LVET in a database comprising 68 healthy and cardiovascular diseased volunteers. The best LVET estimate achieved a low absolute error (15.41   ±   13.66 ms), and a high correlation (ρ = 0.78) with the echocardiographic reference.To assess the potential use of the temporal and morphological characteristics of the proposed MG model components as surrogates for blood pressure and vascular tone, six parameters have been investigated: the stiffness index (SI), the T1_d and T1_2 (defined as the time span between the MG model forward and reflected waves), the reflection index (RI), the R1_d and the R1_2 (defined as their amplitude ratio). Their association to reference values of blood pressure and total peripheral resistance was investigated in 43 volunteers exhibiting hemodynamic instability. A good correlation was found between the majority of the extracted and reference parameters, with an exception to R1_2 (amplitude ratio between the main forward wave and the first reflection wave), which correlated low with all the reference parameters. The highest correlation ([Formula: see text] = 0.45) was found between T1_2 and the total peripheral resistance index (TPRI); while in the patients that experienced syncope, the highest agreement ([Formula: see text] = 0.57) was found between SI and systolic blood pressure (SBP) and mean blood pressure (MBP).In conclusion, the presented method for the extraction of surrogates of cardiovascular performance might improve patient monitoring and warrants further investigation.

KW - Adult

KW - Algorithms

KW - Blood Pressure/physiology

KW - Cardiovascular Diseases/diagnosis

KW - Databases, Factual

KW - Echocardiography, Doppler

KW - Female

KW - Fingers/blood supply

KW - Heart Function Tests/methods

KW - Hemodynamics/physiology

KW - Humans

KW - Linear Models

KW - Male

KW - Middle Aged

KW - Normal Distribution

KW - Photoplethysmography/methods

U2 - 10.1088/0967-3334/36/9/1801

DO - 10.1088/0967-3334/36/9/1801

M3 - SCORING: Journal article

C2 - 26235798

VL - 36

SP - 1801

EP - 1825

JO - PHYSIOL MEAS

JF - PHYSIOL MEAS

SN - 0967-3334

IS - 9

ER -