Validation of a Semi-Classical Signal Analysis method for stroke volume variation assessment: A comparison with the PiCCO technique

Meriem Laleg; Claire Médigue; Yves Papelier; François Cottin; Andry Van De Louw

doi:10.1007/s10439-010-0118-z

Validation of a Semi-Classical Signal Analysis method for stroke volume variation assessment: A comparison with the PiCCO technique

Meriem Laleg^*, Claire Médigue, Yves Papelier, François Cottin, Andry Van De Louw

^*Corresponding author for this work

Computer, Electrical and Mathematical Science and Engineering

Research output: Contribution to journal › Article › peer-review

11 Scopus citations

Abstract

This study proposes a Semi-Classical Signal Analysis (SCSA) method for stroke volume (SV) variations assessment from arterial blood pressure measurements. One of the SCSA parameters, the first systolic invariant (INVS₁), has been shown to be linearly related to SV. To technically validate this approach, the comparison between INVS₁ and SV measured with the currently used PiCCO technique was performed during a 15-min recording in 20 mechanically ventilated patients in intensive care. A strong correlation was estimated by linear regression and cross-correlation analysis (mean coefficient = 0.90 ± 0.01 SEM at the two tests).

Original language	English (US)
Pages (from-to)	3618-3629
Number of pages	12
Journal	Annals of Biomedical Engineering
Volume	38
Issue number	12
DOIs	https://doi.org/10.1007/s10439-010-0118-z
State	Published - Jan 1 2010

Keywords

Arterial blood pressure
First systolic invariant
PiCCO
Semi-classical signal analysis
Stroke volume variations

ASJC Scopus subject areas

Biomedical Engineering

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title = "Validation of a Semi-Classical Signal Analysis method for stroke volume variation assessment: A comparison with the PiCCO technique",

abstract = "This study proposes a Semi-Classical Signal Analysis (SCSA) method for stroke volume (SV) variations assessment from arterial blood pressure measurements. One of the SCSA parameters, the first systolic invariant (INVS1), has been shown to be linearly related to SV. To technically validate this approach, the comparison between INVS1 and SV measured with the currently used PiCCO technique was performed during a 15-min recording in 20 mechanically ventilated patients in intensive care. A strong correlation was estimated by linear regression and cross-correlation analysis (mean coefficient = 0.90 ± 0.01 SEM at the two tests).",

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Validation of a Semi-Classical Signal Analysis method for stroke volume variation assessment : A comparison with the PiCCO technique. / Laleg, Meriem; Médigue, Claire; Papelier, Yves; Cottin, François; Van De Louw, Andry.

In: Annals of Biomedical Engineering, Vol. 38, No. 12, 01.01.2010, p. 3618-3629.

Research output: Contribution to journal › Article › peer-review

TY - JOUR

T1 - Validation of a Semi-Classical Signal Analysis method for stroke volume variation assessment

T2 - A comparison with the PiCCO technique

AU - Laleg, Meriem

AU - Médigue, Claire

AU - Papelier, Yves

AU - Cottin, François

AU - Van De Louw, Andry

PY - 2010/1/1

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N2 - This study proposes a Semi-Classical Signal Analysis (SCSA) method for stroke volume (SV) variations assessment from arterial blood pressure measurements. One of the SCSA parameters, the first systolic invariant (INVS1), has been shown to be linearly related to SV. To technically validate this approach, the comparison between INVS1 and SV measured with the currently used PiCCO technique was performed during a 15-min recording in 20 mechanically ventilated patients in intensive care. A strong correlation was estimated by linear regression and cross-correlation analysis (mean coefficient = 0.90 ± 0.01 SEM at the two tests).

AB - This study proposes a Semi-Classical Signal Analysis (SCSA) method for stroke volume (SV) variations assessment from arterial blood pressure measurements. One of the SCSA parameters, the first systolic invariant (INVS1), has been shown to be linearly related to SV. To technically validate this approach, the comparison between INVS1 and SV measured with the currently used PiCCO technique was performed during a 15-min recording in 20 mechanically ventilated patients in intensive care. A strong correlation was estimated by linear regression and cross-correlation analysis (mean coefficient = 0.90 ± 0.01 SEM at the two tests).

KW - Arterial blood pressure

KW - First systolic invariant

KW - PiCCO

KW - Semi-classical signal analysis

KW - Stroke volume variations

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JO - Annals of Biomedical Engineering

JF - Annals of Biomedical Engineering

SN - 0090-6964

IS - 12

ER -

Validation of a Semi-Classical Signal Analysis method for stroke volume variation assessment: A comparison with the PiCCO technique

Abstract

Keywords

ASJC Scopus subject areas

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