Analysis of central venous pressure (CVP) signals using mathematical methods

Parham Atefvahid; Kamran Hassani; Kamal Jafarian; D. John Doyle; Hessam Ahmadi

doi:10.1007/s10877-016-9882-0

Analysis of central venous pressure (CVP) signals using mathematical methods

Parham Atefvahid
, Kamran Hassani
, Kamal Jafarian
, D. John Doyle
, Hessam Ahmadi

Cleveland Clinic Abu Dhabi

Islamic Azad University

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

2 Scopus citations

Abstract

Central venous pressure (CVP) is an important clinical parameter for physicians but only the absolute CVP value is typically monitored in the intensive care unit (ICU). In this study, we propose a novel mathematical method to present and analyze CVP signals. A total of 44 suitable samples were chosen from a total of 65 collected in an ICU. Pre-processing of the samples included rate reduction and digital filtering. The statistical features of time and frequency domain, wavelet, and empirical mode decomposition of these signals were extracted. We found no significant difference among the CVP signals regarding sex, smoking, coronary disease, and respiration mode of the samples.

Original language	English
Pages (from-to)	607-616
Number of pages	10
Journal	Journal of Clinical Monitoring and Computing
Volume	31
Issue number	3
DOIs	https://doi.org/10.1007/s10877-016-9882-0
State	Published - 1 Jun 2017

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Central venous pressure
Empirical mode decomposition
P value
Signal processing
Statistical analysis

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10.1007/s10877-016-9882-0

Cite this

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title = "Analysis of central venous pressure (CVP) signals using mathematical methods",

abstract = "Central venous pressure (CVP) is an important clinical parameter for physicians but only the absolute CVP value is typically monitored in the intensive care unit (ICU). In this study, we propose a novel mathematical method to present and analyze CVP signals. A total of 44 suitable samples were chosen from a total of 65 collected in an ICU. Pre-processing of the samples included rate reduction and digital filtering. The statistical features of time and frequency domain, wavelet, and empirical mode decomposition of these signals were extracted. We found no significant difference among the CVP signals regarding sex, smoking, coronary disease, and respiration mode of the samples.",

keywords = "Central venous pressure, Empirical mode decomposition, P value, Signal processing, Statistical analysis",

author = "Parham Atefvahid and Kamran Hassani and Kamal Jafarian and Doyle, \{D. John\} and Hessam Ahmadi",

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T1 - Analysis of central venous pressure (CVP) signals using mathematical methods

AU - Atefvahid, Parham

AU - Hassani, Kamran

AU - Jafarian, Kamal

AU - Doyle, D. John

AU - Ahmadi, Hessam

PY - 2017/6/1

Y1 - 2017/6/1

N2 - Central venous pressure (CVP) is an important clinical parameter for physicians but only the absolute CVP value is typically monitored in the intensive care unit (ICU). In this study, we propose a novel mathematical method to present and analyze CVP signals. A total of 44 suitable samples were chosen from a total of 65 collected in an ICU. Pre-processing of the samples included rate reduction and digital filtering. The statistical features of time and frequency domain, wavelet, and empirical mode decomposition of these signals were extracted. We found no significant difference among the CVP signals regarding sex, smoking, coronary disease, and respiration mode of the samples.

AB - Central venous pressure (CVP) is an important clinical parameter for physicians but only the absolute CVP value is typically monitored in the intensive care unit (ICU). In this study, we propose a novel mathematical method to present and analyze CVP signals. A total of 44 suitable samples were chosen from a total of 65 collected in an ICU. Pre-processing of the samples included rate reduction and digital filtering. The statistical features of time and frequency domain, wavelet, and empirical mode decomposition of these signals were extracted. We found no significant difference among the CVP signals regarding sex, smoking, coronary disease, and respiration mode of the samples.

KW - Central venous pressure

KW - Empirical mode decomposition

KW - P value

KW - Signal processing

KW - Statistical analysis

UR - https://www.scopus.com/pages/publications/84965009964

U2 - 10.1007/s10877-016-9882-0

DO - 10.1007/s10877-016-9882-0

M3 - Article

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AN - SCOPUS:84965009964

SN - 1387-1307

VL - 31

SP - 607

EP - 616

JO - Journal of Clinical Monitoring and Computing

JF - Journal of Clinical Monitoring and Computing

IS - 3

ER -

Analysis of central venous pressure (CVP) signals using mathematical methods

Abstract

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Keywords

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