Mathematical Modeling of Arterial Blood Pressure Using Photo- Plethysmography Signal in Breath-hold Maneuver

Armin Soltan Zadi, Raichel M. Alex, Rong Zhang, Donald E. Watenpaugh, Khosrow Behbehani

Research output: Contribution to journalArticle

Abstract

recent research has shown that each apnea episode results in a significant rise of the beat-to-beat blood pressure followed by a drop to the pre-episode levels when patient resumes normal breathing. While the physiological implications of these repetitive and significant oscillations are still unknown, it is of interest to quantify them. Since current array of instruments deployed for polysomnography studies does not include beat-to-beat measurement of blood pressure, but includes oximetry which can supply pulsatile photoplethysmography (PPG) signal, in addition to percent oxygen saturation. Hence, we have investigated a new method for continuous estimation of systolic (SBP), diastolic (DBP), and mean (MBP) blood pressure waveforms from PPG. Peaks and troughs of PPG waveform are used as input to a 5th order autoregressive moving average model to construct estimates of SBP, DBP, and MBP waveforms. Since breath hold maneuvers are shown to faithfully simulate apnea episodes, we evaluated the performance of the proposed method in 7 subjects (4 F; $32 \pm 4$ yrs., BMI $24.57 \pm 3.87$ kg/m2) in supine position doing 5 breath holding maneuvers with 90s of normal breathing between them. The modeling error ranges were (all units are in mmHg $) 0.88 \pm 4.87$ to $- 2.19 \pm 5.73($ SBP); $0.29 \pm 2.39$ to $- 0.97 \pm 3.83($ DBP); and $- 0.42 \pm 2.64$ to $- 1.17 \pm 3.82($ MBP). The cross validation error ranges were $0.28 \pm 6.45$ to $- 1.74 \pm 6.55($ SBP); $0.09 \pm 3.37$ to $0.97 \pm 3.67($ DBP); and $0.33 \pm 4.34$ to $- 0.87 \pm 4.42($ MBP). The overall level of estimation error, as measured by the root mean squared of the model residuals, was less than 7 mmHg.

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Photoplethysmography
Plethysmography
Blood pressure
Arterial Pressure
Apnea
Blood Pressure
Respiration
Breath Holding
Oximetry
Polysomnography
Supine Position
Error analysis
Oxygen
Research

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Cite this

@article{807368feb9f74686bc9a83784108c520,
title = "Mathematical Modeling of Arterial Blood Pressure Using Photo- Plethysmography Signal in Breath-hold Maneuver",
abstract = "recent research has shown that each apnea episode results in a significant rise of the beat-to-beat blood pressure followed by a drop to the pre-episode levels when patient resumes normal breathing. While the physiological implications of these repetitive and significant oscillations are still unknown, it is of interest to quantify them. Since current array of instruments deployed for polysomnography studies does not include beat-to-beat measurement of blood pressure, but includes oximetry which can supply pulsatile photoplethysmography (PPG) signal, in addition to percent oxygen saturation. Hence, we have investigated a new method for continuous estimation of systolic (SBP), diastolic (DBP), and mean (MBP) blood pressure waveforms from PPG. Peaks and troughs of PPG waveform are used as input to a 5th order autoregressive moving average model to construct estimates of SBP, DBP, and MBP waveforms. Since breath hold maneuvers are shown to faithfully simulate apnea episodes, we evaluated the performance of the proposed method in 7 subjects (4 F; $32 \pm 4$ yrs., BMI $24.57 \pm 3.87$ kg/m2) in supine position doing 5 breath holding maneuvers with 90s of normal breathing between them. The modeling error ranges were (all units are in mmHg $) 0.88 \pm 4.87$ to $- 2.19 \pm 5.73($ SBP); $0.29 \pm 2.39$ to $- 0.97 \pm 3.83($ DBP); and $- 0.42 \pm 2.64$ to $- 1.17 \pm 3.82($ MBP). The cross validation error ranges were $0.28 \pm 6.45$ to $- 1.74 \pm 6.55($ SBP); $0.09 \pm 3.37$ to $0.97 \pm 3.67($ DBP); and $0.33 \pm 4.34$ to $- 0.87 \pm 4.42($ MBP). The overall level of estimation error, as measured by the root mean squared of the model residuals, was less than 7 mmHg.",
author = "Zadi, {Armin Soltan} and Alex, {Raichel M.} and Rong Zhang and Watenpaugh, {Donald E.} and Khosrow Behbehani",
year = "2018",
month = "7",
day = "1",
doi = "10.1109/EMBC.2018.8512776",
language = "English (US)",
volume = "2018",
pages = "2711--2714",
journal = "Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference",
issn = "1557-170X",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

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TY - JOUR

T1 - Mathematical Modeling of Arterial Blood Pressure Using Photo- Plethysmography Signal in Breath-hold Maneuver

AU - Zadi, Armin Soltan

AU - Alex, Raichel M.

AU - Zhang, Rong

AU - Watenpaugh, Donald E.

AU - Behbehani, Khosrow

PY - 2018/7/1

Y1 - 2018/7/1

N2 - recent research has shown that each apnea episode results in a significant rise of the beat-to-beat blood pressure followed by a drop to the pre-episode levels when patient resumes normal breathing. While the physiological implications of these repetitive and significant oscillations are still unknown, it is of interest to quantify them. Since current array of instruments deployed for polysomnography studies does not include beat-to-beat measurement of blood pressure, but includes oximetry which can supply pulsatile photoplethysmography (PPG) signal, in addition to percent oxygen saturation. Hence, we have investigated a new method for continuous estimation of systolic (SBP), diastolic (DBP), and mean (MBP) blood pressure waveforms from PPG. Peaks and troughs of PPG waveform are used as input to a 5th order autoregressive moving average model to construct estimates of SBP, DBP, and MBP waveforms. Since breath hold maneuvers are shown to faithfully simulate apnea episodes, we evaluated the performance of the proposed method in 7 subjects (4 F; $32 \pm 4$ yrs., BMI $24.57 \pm 3.87$ kg/m2) in supine position doing 5 breath holding maneuvers with 90s of normal breathing between them. The modeling error ranges were (all units are in mmHg $) 0.88 \pm 4.87$ to $- 2.19 \pm 5.73($ SBP); $0.29 \pm 2.39$ to $- 0.97 \pm 3.83($ DBP); and $- 0.42 \pm 2.64$ to $- 1.17 \pm 3.82($ MBP). The cross validation error ranges were $0.28 \pm 6.45$ to $- 1.74 \pm 6.55($ SBP); $0.09 \pm 3.37$ to $0.97 \pm 3.67($ DBP); and $0.33 \pm 4.34$ to $- 0.87 \pm 4.42($ MBP). The overall level of estimation error, as measured by the root mean squared of the model residuals, was less than 7 mmHg.

AB - recent research has shown that each apnea episode results in a significant rise of the beat-to-beat blood pressure followed by a drop to the pre-episode levels when patient resumes normal breathing. While the physiological implications of these repetitive and significant oscillations are still unknown, it is of interest to quantify them. Since current array of instruments deployed for polysomnography studies does not include beat-to-beat measurement of blood pressure, but includes oximetry which can supply pulsatile photoplethysmography (PPG) signal, in addition to percent oxygen saturation. Hence, we have investigated a new method for continuous estimation of systolic (SBP), diastolic (DBP), and mean (MBP) blood pressure waveforms from PPG. Peaks and troughs of PPG waveform are used as input to a 5th order autoregressive moving average model to construct estimates of SBP, DBP, and MBP waveforms. Since breath hold maneuvers are shown to faithfully simulate apnea episodes, we evaluated the performance of the proposed method in 7 subjects (4 F; $32 \pm 4$ yrs., BMI $24.57 \pm 3.87$ kg/m2) in supine position doing 5 breath holding maneuvers with 90s of normal breathing between them. The modeling error ranges were (all units are in mmHg $) 0.88 \pm 4.87$ to $- 2.19 \pm 5.73($ SBP); $0.29 \pm 2.39$ to $- 0.97 \pm 3.83($ DBP); and $- 0.42 \pm 2.64$ to $- 1.17 \pm 3.82($ MBP). The cross validation error ranges were $0.28 \pm 6.45$ to $- 1.74 \pm 6.55($ SBP); $0.09 \pm 3.37$ to $0.97 \pm 3.67($ DBP); and $0.33 \pm 4.34$ to $- 0.87 \pm 4.42($ MBP). The overall level of estimation error, as measured by the root mean squared of the model residuals, was less than 7 mmHg.

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