Journal articles: 'Arterial blood pressure estimation'

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Soltan Zadi, Armin, Raichel Alex, Rong Zhang, Donald E. Watenpaugh, and Khosrow Behbehani. "Arterial blood pressure feature estimation using photoplethysmography." Computers in Biology and Medicine 102 (November 2018): 104–11. http://dx.doi.org/10.1016/j.compbiomed.2018.09.013.

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Zakharov, S. M. "Estimation of arterial pressure from pletismography data." Issues of radio electronics, no. 10 (October 31, 2019): 70–76. http://dx.doi.org/10.21778/2218-5453-2019-10-70-76.

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Continuous blood pressure monitoring is important for the prevention and early diagnosis of cardiovascular diseases, the number of which is growing worldwide. A method for measuring blood pressure (BP) based on a plethysmography signal is one of many simple methods for non-invasive monitoring of blood pressure. The article presents a comparative analysis of blood pressure signals and plethysmograms (PG) synchronized in time, as well as their spectral features. A certain temporal structural similarity of the BP and PG signals (correspondence of time intervals, amplitudes) with a simultaneous time shift of the PG signal was revealed. It is shown how adequately one can judge blood pressure, having only the captured PG data. As the time intervals, the minute sequence of cardiac cycles was chosen. It is noted that with appropriate calibration of PG signals, it is possible to estimate the average blood pressure value for several cardiac cycles. The results obtained can be used in the diagnosis of various pathologies.

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Zanderigo, Eleonora, Daniel Leibundgut, Franta Kraus, Rolf Wymann, and Manfred Morari. "REAL-TIME ESTIMATION OF MEAN ARTERIAL BLOOD PRESSURE." IFAC Proceedings Volumes 38, no. 1 (2005): 66–71. http://dx.doi.org/10.3182/20050703-6-cz-1902.02125.

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Ahn, Wonsik, and Young Jin Lim. "Mean arterial blood pressure estimation and its limitation." Canadian Journal of Anesthesia/Journal canadien d'anesthésie 52, no. 9 (November 2005): 1000–1001. http://dx.doi.org/10.1007/bf03022073.

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Baktash, Seddigheh, Mohamad Forouzanfar, Izmail Batkin, Miodrag Bolic, Voicu Z. Groza, Saif Ahmad, and Hilmi R. Dajani. "Characteristic Ratio-Independent Arterial Stiffness-Based Blood Pressure Estimation." IEEE Journal of Biomedical and Health Informatics 21, no. 5 (September 2017): 1263–70. http://dx.doi.org/10.1109/jbhi.2016.2594177.

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Muntinga, J. H., and K. R. Visser. "Estimation of blood pressure-related parameters by electrical impedance measurement." Journal of Applied Physiology 73, no. 5 (November 1, 1992): 1946–57. http://dx.doi.org/10.1152/jappl.1992.73.5.1946.

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In 13 healthy volunteers a computerized experimental set-up was used to measure the electrical impedance of the upper arm at changing cuff pressure, together with the finger arterial blood pressure in the contralateral arm. On the basis of a model for the admittance response, the arterial blood volume per centimeter length (1.4 +/- 0.3 ml/cm), the venous blood volume as a percentage of the total blood compartment (49.2 +/- 12.6%), and the total arterial compliance as a function of mean arterial transmural pressure were estimated. The effective physiological arterial compliance amounted to 2.0 +/- 1.3 microliters.mmHg-1.cm-1 and the maximum compliance to 33.4 +/- 12.0 microliters.mmHg-1.cm-1. Additionally, the extravascular fluid volume expelled by the occluding cuff (0.3 +/- 0.3 ml/cm) was estimated. These quantities are closely related to patient-dependent sources of an unreliable blood pressure measurement and vary with changes in cardiovascular function, such as those found in hypertension. Traditionally, a combination of several methods is needed to estimate them. Such methods, however, usually neglect the contribution of extravascular factors.

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Aguirre, Nicolas, Leandro J. Cymberknop, Edith Grall-Maës, Eugenia Ipar, and Ricardo L. Armentano. "Central Arterial Dynamic Evaluation from Peripheral Blood Pressure Waveforms Using CycleGAN: An In Silico Approach." Sensors 23, no. 3 (February 1, 2023): 1559. http://dx.doi.org/10.3390/s23031559.

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Arterial stiffness is a major condition related to many cardiovascular diseases. Traditional approaches in the assessment of arterial stiffness supported by machine learning techniques are limited to the pulse wave velocity (PWV) estimation based on pressure signals from the peripheral arteries. Nevertheless, arterial stiffness can be assessed based on the pressure–strain relationship by analyzing its hysteresis loop. In this work, the capacity of deep learning models based on generative adversarial networks (GANs) to transfer pressure signals from the peripheral arterial region to pressure and area signals located in the central arterial region is explored. The studied signals are from a public and validated virtual database. Compared to other works in which the assessment of arterial stiffness was performed via PWV, in the present work the pressure–strain hysteresis loop is reconstructed and evaluated in terms of classical machine learning metrics and clinical parameters. Least-square GAN (LSGAN) and Wasserstein GAN with gradient penalty (WGAN-GP) adversarial losses are compared, yielding better results with LSGAN. LSGAN mean ± standard deviation of error for pressure and area pulse waveforms are 0.8 ± 0.4 mmHg and 0.1 ± 0.1 cm2, respectively. Regarding the pressure–strain elastic modulus, it is achieved a mean absolute percentage error of 6.5 ± 5.1%. GAN-based deep learning models can recover the pressure–strain loop of central arteries while observing pressure signals from peripheral arteries.

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CLOUD, Geoffrey C., Chakravarthi RAJKUMAR, Jaspal KOONER, Jonathan COOKE, and Christopher J. BULPITT. "Estimation of central aortic pressure by SphygmoCor® requires intra-arterial peripheral pressures." Clinical Science 105, no. 2 (August 1, 2003): 219–25. http://dx.doi.org/10.1042/cs20030012.

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Central arterial pressure, measured close to the heart, may be of more patho-physiological importance than conventional non-invasive cuff blood pressure. The technique of applanation tonometry using SphygmoCor® has been proposed as a non-invasive method of estimating central pressure. This relies on mathematically derived generalized transfer functions, which have been previously validated using invasive peripheral pressure measurements. We compared simultaneous estimates of central aortic pressure using this technique with those measured directly during the routine diagnostic cardiac catheterization of 30 subjects (age range 27–84 years), half of whom were aged 65 years or more. This was done by applanating the left radial artery and recording the non-invasive brachial cuff blood pressure to generate a central aortic pressure estimate, using the SphygmoCor® radial transfer function. The comparative results were analysed using Bland—Altman plots of mean difference. SphygmoCor®, on average, underestimated systolic central arterial pressure by 13.3 mmHg and overestimated diastolic pressure by 11.5 mmHg. The results were similar in patients aged under and above 65 years. Furthermore, non-invasively measured brachial pressures were seen to give an overall closer estimate of the central arterial pressure than the SphygmoCor® system. The transfer function has been validated from invasively measured arterial pressures and the current use by the system of non-invasive measures may explain the discrepancies. However, age, drugs and arterial disease would also be expected to play a role.

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Gircys, Rolandas, Agnius Liutkevicius, Arunas Vrubliauskas, and Egidijus Kazanavicius. "Blood Pressure Estimation Accoording to Photoplethysmographic Signal Steepness." Information Technology And Control 44, no. 4 (December 18, 2015): 443–50. http://dx.doi.org/10.5755/j01.itc.44.4.12562.

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Abstract. The purpose of this paper is to prove the assumption that there is a correlation between the systolic blood pressure and the photoplethysmographic signal steepness. A method for indirect systolic blood pressure estimation based on photoplethysmographic signal steepness is proposed in this paper. Method: It is proved that based on Hooke’s law, the steepness of pressure and volume (diameter) of pulse waves differ by a constant. The coefficient for calculating arterial blood pressure when volume pulse wave steepness is known is presented in this paper. The Windkessel model is selected for the modeling. Experimental evaluation is based on veloergometrical trials. Volume pulse wave was obtained using a photoplethysmography device that is put on a finger. Blood pressure was measured using a semi-automatic OMRON blood pressure monitor. Results: The simulation of an arterial system using the Windkessel model shows that the steepness of pressure and volume pulse waves correlate. Ten veloergometrical trials were performed during the experimental evaluation. A significant 0.855±0.025 (p < 0.001) correlation between the photoplethysmographic signal steepness and the systolic blood pressure was obtained. The calculated and measured blood pressure values vary no more than ±5mmHg. Conclusions: The results demonstrate that the photoplethysmographic signal wavefront can be successfully applied in wearable devices that can be used for constant 24 hour registration of blood pressure for both home use and clinical practice.DOI: http://dx.doi.org/10.5755/j01.itc.44.4.12562

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Varsos, Georgios V., Angelos G. Kolias, Peter Smielewski, Ken M. Brady, Vassilis G. Varsos, Peter J. Hutchinson, John D. Pickard, and Marek Czosnyka. "A noninvasive estimation of cerebral perfusion pressure using critical closing pressure." Journal of Neurosurgery 123, no. 3 (September 2015): 638–48. http://dx.doi.org/10.3171/2014.10.jns14613.

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OBJECT Cerebral blood flow is associated with cerebral perfusion pressure (CPP), which is clinically monitored through arterial blood pressure (ABP) and invasive measurements of intracranial pressure (ICP). Based on critical closing pressure (CrCP), the authors introduce a novel method for a noninvasive estimator of CPP (eCPP). METHODS Data from 280 head-injured patients with ABP, ICP, and transcranial Doppler ultrasonography measurements were retrospectively examined. CrCP was calculated with a noninvasive version of the cerebrovascular impedance method. The eCPP was refined with a predictive regression model of CrCP-based estimation of ICP from known ICP using data from 232 patients, and validated with data from the remaining 48 patients. RESULTS Cohort analysis showed eCPP to be correlated with measured CPP (R = 0.851, p < 0.001), with a mean ± SD difference of 4.02 ± 6.01 mm Hg, and 83.3% of the cases with an estimation error below 10 mm Hg. eCPP accurately predicted low CPP (< 70 mm Hg) with an area under the curve of 0.913 (95% CI 0.883–0.944). When each recording session of a patient was assessed individually, eCPP could predict CPP with a 95% CI of the SD for estimating CPP between multiple recording sessions of 1.89–5.01 mm Hg. CONCLUSIONS Overall, CrCP-based eCPP was strongly correlated with invasive CPP, with sensitivity and specificity for detection of low CPP that show promise for clinical use.

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Sigal, M. Z., E. V. Kreshetov, and S. S. Ksembaev. "Angiotensometry of the maxillofacial region." Kazan medical journal 69, no. 6 (December 15, 1988): 419–22. http://dx.doi.org/10.17816/kazmj99658.

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We (M.Z. Sigal, S.S. Ksembaev) proposed a method of estimation of blood pressure in vessels of maxillofacial area: arterial pressure - in facial, upper and lower lip arteries, venous - in upper and lower lip veins. The study was carried out with the help of M.Z. Sigal and A.I. Lisin's apparatus.

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Soueidan, Karen, Silu Chen, Hilmi R. Dajani, Miodrag Bolic, and Voicu Groza. "Augmented blood pressure measurement through the noninvasive estimation of physiological arterial pressure variability." Physiological Measurement 33, no. 6 (May 3, 2012): 881–99. http://dx.doi.org/10.1088/0967-3334/33/6/881.

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Schumacher, Gerhard, Jens J. Kaden, and Frederik Trinkmann. "Multiple coupled resonances in the human vascular tree: refining the Westerhof model of the arterial system." Journal of Applied Physiology 124, no. 1 (January 1, 2018): 131–39. http://dx.doi.org/10.1152/japplphysiol.00405.2017.

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The human arterial vascular tree can be described by multicompartment models using electrical components. First introduced in the 1960s by Noordergraaf and Westerhof, these hardware-based approaches required several simplifications. We were able to remove the restrictions using modern software simulation tools and improve overall model quality considerably. Whereas the original Westerhof model consisted of 121 Windkessel elements, the refined model has 711 elements and gives realistic pulse waveforms of the aorta and brachial and radial arteries with realistic blood pressures. Moreover, novel insights concerning the formation of the physiological aortic-to-radial transfer function were gained. Its being potentially due to the coupling of many small resonant elements gives new impetus to the discussion of arterial pressure wave reflection. The individualized transfer function derived from our improved model incorporates distinct patient characteristics and can potentially be used for estimation of central blood pressure values. NEW & NOTEWORTHY We were able to find an individualized transfer function giving realistic pulse waveforms and blood pressures using a multicompartment model of the arterial system. Based on the hardware-built Westerhof approach, several simplifications initially introduced in the 1960s could be reversed using software simulation. Overall model quality was improved considerably, and multiple coupled resonances were identified as potential explanation for the formation of the aortic-to-radial transfer function, giving new impetus to the discussion of arterial pressure wave reflection.

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Raj, J. U., P. Chen, and L. Navazo. "Effect of inflation on microvascular pressures in lungs of young rabbits." American Journal of Physiology-Heart and Circulatory Physiology 252, no. 1 (January 1, 1987): H80—H84. http://dx.doi.org/10.1152/ajpheart.1987.252.1.h80.

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We have examined the effect of positive pressure inflation on the longitudinal distribution of vascular resistance and intravascular pressures in isolated blood-perfused lungs of 3- to 4-wk-old rabbits. Lungs were perfused in zone 3 at airway inflation pressures (P airway) of 6, 14, and 19 cmH2O (pleural pressure, atmospheric) corresponding to 60, 80, and 90% of total lung capacity. We measured microvascular pressures by the micropipette servo-nulling technique in 20- to 50-microns diameter subpleural arterioles and venules. Pulmonary arterial and left atrial pressures were also measured. Lung blood flow was kept constant at 145 +/- 18 ml X kg body wt-1 X min-1. We found that at P airway of 6 cmH2O, approximately 55% of the total pressure drop was in arteries, approximately 23% in microvessels, and approximately 22% in veins. With increasing P airway and lung volume, there was a significant decrease in arterial and venous resistance, but an increase in resistance in microvessels. We conclude that lung inflation significantly alters the distribution of segmental vascular resistance, and therefore lung volume is an important variable that should be considered during estimation of capillary filtration pressure.

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Kahkashan, Nudrath, Mehnaaz Sameera Arifuddin, Mohammed Abdul Hannan Hazari, Safia Sultana, Farah Fatima, and Syyeda Anees. "Variation in carotid-femoral pulse wave velocity, augmentation pressure and augmentation index during different phases of menstrual cycle." Annals of Medical Physiology 2, no. 3 (November 28, 2018): 27–32. http://dx.doi.org/10.23921/amp.2018v2i3.10454.

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Physiological variation of estrogen and progesterone during menstrual cycle is well known. They not only have an effect on blood pressure control, but also seem to have a role in regulating arterial compliance. This study was done to find out whether there are any changes in central arterial parameters during different phases of menstrual cycle. Thirty female subjects in the age group of 18-22 years with normal, regular menstrual cycles participated in this prospective observational study at our teaching hospital. Anthropometric parameters were recorded. Blood pressure in all 4 limbs was recorded using cardiovascular risk analyzer-Periscope™ on Day 3rd to 5th (follicular phase), Day 12th to 14th (ovulation phase), Day 22nd to 24th (luteal phase) of their menstrual cycle. We collected blood samples during these three phases for estimation of estradiol and progesterone by ELISA technique. Analysis of variance and correlation statistics were done using SPSS 17.0 statistical software. No significant statistical changes were observed in systolic blood pressure, diastolic blood pressure, mean arterial pressure, pulse pressure, aortic systolic pressure, aortic diastolic pressure, aortic augmentation pressure, aortic index and pulse wave velocity during the three recorded phases of the menstrual cycle. There are many studies which correlate changes in peripheral artery blood pressure with different phases of menstrual cycle. But there is scarcity in data available which correlates central arterial pressures and arterial stiffness with natural hormonal variations in different phases of menstrual cycle. However, our results show that although there are subtle changes in blood pressure parameters along with estrogen and progesterone levels throughout the menstrual cycle, yet these were not statistically significant.

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Forouzanfar, Mohamad, Saif Ahmad, Izmail Batkin, Hilmi R. Dajani, Voicu Z. Groza, and Miodrag Bolic. "Model-Based Mean Arterial Pressure Estimation Using Simultaneous Electrocardiogram and Oscillometric Blood Pressure Measurements." IEEE Transactions on Instrumentation and Measurement 64, no. 9 (September 2015): 2443–52. http://dx.doi.org/10.1109/tim.2015.2412000.

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Ma, Song, Guan Wang, Liubin Li, and Yuhua Cheng. "A coefficient-free and continuous blood pressure estimation method based on the arterial lumen area model." Biomedical Engineering / Biomedizinische Technik 64, no. 3 (May 27, 2019): 263–73. http://dx.doi.org/10.1515/bmt-2017-0146.

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Abstract Oscillometry is the most popular technique for automatic blood pressure (BP) estimation. This method relies on recording the cuff deflation curve (CDC) from a high suprasystolic BP (SSBP) to a low subdiastolic BP (SDBP) and is very sensitive to noise caused by breathing, motion artifacts, muscle contraction and the environment. We developed a unified BP estimation method involving two integrated sub-procedures based on the arterial lumen area (ALA) model and applied it for continuous BP measurement. Our proposed method is coefficient free and continuous. No empirical coefficients are applied, and the CDC varies within a low-pressure range of 40–80 mm Hg, which can be sustainably imposed on our wrists. The first sub-procedure estimates the mean arterial pressure (MAP) and arterial compliance parameter b under a complete CDC period. In the second sub-procedure, the systolic BP (SBP) and diastolic BP (DBP) are estimated based on the dynamic-updated oscillometric waveform. We applied this method on 300 continuously oscillometric traces recorded from 20 male and female healthy subjects aged 20–60 years. The validated results were compared with those from a double stethoscope check. We observed mean absolute errors of 4.77 and 4.24 mm Hg in estimating the SBP and DBP, respectively.

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Bogachev, M. I., O. V. Mamontov, A. O. Conrady, and Y. D. Ulyanitskiy. "The calculation of spontaneous arterial barorexlex sensitivity via joint analysis of arterial blood pressure and heart ratebeat-to-beat fluctuation." "Arterial’naya Gipertenziya" ("Arterial Hypertension") 13, no. 1 (February 28, 2007): 69–75. http://dx.doi.org/10.18705/1607-419x-2007-13-1-69-75.

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Autonomic dysfunction is associated with negative prognosis in cardiovascular patiens and several other pathologies. Arterial baroreflex sensitivity is an important marker of autonomic regulation. Present work is devoted to the new approach to spontaneous baroreflex estimation, which permit to improve quality of the continious blood pressure and ECG monitoring analysis. The method of combined estimation of probability density of blood pressure and R-R intervals is proposed in this article, which improves efficacy of use of date records due to the increased number of included beats in calculation. This method is appeared to have better reproducibility and, probably, sensitivity for autonomic dysfunction diagnosis compared to traditional approaches. Moreover, offered method allow to measure additional arterial barorexlex characteristics. Thus, the calculation of barorexlex sensitivity combined probability density allows to wide the sphere of spontaneous baroreflex estimation, including changeable conditions.

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Vennin, Samuel, Alexia Mayer, Ye Li, Henry Fok, Brian Clapp, Jordi Alastruey, and Phil Chowienczyk. "Noninvasive calculation of the aortic blood pressure waveform from the flow velocity waveform: a proof of concept." American Journal of Physiology-Heart and Circulatory Physiology 309, no. 5 (September 2015): H969—H976. http://dx.doi.org/10.1152/ajpheart.00152.2015.

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Estimation of aortic and left ventricular (LV) pressure usually requires measurements that are difficult to acquire during the imaging required to obtain concurrent LV dimensions essential for determination of LV mechanical properties. We describe a novel method for deriving aortic pressure from the aortic flow velocity. The target pressure waveform is divided into an early systolic upstroke, determined by the water hammer equation, and a diastolic decay equal to that in the peripheral arterial tree, interposed by a late systolic portion described by a second-order polynomial constrained by conditions of continuity and conservation of mean arterial pressure. Pulse wave velocity (PWV, which can be obtained through imaging), mean arterial pressure, diastolic pressure, and diastolic decay are required inputs for the algorithm. The algorithm was tested using 1) pressure data derived theoretically from prespecified flow waveforms and properties of the arterial tree using a single-tube 1-D model of the arterial tree, and 2) experimental data acquired from a pressure/Doppler flow velocity transducer placed in the ascending aorta in 18 patients (mean ± SD: age 63 ± 11 yr, aortic BP 136 ± 23/73 ± 13 mmHg) at the time of cardiac catheterization. For experimental data, PWV was calculated from measured pressures/flows, and mean and diastolic pressures and diastolic decay were taken from measured pressure (i.e., were assumed to be known). Pressure reconstructed from measured flow agreed well with theoretical pressure: mean ± SD root mean square (RMS) error 0.7 ± 0.1 mmHg. Similarly, for experimental data, pressure reconstructed from measured flow agreed well with measured pressure (mean RMS error 2.4 ± 1.0 mmHg). First systolic shoulder and systolic peak pressures were also accurately rendered (mean ± SD difference 1.4 ± 2.0 mmHg for peak systolic pressure). This is the first noninvasive derivation of aortic pressure based on fluid dynamics (flow and wave speed) in the aorta itself.

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Chakraborty, Nitisha, Sankar Roy, Debajyoti Sur, Arunava Biswas, Dipasri Bhattacharya, and Anjan Adhikari. "Comparison between esmolol and verapamil in attenuation of cardiovascular stress response to laryngoscopy and endotracheal intubation in elective surgery." Asian Journal of Medical Sciences 12, no. 7 (July 1, 2021): 64–68. http://dx.doi.org/10.3126/ajms.v12i7.35759.

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Background: Cardiovascular stress due to reflex sympathetic over activity is a great concern during laryngoscopy and endotracheal intubation. Aims and Objectives: To compare the efficacy and safety of esmolol and verapamil for attenuation of hemodynamic effects (heart rate, systolic blood pressure, diastolic blood pressure and mean arterial pressure) due to laryngoscopy and endotracheal intubation in elective surgical cases. Materials and Methods: A prospective, randomized, double blinded, controlled study was conducted on 60 patients divided equally into 30 each receiving esmolol (2 mg/kg body weight) and verapamil (0.1 mg/kg body weight) respectively. Heart rate, systolic and diastolic blood pressure and mean arterial pressure were recordedat pre-operative stage, after administration of the study drugs, immediately after intubation and at 1 ,3 ,5 minutes after intubation. Data collected were statistically analyzed. Results: The mean systolic blood pressure was lower in the esmolol group at all times of estimation compared with the verapamil group and the difference was at the time of intubation (p value <0.001).The mean diastolic blood pressure was lower in the esmolol group at all times of estimation compared to the verapamil group which was not statistically significant at any time of estimation. The mean arterial pressure was significantly lower at the time of immediately after intubation (p<0.001) in esmolol as compared to verapamil group. Adverse effects in both the study groups were insignificant. Conclusion: Esmololand Verapamil can effectively attenuate the cardiovascular stress to laryngoscopy and endotracheal intubation with the former appears to be a better alternative from efficacy and safety perspectives.

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Nagasawa, Takumi, Kaito Iuchi, Ryo Takahashi, Mari Tsunomura, Raquel Pantojo de Souza, Keiko Ogawa-Ochiai, Norimichi Tsumura, and George C. Cardoso. "Blood Pressure Estimation by Photoplethysmogram Decomposition into Hyperbolic Secant Waves." Applied Sciences 12, no. 4 (February 9, 2022): 1798. http://dx.doi.org/10.3390/app12041798.

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Photoplethysmographic (PPG) pulses contain information about cardiovascular parameters. In particular, blood pressure can be estimated using PPG pulse decomposition analysis, which assumes that a PPG pulse is composed of the original heart ejection blood wave and its reflections in arterial branchings. Among pulse decomposition wave functions that have been studied in the literature, Gaussian waves are the most successful ones. However, a more adequate pulse decomposition function could be found to improve blood pressure estimates. In this paper, we propose pulse decomposition analysis using hyperbolic secant (sech) waves and compare results with corresponding Gaussian wave decomposition. We analyze how the parameters of each of the two types of decomposition waves correlate with blood pressure. For this analysis, continuous blood pressure data and PPG data were acquired from ten healthy volunteers. The blood pressure of volunteers was varied by asking them to hold their breath for up to 60 s. The results suggested sech wave decomposition had higher accuracy in estimating blood pressure than the Gaussian function. Thus, sech wave decomposition should be considered as a more robust alternative to Gaussian wave pulse decomposition for blood pressure estimation models.

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Ursino, Mauro, and Cristina Cristalli. "Mathematical Modeling of Noninvasive Blood Pressure Estimation Techniques—Part II: Brachial Hemodynamics." Journal of Biomechanical Engineering 117, no. 1 (February 1, 1995): 117–26. http://dx.doi.org/10.1115/1.2792259.

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The main biomechanical factors which may affect the accuracy of the oscillometric method for indirect blood pressure measurement are analyzed using a new model of brachial hemodynamics. In a first stage of this work, the model has been used to reproduce some well-known responses of collapsing arteries, such as the sharp increase in compliance, and the nonlinear pressure-flow characteristic with negative dynamic resistance. In a second stage the model has been linked to the arm tissue mechanics description presented in a previous work. The final model so obtained has then been employed to analyze the pattern of the main hemodynamic quantities (pressure pulsations in the cuffs, blood volume changes, blood flow upstream and downstream of the cuffs) during deflation manoeuvres. The simulation results agree with those found in the recent literature quite well. Results indicate that the cuff pressure value for maximum pulsations exhibits a large plateau, located approximately around the mean arterial pressure. However, stiffness of wall artery, or stretching of the cuff internal surface, may significantly alter the obtained results causing a phenomena of “pseudohypertension.”

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Casadei, Benedetta C., Alessandro Gumiero, Giorgio Tantillo, Luigi Della Torre, and Gabriella Olmo. "Systolic Blood Pressure Estimation from PPG Signal Using ANN." Electronics 11, no. 18 (September 14, 2022): 2909. http://dx.doi.org/10.3390/electronics11182909.

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High blood pressure is one of the most important precursors for Cardiovascular Diseases (CVDs), the most common cause of death in 2020, as reported by the World Health Organization (WHO). Moreover, many patients affected by neurodegenerative diseases (e.g., Parkinson’s Disease) exhibit impaired autonomic control, with inversion of the normal circadian arterial pressure cycle, and consequent augmented cardiovascular and fall risk. For all these reasons, a continuous pressure monitoring of these patients could represent a significant prognostic factor, and help adjusting their therapy. However, the existing cuff-based methods cannot provide continuous blood pressure readings. Our work is inspired by the newest approaches based on the photoplethysmographic (PPG) signal only, which has been used to continuously estimate systolic blood pressure (SP), using artificial neural networks (ANN), in order to create more compact and wearable devices. Our first database was derived from the PhysioNet resource; we extracted PPG and arterial blood pressure (ABP) signals, collected at a sampling frequency of 125 Hz, in a hospital environment. It consists of 249,672 PPG periods and the relative SP values. The second database was collected at STMicroelectronics s.r.l., in Agrate Brianza, using the MORFEA3 wearable device and a digital cuff-based sphygmomanometer, as reference. The pre-processing phase, in order to remove noise and motion artifacts and to segment the signal into periods, was carried out on Matlab R2019b. The noise removal was one of the challenging parts of the study because of the inaccuracy of the PPG signal during everyday-life activity, and this is the reason why the MORFEA3 dataset was acquired in a controlled environment in a static position. Different solutions were implemented to choose the input features that best represent the period morphology. The first database was used to train the multilayer feed-forward neural network with a back-propagation model, whereas the second one was used to test it. The results obtained in this project are promising and match the Association for the Advancement of Medical Instruments (AAMI) and the British Hypertension Society (BHS) standards. They show a Mean Absolute Error of 3.85 mmHg with a Standard Deviation of 4.29 mmHg, under the AAMI standard, and reach the grade A under the BHS standard.

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Li, Yibin, Shengnan Li, Houbing Song, Bin Shao, Xiao Yang, and Ning Deng. "Noninvasive blood pressure estimation with peak delay of different pulse waves." International Journal of Distributed Sensor Networks 15, no. 3 (March 2019): 155014771983787. http://dx.doi.org/10.1177/1550147719837877.

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In this article, we discuss the validity of noninvasive continuous blood pressure estimation with two different types of peripheral pulse waves. Artery-blocking experiment shows that phase difference of two pulse waves at the same location is well related with blood pressure and blood flow fluctuation. Exercise-recovery experiment resulting from 16 subjects shows that phase difference varies with blood pressure with the correlation from 0.63 to 0.88 when blood pressure changes rapidly. Simulations based on a classic hemodynamic model verify the relationship between phase difference and blood pressure. However, phase difference is strongly correlated with smooth muscle state of the arterial wall as well. If smooth muscle information can be obtained by further study, phase difference can act as a promising approach to portable and wearable device for real-time blood pressure monitoring.

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Nabeel, P. M., Joseph Jayaraj, Karthik Srinivasa, Sivaprakasam Mohanasankar, and M. Chenniappan. "Bi-Modal Arterial Compliance Probe for Calibration-Free Cuffless Blood Pressure Estimation." IEEE Transactions on Biomedical Engineering 65, no. 11 (November 2018): 2392–404. http://dx.doi.org/10.1109/tbme.2018.2866332.

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T. Butt, A., Y. A. Abakr, and K. B. Mustapha. "Blood Flow Modeling to Improve Cardiovascular Diagnostics: Application of A GTF to Predict Central Aortic Pressure using a 1-D Model." International Journal of Engineering & Technology 7, no. 4.26 (November 30, 2018): 146. http://dx.doi.org/10.14419/ijet.v7i4.26.22156.

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This study aims to demonstrate that a comprehensive one-dimensional model of the arterial network can be used in conjunction with the generalized transfer function (GTF) technique to estimate central aortic pressure using pressure waveforms obtained from peripheral sites. The peripheral and central pressure waveforms for a healthy subject are used to estimate transfer functions, which are then used to reconstruct central aortic pressure waveforms for a second model that simulates arterial stiffening. The similarities between the simulated aortic waveform and the waveforms estimated using the transfer function are and from the brachial, carotid and iliac arteries, respectively. The root-mean-square errors (RMSE) for the reconstructed waveforms from the brachial, carotid and iliac arteries are and mmHg, respectively. The results from this study illustrate that the proposed method provides a feasible alternative to higher dimensional models as well as experimental studies and can greatly enhance the accuracy of central aortic pressure estimation.

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Acharya, Deepshikha, Ankita Mukherjea, Jiaming Cao, Alexander Ruesch, Samantha Schmitt, Jason Yang, Matthew A. Smith, and Jana M. Kainerstorfer. "Non-Invasive Spectroscopy for Measuring Cerebral Tissue Oxygenation and Metabolism as a Function of Cerebral Perfusion Pressure." Metabolites 12, no. 7 (July 20, 2022): 667. http://dx.doi.org/10.3390/metabo12070667.

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Near-infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS) measure cerebral hemodynamics, which in turn can be used to assess the cerebral metabolic rate of oxygen (CMRO2) and cerebral autoregulation (CA). However, current mathematical models for CMRO2 estimation make assumptions that break down for cerebral perfusion pressure (CPP)-induced changes in CA. Here, we performed preclinical experiments with controlled changes in CPP while simultaneously measuring NIRS and DCS at rest. We observed changes in arterial oxygen saturation (~10%) and arterial blood volume (~50%) with CPP, two variables often assumed to be constant in CMRO2 estimations. Hence, we propose a general mathematical model that accounts for these variations when estimating CMRO2 and validate its use for CA monitoring on our experimental data. We observed significant changes in the various oxygenation parameters, including the coupling ratio (CMRO2/blood flow) between regions of autoregulation and dysregulation. Our work provides an appropriate model and preliminary experimental evidence for the use of NIRS- and DCS-based tissue oxygenation and metabolism metrics for non-invasive diagnosis of CA health in CPP-altering neuropathologies.

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Talts, J. "Estimation of the finger arterial pressure–volume relationship and blood pressure waveform from photoplethysmographic signals." Proceedings of the Estonian Academy of Sciences. Engineering 10, no. 2 (2004): 137. http://dx.doi.org/10.3176/eng.2004.2.07.

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Panerai, R. B., E. L. Sammons, S. M. Smith, W. E. Rathbone, S. Bentley, J. F. Potter, D. H. Evans, and N. J. Samani. "Cerebral critical closing pressure estimation from Finapres and arterial blood pressure measurements in the aorta." Physiological Measurement 27, no. 12 (November 10, 2006): 1387–402. http://dx.doi.org/10.1088/0967-3334/27/12/010.

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Kashif, F. M., G. C. Verghese, V. Novak, M. Czosnyka, and T. Heldt. "Model-Based Noninvasive Estimation of Intracranial Pressure from Cerebral Blood Flow Velocity and Arterial Pressure." Science Translational Medicine 4, no. 129 (April 11, 2012): 129ra44. http://dx.doi.org/10.1126/scitranslmed.3003249.

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Arai, Tatsuya, Kichang Lee, Robert P. Marini, and Richard J. Cohen. "Estimation of changes in instantaneous aortic blood flow by the analysis of arterial blood pressure." Journal of Applied Physiology 112, no. 11 (June 1, 2012): 1832–38. http://dx.doi.org/10.1152/japplphysiol.01565.2011.

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The purpose of this study was to introduce and validate a new algorithm to estimate instantaneous aortic blood flow (ABF) by mathematical analysis of arterial blood pressure (ABP) waveforms. The algorithm is based on an autoregressive with exogenous input (ARX) model. We applied this algorithm to diastolic ABP waveforms to estimate the autoregressive model coefficients by requiring the estimated diastolic flow to be zero. The algorithm incorporating the coefficients was then applied to the entire ABP signal to estimate ABF. The algorithm was applied to six Yorkshire swine data sets over a wide range of physiological conditions for validation. Quantitative measures of waveform shape (standard deviation, skewness, and kurtosis), as well as stroke volume and cardiac output from the estimated ABF, were computed. Values of these measures were compared with those obtained from ABF waveforms recorded using a Transonic aortic flow probe placed around the aortic root. The estimation errors were compared with those obtained using a windkessel model. The ARX model algorithm achieved significantly lower errors in the waveform measures, stroke volume, and cardiac output than those obtained using the windkessel model ( P < 0.05).

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Karlsson, Jonas, Joacim Linde, Christer Svensen, and Mikael Gellerfors. "Prehospital Invasive Arterial Pressure: Use of a Minimized Flush System." Prehospital and Disaster Medicine 33, no. 5 (August 31, 2018): 490–94. http://dx.doi.org/10.1017/s1049023x18000729.

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AbstractIntroductionInvasive blood pressure (IBP) monitoring could be of benefit for certain prehospital patient groups such as trauma and cardiac arrest patients. However, there are disadvantages with using conventional IBP devices. These include time to prepare the transducer kit and flush system as well as the addition of long tubing connected to the patient. It has been suggested to simplify the IBP equipment by replacing the continuous flush system with a syringe and a short stopcock.HypothesisIn this study, blood pressures measured by a standard IBP (sIBP) transducer kit with continuous flush was compared to a transducer kit connected to a simplified and minimized flush system IBP (mIBP) using only a syringe.MethodsA mechanical, experimental model was used to create arterial pressure pulsations. Measurements were made simultaneously using a sIBP and mIBP device, respectively. This was repeated four times using different mean arterial pressure (MAP): 40, 70, 110, and 140mm Hg. For each series, 16 measurements were taken during 20 minutes. Data were analyzed using Bland-Altman plots. Measurement error greater than five percent was regarded as clinically significant.ResultsMean bias and standard deviation (SD) for systolic blood pressure (SBP), diastolic blood pressure (DBP), and MAP was -3.05 (SD = 2.07), 0.2 (SD = 0.48), and -0.3 (SD = 0.55) mmHg, respectively. Bland-Altman plots revealed that the bias and SD for systolic pressures was mainly due to an increased under-estimation of pressures in lower ranges. All MAP and 98.4% of diastolic pressure measurements had an error of less than five percent. Systolic pressures in the MAP 40 series all had an error of greater than five percent. All other systolic pressures had an error of less than five percent.ConclusionThus, IBP with the mIBP flush system provides accurate measurement of MAP and DBP in a wide range of physiological pressures. For SBP, there was a tendency to under-estimate pressures, with larger error in lower pressures. Implementation of a simplified flush system could allow further development and potentially simplify the use of IBP for prehospital critical care teams.KarlssonJ,LindeJ,SvensenC,GellerforsM.Prehospital invasive arterial pressure: use of a minimized flush system.Prehosp Disaster Med.2018;33(5):490–494.

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Fan, Xiaomao, Hailiang Wang, Yang Zhao, Ye Li, and Kwok Leung Tsui. "An Adaptive Weight Learning-Based Multitask Deep Network for Continuous Blood Pressure Estimation Using Electrocardiogram Signals." Sensors 21, no. 5 (February 25, 2021): 1595. http://dx.doi.org/10.3390/s21051595.

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Estimating blood pressure via combination analysis with electrocardiogram and photoplethysmography signals has attracted growing interest in continuous monitoring patients’ health conditions. However, most wearable/portal monitoring devices generally acquire only one kind of physiological signals due to the consideration of energy cost, device weight and size, etc. In this study, a novel adaptive weight learning-based multitask deep learning framework based on single lead electrocardiogram signals is proposed for continuous blood pressure estimation. Specifically, the proposed method utilizes a 2-layer bidirectional long short-term memory network as the sharing layer, followed by three identical architectures of 2-layer fully connected networks for task-specific blood pressure estimation. To learn the importance of task-specific losses automatically, an adaptive weight learning scheme based on the trend of validation loss is proposed. Extensive experiment results on Physionet Multiparameter Intelligent Monitoring in Intensive Care (MIMIC) II waveform database demonstrate that the proposed method using electrocardiogram signals obtains estimating performance of 0.12±10.83 mmHg, 0.13±5.90 mmHg, and 0.08±6.47 mmHg for systolic blood pressure, diastolic blood pressure, and mean arterial pressure, respectively. It can meet the requirements of the British Hypertension Society standard and US Association of Advancement of Medical Instrumentation standard with a considerable margin. Combined with a wearable/portal electrocardiogram device, the proposed model can be deployed to a healthcare system to provide a long-term continuous blood pressure monitoring service, which would help to reduce the incidence of malignant complications to hypertension.

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Kim, Seon-Chil, and Sung-Hyoun Cho. "Blood Pressure Estimation Algorithm Based on Photoplethysmography Pulse Analyses." Applied Sciences 10, no. 12 (June 12, 2020): 4068. http://dx.doi.org/10.3390/app10124068.

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Though small wrist-type blood pressure (BP) measurement devices using simple sensors have recently been developed, they lack accuracy and require the input of personal user data. To miniaturize BP measurement devices, this study proposes the use of algorithms that can calculate BP using sensors that utilize only two photoplethysmographies (PPGs), without the need for electrocardiograms. To reduce the error of indirect BP measurement, specific values representing individual blood vessel conditions are improved via the application of an algorithm developed using mean arterial pressure and PPG phase difference. To reduce the error that occurs when measuring BP using PPG, a specific value algorithm used to develop a miniaturized BP measuring device using two PPGs is proposed along with a new model. The developed ultra-small PPG measuring device uses a reflective photoplethysmography measurement circuit. This is presented as a PPG-only model that deviates from the method of additionally linking existing electrocardiography (ECG). The measurement device developed in this study is compared with the air-pressurized automatic BP measurement device in terms of the BP measurement value; the result of maintaining the error stably at 5% is derived to prove the superiority of the algorithm.

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Haque, Chowdhury Azimul, Tae-Ho Kwon, and Ki-Doo Kim. "Cuffless Blood Pressure Estimation Based on Monte Carlo Simulation Using Photoplethysmography Signals." Sensors 22, no. 3 (February 4, 2022): 1175. http://dx.doi.org/10.3390/s22031175.

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Blood pressure measurements are one of the most routinely performed medical tests globally. Blood pressure is an important metric since it provides information that can be used to diagnose several vascular diseases. Conventional blood pressure measurement systems use cuff-based devices to measure the blood pressure, which may be uncomfortable and sometimes burdensome to the subjects. Therefore, in this study, we propose a cuffless blood pressure estimation model based on Monte Carlo simulation (MCS). We propose a heterogeneous finger model for the MCS at wavelengths of 905 nm and 940 nm. After recording the photon intensities from the MCS over a certain range of blood pressure values, the actual photoplethysmography (PPG) signals were used to estimate blood pressure. We used both publicly available and self-made datasets to evaluate the performance of the proposed model. In case of the publicly available dataset for transmission-type MCS, the mean absolute errors are 3.32 ± 6.03 mmHg for systolic blood pressure (SBP), 2.02 ± 2.64 mmHg for diastolic blood pressure (DBP), and 1.76 ± 2.8 mmHg for mean arterial pressure (MAP). The self-made dataset is used for both transmission- and reflection-type MCSs; its mean absolute errors are 2.54 ± 4.24 mmHg for SBP, 1.49 ± 2.82 mmHg for DBP, and 1.51 ± 2.41 mmHg for MAP in the transmission-type case as well as 3.35 ± 5.06 mmHg for SBP, 2.07 ± 2.83 mmHg for DBP, and 2.12 ± 2.83 mmHg for MAP in the reflection-type case. The estimated results of the SBP and DBP satisfy the requirements of the Association for the Advancement of Medical Instrumentation (AAMI) standards and are within Grade A according to the British Hypertension Society (BHS) standards. These results show that the proposed model is efficient for estimating blood pressures using fingertip PPG signals.

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Kos, Martina, Tihana Nađ, Lorena Stanojević, Matea Lukić, Ana Stupin, Ines Drenjančević, Silvija Pušeljić, et al. "Estimation of Salt Intake in Normotensive and Hypertensive Children: The Role of Body Weight." Nutrients 15, no. 3 (February 1, 2023): 736. http://dx.doi.org/10.3390/nu15030736.

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Objective: The connection between increased dietary salt intake and arterial hypertension has been recognized for a long time, even in children. This study aimed to investigate salt consumption in normotensive and hypertensive children and evaluate their dietary habits. Materials and Methods: A total of fifty participants were included in this cross-sectional study: twenty-five normotensive children and 25 children of both sexes with essential arterial hypertension from 12–17 years old. Subjects’ body mass index, waist-to-hip ratio, body composition and arterial blood pressure were measured, and their daily salt intake was calculated from 24-h urine samples. Using the food frequency questionnaire (FFQ), the data on the average daily total energy and food intakes were collected and analyzed using a suitable program. Results: Estimated daily salt intake was significantly higher in hypertensive compared to normotensive children, and this is positively associated with blood pressure and body mass index (BMI). Hypertensive children had significantly higher BMIs, which also positively correlated with blood pressure. Consistently, resting metabolic rate (kcal) is higher in hypertensive children compared to normotensive, and this is also associated with blood pressure. Reported energy intake is also enlarged in hypertensive compared to normotensive children and for both groups, levels are significantly higher than the recommended values. Conclusions: Our study results confirm the relationship between daily salt consumption, blood pressure and body weight. Sodium consumption related to blood pressure and body weight among children. Cardiovascular disease prevention should start in early childhood by reducing salt intake and preventing overweight/obesity since these are two of the most important modifiable risk factors for hypertension.

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Brophy, Eoin, Maarten De Vos, Geraldine Boylan, and Tomás Ward. "Estimation of Continuous Blood Pressure from PPG via a Federated Learning Approach." Sensors 21, no. 18 (September 21, 2021): 6311. http://dx.doi.org/10.3390/s21186311.

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Ischemic heart disease is the highest cause of mortality globally each year. This puts a massive strain not only on the lives of those affected, but also on the public healthcare systems. To understand the dynamics of the healthy and unhealthy heart, doctors commonly use an electrocardiogram (ECG) and blood pressure (BP) readings. These methods are often quite invasive, particularly when continuous arterial blood pressure (ABP) readings are taken, and not to mention very costly. Using machine learning methods, we develop a framework capable of inferring ABP from a single optical photoplethysmogram (PPG) sensor alone. We train our framework across distributed models and data sources to mimic a large-scale distributed collaborative learning experiment that could be implemented across low-cost wearables. Our time-series-to-time-series generative adversarial network (T2TGAN) is capable of high-quality continuous ABP generation from a PPG signal with a mean error of 2.95 mmHg and a standard deviation of 19.33 mmHg when estimating mean arterial pressure on a previously unseen, noisy, independent dataset. To our knowledge, this framework is the first example of a GAN capable of continuous ABP generation from an input PPG signal that also uses a federated learning methodology.

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Harfiya, Latifa Nabila, Ching-Chun Chang, and Yung-Hui Li. "Continuous Blood Pressure Estimation Using Exclusively Photopletysmography by LSTM-Based Signal-to-Signal Translation." Sensors 21, no. 9 (April 23, 2021): 2952. http://dx.doi.org/10.3390/s21092952.

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Monitoring continuous BP signal is an important issue, because blood pressure (BP) varies over days, minutes, or even seconds for short-term cases. Most of photoplethysmography (PPG)-based BP estimation methods are susceptible to noise and only provides systolic blood pressure (SBP) and diastolic blood pressure (DBP) prediction. Here, instead of estimating a discrete value, we focus on different perspectives to estimate the whole waveform of BP. We propose a novel deep learning model to learn how to perform signal-to-signal translation from PPG to arterial blood pressure (ABP). Furthermore, using a raw PPG signal only as the input, the output of the proposed model is a continuous ABP signal. Based on the translated ABP signal, we extract the SBP and DBP values accordingly to ease the comparative evaluation. Our prediction results achieve average absolute error under 5 mmHg, with 70% confidence for SBP and 95% confidence for DBP without complex feature engineering. These results fulfill the standard from Association for the Advancement of Medical Instrumentation (AAMI) and the British Hypertension Society (BHS) with grade A. From the results, we believe that our model is applicable and potentially boosts the accuracy of an effective signal-to-signal continuous blood pressure estimation.

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Chen, Yang, Chengcheng Hong, Michael R. Pinsky, Ting Ma, and Gilles Clermont. "Estimating Surgical Blood Loss Volume Using Continuously Monitored Vital Signs." Sensors 20, no. 22 (November 17, 2020): 6558. http://dx.doi.org/10.3390/s20226558.

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Background: There are currently no effective and accurate blood loss volume (BLV) estimation methods that can be implemented in operating rooms. To improve the accuracy and reliability of BLV estimation and facilitate clinical implementation, we propose a novel estimation method using continuously monitored photoplethysmography (PPG) and invasive arterial blood pressure (ABP). Methods: Forty anesthetized York Pigs (31.82 ± 3.52 kg) underwent a controlled hemorrhage at 20 mL/min until shock development was included. Machine-learning-based BLV estimation models were proposed and tested on normalized features derived by vital signs. Results: The results showed that the mean ± standard deviation (SD) for estimating BLV against the reference BLV of our proposed random-forest-derived BLV estimation models using PPG and ABP features, as well as the combination of ABP and PPG features, were 11.9 ± 156.2, 6.5 ± 161.5, and 7.0 ± 139.4 mL, respectively. Compared with traditional hematocrit computation formulas (estimation error: 102.1 ± 313.5 mL), our proposed models outperformed by nearly 200 mL in SD. Conclusion: This is the first attempt at predicting quantitative BLV from noninvasive measurements. Normalized PPG features are superior to ABP in accurately estimating early-stage BLV, and normalized invasive ABP features could enhance model performance in the event of a massive BLV.

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Pinsino, A., F. Castagna, E. J. Stöhr, B. J. McDonnell, J. R. Cockcroft, M. Tiburcio, L. Effner, et al. "Estimation of Mean Arterial Pressure in HeartMate II Patients Using Doppler Blood Pressure and Pump Speed." Journal of Heart and Lung Transplantation 37, no. 4 (April 2018): S30. http://dx.doi.org/10.1016/j.healun.2018.01.053.

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Kim, Boyeon, and Yunseok Chang. "Digital Blood Pressure Estimation with the Differential Value of the Arterial Pulse Waveform." KIPS Transactions on Computer and Communication Systems 5, no. 6 (June 30, 2016): 135–42. http://dx.doi.org/10.3745/ktccs.2016.5.6.135.

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de Nadal, M., A. Camps, A. Ruiz-San Martin, A. Garcia-Roche, J. Riera, and J. C. Ruiz-Rodriguez. "Continuous and non-invasive estimation of mean arterial blood pressure using photoplethysmograph waveform." European Journal of Anaesthesiology 29 (June 2012): 45. http://dx.doi.org/10.1097/00003643-201206001-00144.

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Pielmuş, Alexandru-Gabriel, Dennis Osterland, Michael Klum, Timo Tigges, Aarne Feldheiser, Oliver Hunsicker, and Reinhold Orglmeister. "Correlation of arterial blood pressure to synchronous piezo, impedance and photoplethysmographic signal features." Current Directions in Biomedical Engineering 3, no. 2 (September 7, 2017): 749–53. http://dx.doi.org/10.1515/cdbme-2017-0158.

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AbstractIn this paper we investigate which pulse wave pick-up technologies are well suited for blood pressure trend estimation. We use custom built hardware to acquire electrocardiographic, applanation-tonometric, photo- and impedance-plethysmographic signals during low intensity workouts. Beat-to-beat features and pulse wave runtimes are correlated to the reference arterial blood pressure. Temporal lag adjustment is performed to determine the latency of feature response. Best results are obtained for systolic arterial blood pressure. These suggest that every subject has a range of well-performing features, but it is not consistent among all. Spearman Rho values reach in excess of 0.8, with their significance being validated by p-values lower than 0.01.

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LI, XIRU, XIAOFENG LI, JINLIN XU, HAIBO TAN, and MUNAN YUAN. "A NOVEL CONTINUOUS AND NONINVASIVE MEASUREMENT FOR BLOOD PRESSURE BASED ON PHOTOPLETHYSMOGRAPHY." Journal of Mechanics in Medicine and Biology 17, no. 03 (July 27, 2016): 1750044. http://dx.doi.org/10.1142/s0219519417500440.

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Implementation of continuous noninvasive blood pressure (NIBP) measurement is important for prevention and control of the cardiovascular disease. This paper study a novel continuous noninvasive blood pressure (BP) fitting method based on the photoplethysmography (PPG), electrocardiogram (ECG) and blood volume characteristics. The estimation model of systolic blood pressure (SBP) was established from ECG and PPG in Multiparameter Intelligent Monitoring in Intensive Care (MIMIC) II openness medical database. According to analysis of Beer–Lambert law applied in arterial blood characteristics and PPG waveform, the estimation model of differential pressure (DP) was constructed. Taking the SBP and diastolic blood pressure (DBP) from MIMIC II database as the gold standard value, the validation results show that the mean difference and standard deviation of the fitting results are within the standard range of ([Formula: see text])[Formula: see text]mm/Hg. The method proposed in this paper can effectively achieve continuous BP measurement.

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Guo, Cheng-Yan, Hao-Ching Chang, Kuan-Jen Wang, and Tung-Li Hsieh. "An Arterial Compliance Sensor for Cuffless Blood Pressure Estimation Based on Piezoelectric and Optical Signals." Micromachines 13, no. 8 (August 16, 2022): 1327. http://dx.doi.org/10.3390/mi13081327.

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Objective: Blood pressure (BP) data can influence therapeutic decisions for some patients, while non-invasive devices that continuously monitor BP can provide patients with a more comprehensive BP assessment. Therefore, this study proposes a multi-sensor-based small cuffless BP monitoring device that integrates a piezoelectric sensor array and an optical sensor, which can monitor the patient’s physiological signals from the radial artery. Method: Based on the Moens–Korteweg (MK) equation of the hemodynamic model, pulse wave velocity (PWV) can be correlated with arterial compliance and BP can be estimated. Therefore, the novel method proposed in this study involves using a piezoelectric sensor array to measure the PWV and an optical sensor to measure the photoplethysmography (PPG) intensity ratio (PIR) signal to estimate the participant’s arterial parameters. The parameters measured by multiple sensors were combined to estimate BP based on the P–β model derived from the MK equation. Result: We recruited 20 participants for the BP monitoring experiment to compare the performance of the BP estimation method with the regression model and the P–β model method with arterial compliance. We then compared the estimated BP with a reference device for validation. The results are presented as the error mean ± standard deviation (SD). Based on the regression model method, systolic blood pressure (SBP) was 0.32 ± 5.94, diastolic blood pressure (DBP) was 2.17 ± 6.22, and mean arterial pressure (MAP) was 1.55 ± 5.83. The results of the P–β model method were as follows: SBP was 0.75 ± 3.9, DBP was 1.1 ± 3.12, and MAP was 0.49 ± 2.82. Conclusion: According to the results of our proposed small cuffless BP monitoring device, both methods of estimating BP conform to ANSI/AAMI/ISO 81060-2:20181_5.2.4.1.2 criterion 1 and 2, and using arterial parameters to calibrate the MK equation model can improve BP estimate accuracy. In the future, our proposed device can provide patients with a convenient and comfortable BP monitoring solution. Since the device is small, it can be used in a public place without attracting other people’s attention, thereby effectively improving the patient’s right to privacy, and increasing their willingness to use it.

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Lee, Soojeong, Gwanggil Jeon, and Seokhoon Kang. "Two-Step Pseudomaximum Amplitude-Based Confidence Interval Estimation for Oscillometric Blood Pressure Measurements." BioMed Research International 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/920206.

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Blood pressure (BP) is an important vital sign to determine the health of an individual. Although the estimation of average arterial blood pressure using oscillometric methods is possible, there are no established methods for obtaining confidence intervals (CIs) for systolic blood pressure (SBP) and diastolic blood pressure (DBP). In this paper, we propose a two-step pseudomaximum amplitude (TSPMA) as a novel approach to obtain improved CIs of SBP and DBP using a double bootstrap approach. The weighted median (WM) filter is employed to reduce impulsive and Gaussian noises in the step of preprocessing. Application of the proposed method provides tighter CIs and smaller standard deviation of CIs than the pseudomaximum amplitude-envelope and maximum amplitude algorithms with Student’st-method.

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Butlin, Mark, Fatemeh Shirbani, Edward Barin, Isabella Tan, Bart Spronck, and Alberto P. Avolio. "Cuffless Estimation of Blood Pressure: Importance of Variability in Blood Pressure Dependence of Arterial Stiffness Across Individuals and Measurement Sites." IEEE Transactions on Biomedical Engineering 65, no. 11 (November 2018): 2377–83. http://dx.doi.org/10.1109/tbme.2018.2823333.

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CASTIGLIONI, Paolo, Gianfranco PARATI, Stefano OMBONI, Giuseppe MANCIA, Ben P. M. IMHOLZ, Karel H. WESSELING, and Marco DI RIENZO. "Broad-band spectral analysis of 24 h continuous finger blood pressure: comparison with intra-arterial recordings." Clinical Science 97, no. 2 (June 16, 1999): 129–39. http://dx.doi.org/10.1042/cs0970129.

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The present study compares the spectral characteristics of 24-h blood pressure variability estimated invasively at the brachial artery level with those estimated by measurement of blood pressure at the finger artery using the non-invasive Portapres device. Broad-band spectra (from 3×10-5 to 0.5 Hz) were derived from both finger and intra-brachial pressures recorded simultaneously for 24 h in eight normotensive and twelve hypertensive ambulant subjects. At frequencies lower than 0.07 Hz, higher spectral estimates were obtained by Portapres than by intra-brachial measurements. The maximum overestimation occurred in systolic pressure at around 10-2 Hz, where the amplitude of the oscillations was two times greater when measured by Portapres. A less pronounced overestimation was found for diastolic pressures. The maximum overestimation was greater during daytime than during night-time. At around 0.1 Hz, invasive and non-invasive spectra were similar. At the respiratory frequencies (0.15-0.50 Hz), the power spectra were overestimated by Portapres during daytime, and underestimated at night. These results provide reference information for the correct interpretation of Portapres data in the estimation of 24-h blood pressure spectral power.

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Hakim, T. S., and S. Kelly. "Occlusion pressures vs. micropipette pressures in the pulmonary circulation." Journal of Applied Physiology 67, no. 3 (September 1, 1989): 1277–85. http://dx.doi.org/10.1152/jappl.1989.67.3.1277.

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Because of the discrepancies between the arterial and venous occlusion technique and the micropuncture technique in estimating pulmonary capillary pressure gradient, we compared measurements made with the two techniques in the same preparations (isolated left lower lobe of dog lung). In addition, we also obtained direct and reliable measurements of pressures in 0.9-mm arteries and veins using a retrograde catheterization technique, as well as a microvascular pressure made with the double-occlusion technique. The following conclusions were made from dog lobes perfused with autologous blood at normal flow rate of 500–600 ml/min and pressure gradient of 12 mmHg. 1) The double-occlusion technique measures pressure in the capillaries, 2) a small pressure gradient (0.5 mmHg) exists between 30- to 50-micron arteries and veins, 3) a large pressure gradient occurs in arteries and veins greater than 0.9 mm, 4) the arterial and venous occlusion techniques measure pressures in vessels that are less than 900 microns diam but greater than 50 microns, very likely close to 100 microns, 5) serotonin constricts arteries (larger and smaller than 0.9 mm) whereas histamine constricts veins (larger and smaller than 0.9 mm). Thus three different techniques (small retrograde catheter, arterial and venous occlusion, and micropuncture) show consistent results, confirming the presence of significant resistance in large arteries and veins with minimal resistance in the microcirculation.

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Moon, Young-Jin, Hyun S. Moon, Dong-Sub Kim, Jae-Man Kim, Joon-Kyu Lee, Woo-Hyun Shim, Sung-Hoon Kim, Gyu-Sam Hwang, and Jae-Soon Choi. "Deep Learning-Based Stroke Volume Estimation Outperforms Conventional Arterial Contour Method in Patients with Hemodynamic Instability." Journal of Clinical Medicine 8, no. 9 (September 9, 2019): 1419. http://dx.doi.org/10.3390/jcm8091419.

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Abstract:

Although the stroke volume (SV) estimation by arterial blood pressure has been widely used in clinical practice, its accuracy is questionable, especially during periods of hemodynamic instability. We aimed to create novel SV estimating model based on deep-learning (DL) method. A convolutional neural network was applied to estimate SV from arterial blood pressure waveform data recorded from liver transplantation (LT) surgeries. The model was trained using a gold standard referential SV measured via pulmonary artery thermodilution method. Merging a gold standard SV and corresponding 10.24 seconds of arterial blood pressure waveform as an input/output data set with 2-senconds of sliding overlap, 484,384 data sets from 34 LT surgeries were used for training and validation of DL model. The performance of DL model was evaluated by correlation and concordance analyses in another 491,353 data sets from 31 LT surgeries. We also evaluated the performance of pre-existing commercialized model (EV1000), and the performance results of DL model and EV1000 were compared. The DL model provided an acceptable performance throughout the surgery (r = 0.813, concordance rate = 74.15%). During the reperfusion phase, where the most severe hemodynamic instability occurred, DL model showed superior correlation (0.861; 95% Confidence Interval, (CI), 0.855–0.866 vs. 0.570; 95% CI, 0.556–0.584, P < 0.001) and higher concordance rate (90.6% vs. 75.8%) over EV1000. In conclusion, the DL-based model was superior for estimating intraoperative SV and thus might guide physicians to precise intraoperative hemodynamic management. Moreover, the DL model seems to be particularly promising because it outperformed EV1000 in circumstance of rapid hemodynamic changes where physicians need most help.

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Journal articles on the topic 'Arterial blood pressure estimation'

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