Correction factor estimation for a parametric model between pulse transit time and systolic blood pressure, for non-invasive blood pressure estimation

Author(s):  
W.U.C. De Alwis ◽  
R.N.S. Rajapaksha ◽  
N.N.S. Ranaweera ◽  
P.A.P.M.B. Pitigalaarachchi ◽  
A. Pasqual
2016 ◽  
Vol 3 (1) ◽  
Author(s):  
Hieyong Jeong ◽  
Kayo Yoshimoto ◽  
Tianyi Wang ◽  
Takafumi Ohno ◽  
Kenji Yamada ◽  
...  

Diagnostics ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 361
Author(s):  
Leo Kilian ◽  
Philipp Krisai ◽  
Thenral Socrates ◽  
Christian Arranto ◽  
Otmar Pfister ◽  
...  

Background: The Somnotouch-Non-Invasive-Blood-Pressure (NIBP) device delivers raw data consisting of electrocardiography and photoplethysmography for estimating blood pressure (BP) over 24 h using pulse-transit-time. The study’s aim was to analyze the impact on 24-hour BP results when processing raw data by two different software solutions delivered with the device. Methods: We used data from 234 participants. The Somnotouch-NIBP measurements were analyzed using the Domino-light and Schiller software and compared. BP values differing >5 mmHg were regarded as relevant and explored for their impact on BP classification (normotension vs. hypertension). Results: Mean (±standard deviation) absolute systolic/diastolic differences for 24-hour mean BP were 1.5 (±1.7)/1.1 (±1.3) mm Hg. Besides awake systolic BP (p = 0.022), there were no statistically significant differences in systolic/diastolic 24-hour mean, awake, and asleep BP. Twenty four-hour mean BP agreement (number (%)) between the software solutions within 5, 10, and 15 mmHg were 222 (94.8%), 231 (98.7%), 234 (100%) for systolic and 228 (97.4%), 232 (99.1%), 233 (99.5%) for diastolic measurements, respectively. A BP difference of >5 mmHg was present in 24 (10.3%) participants leading to discordant classification in 4–17%. Conclusion: By comparing the two software solutions, differences in BP are negligible at the population level. However, at the individual level there are, in a minority of cases, differences that lead to different BP classifications, which can influence the therapeutic decision.


2021 ◽  
Vol 7 (2) ◽  
pp. 843-846
Author(s):  
Dagmar Krefting ◽  
Tibor Kesztyüs ◽  
Henning Dathe

Abstract Continuous non-invasive blood pressure measurements bear a high potential. Particular in Somnology they allow to derive comfortably the systolic and diastolic blood pressure from an electrocardiogram and a synchronous photoplethysmogram without sleep disruption. In this short article some possible problems of this method are discussed along overnight recordings with a SOMNOtouch NIBP device.


Author(s):  
Ajay K. Verma ◽  
John Zanetti ◽  
Reza Fazel-Rezai ◽  
Kouhyar Tavakolian

Blood pressure is an indicator of a cardiovascular functioning and could provide early symptoms of cardiovascular system impairment. Blood pressure measurement using catheterization technique is considered the gold standard for blood pressure measurement [1]. However, due its invasive nature and complexity, non-invasive techniques of blood pressure estimation such as auscultation, oscillometry, and volume clamping have gained wide popularity [1]. While these non-invasive cuff based methodologies provide a good estimate of blood pressure, they are limited by their inability to provide a continuous estimate of blood pressure [1–2]. Continuous blood pressure estimate is critical for monitoring cardiovascular diseases such as hypertension and heart failure. Pulse transit time (PTT) is a time taken by a pulse wave to travel between a proximal and distal arterial site [3]. The speed at which pulse wave travels in the artery has been found to be proportional to blood pressure [1, 3]. A rise in blood pressure would cause blood vessels to increase in diameter resulting in a stiffer arterial wall and shorter PTT [1–3]. To avail such relationship with blood pressure, PTT has been extensively used as a marker of arterial elasticity and a non-invasive surrogate for arterial blood pressure estimation. Typically, a combination of electrocardiogram (ECG) and photoplethysmogram (PPG) or arterial blood pressure (ABP) signal is used for the purpose of blood pressure estimation [3], where the proximal and distal timing of PTT (also referred as pulse arrival time, PAT) is marked by R peak of ECG and a foot/peak of a PPG, respectively. In the literature, it has been shown that PAT derived using ECG-PPG combination infers an inaccurate estimate of blood pressure due to the inclusion of isovolumetric contraction period [1–3, 4]. Seismocardiogram (SCG) is a recording of chest acceleration due to heart movement, from which the opening and closing of the aortic valve can be obtained [5]. There is a distinct point on the dorso-ventral SCG signal that marks the opening of the aortic valve (annotated as AO). In the literature, AO has been proposed for timing the onset of the proximal pulse of the wave [6–8]. A combination of AO as a proximal pulse and PPG as a distal pulse has been used to derive pulse transit time and is shown to be correlated with blood pressure [7]. Ballistocardiogram (BCG) which is a measure of recoil forces of a human body in response to pumping of blood in blood vessels has also been explored as an alternative to ECG for timing proximal pulse [5, 9]. Use of SCG or BCG for timing the proximal point of a pulse can overcome the limitation of ECG-based PTT computation [6–7, 9]. However, a limitation of current blood pressure estimation systems is the requirement of two morphologically different signals, one for annotating the proximal (ECG, SCG, BCG) and other for annotating the distal (PPG, ABP) timing of a pulse wave. In the current research, we introduce a methodology to derive PTT from seismocardiograms alone. Two accelerometers were used for such purpose, one was placed on the xiphoid process of the sternum (marks proximal timing) and the other one was placed on the external carotid artery (marks distal timing). PTT was derived as a time taken by a pulse wave to travel between AO of both the xiphoidal and carotid SCG.


2020 ◽  
Author(s):  
Sebastian Schaanning ◽  
Nils Kristian Skjærvold

Abstract Background : Substantial investigation has been made into the correlation between Pulse Transit Time (PTT) and Blood Pressure (BP), as a possible route to achieve continuous non-invasive measurement of BP (cNIBP). We investigated whether PTT-trends could model BP-trends during episodes of rapid declines in Systolic Blood Pressure (SBP). Methods: From the freely available Medical Information Mart for Intensive Care (MIMIC-III) waveform database, we identified subjects who experienced a reduction in SBP from ≥ 120mmHg to ≤ 90 mmHg during a period of ≤ 15 minutes, for whom complete peak detection was possible. SBP was extracted from the Arterial Blood Pressure (ABP) waveform, and PTT was calculated from the R-peak of the ECG to the peak of the ABP waveform. Both SBP and PTT were processed using a moving average filter, yielding the variables SBP AV and PTT-RA AV . A moving average of continuous heart rate (HR AV ) was also analysed as a negative control to assess the effect of averaging. The intra-individual association between variables was assessed per subject using linear regression. Results: 511 patients were included for the main analysis. Median correlation coefficients (r) obtained from linear regression versus SBP AV were as follows: PTT-RA AV -0.93 (IQR -0.98 to -0.76), HR AV 0.46 (IQR -0.16 to 0.83). Regression slopes for the relationship between SBP AV and PTT-RA AV displayed a median of -2.46 mmHg/ms (IQR -3.47 mmHg/ms to -1.61 mmHg/ms). In supplementary analysis, results did not differ substantially when widening inclusion criteria, but the results were not always consistent within subjects across episodes of hypotension. Conclusions: In a large cohort of critically ill patients experiencing episodes of rapid declines in systolic blood pressure, there was a moderate-strong intra-individual correlation between averaged systolic blood pressure and averaged pulse transit time as measured from ECG R-peak to the peak of the arterial blood pressure waveform. Our findings encourage further investigation into using the pulse transit time for non-invasive real-time detection of hypotension.


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