scholarly journals Novel computation of pulse transit time from multi-channel PPG signals by wavelet transform

2016 ◽  
Vol 2 (1) ◽  
pp. 209-213 ◽  
Author(s):  
Alexandru-Gabriel Pielmuş ◽  
Maik Pflugradt ◽  
Timo Tigges ◽  
Michael Klum ◽  
Aarne Feldheiser ◽  
...  

AbstractBeing able to accurately monitor blood pressure in a reliable, truly non-invasive manner is a highly sought after goal within the biomedical community. In this paper we propose and assess a system, methodology and algorithm for unobtrusively obtaining true pulse transit time data from readily accessible peripheral locations, such as the hand, using a highly synchronous body-sensor-network encompassing an electrocardiogram- and dual mode photoplethysmogram sensor node. The results suggest the feasibility of acquiring such data, which strongly correlates with the recorded reference blood pressure, and can therefore be further employed to track changes thereof.

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.


2019 ◽  
Vol 10 (1) ◽  
pp. 61
Author(s):  
Ernia Susana

<p>Currently used non-invasive blood pressure (NIBP) measurements (oscillometric method) has disadvantages related to pumping cuffs which can cause discomfort for patients due to pressure from pumping cuffs.  The aim of this study was to measure blood pressure in a non-invasive manner without cuffs with the Pulse Transit Time (PTT) methodbase on machine learning technology.The blood pressure measurement by the PTT method is obtained from the calculation of the distance of the R-ECG wave with the peak signal <em>photoplethysmogram</em><em> </em>(PPG). The main problem of the PTT method in some previous studies is that the estimation of systolic (SBP) and diastolic (DBP) values is still inaccurate. The blood pressure measurement method in this study used a combination of PTT calculations with machine learning multivariate regression. Therefore expected to obtain a more accurate estimate of systolic (SBP) and diastolic blood pressure (DBP). This study is a laboratory experiment research on 30 healthy volunteers aged 20 ± 1 years. The measurement of the blood pressure value of the PTT-to-oscillometric method is 5 ± 5 mmHg. The blood pressure values generated by this PTT method have a p-value for the sequential estimation of SBP and DBP of 0.7374 and 0.0262.<strong></strong></p>


Author(s):  
Hong Long Pua ◽  
Kok Beng Gan

It is not only a problem for old age anyone. So, blood pressure is the one provides importance information with vital signs about cardiovascular health using oscillometric method. Unfortunately, this method required inflation and following deflation of the cuff. This method only gives instantaneous blood pressure and continuous measurement is not available. It is not available to the patients that required long term monitoring. To overcome this problem, the development of Continuous Non-Invasive Blood Pressure (NIBP) algorithm based on Pulse Transit Time (PTT) using two channel Photoplethysmograph (PPG) is proposed in this study. PPG is a non-invasive device for detecting blood volume changes can be affected by various physiological factors, analysis of the PPG signal can provide sufficient information on the human health condition; more specifically their cardio-vascular related performance. Literatures show that the PTT has linear relationship with blood pressure. Nevertheless, the determination of the model structure, order and real-time implementation to offer a continuous measurement of the PTT still remains challenging tasks in this area. PTT can be as index to monitor cardiovascular disease. In this project, dynamic model based on pulse transit time will be proposed to continuously monitor blood pressure by using PPG signals. Different kind of resolutions in microcontroller combined with PPG sensor will be used as well. MATLAB software is also been applied for PTT calculation based on two PPG sensors. PPG is method for detect blood volume changes with optical source transmitter send from one end and received the signal from another by receiver through body tissue as medium. MATLAB functions as Digital Signal Processing (DSP) for signals received in computer. Linear Regression technique and Fung's algorithm are applied to obtain the best fit line for all the points in order to systolic and diastolic blood pressure measurement. The results showed that the algorithm based on pulse transit time has been developed for the assessment of blood pressure and justify patient’ condition with 86.34% and 88.20% accuracy. Finally, this technique is a simple, user friendly and operator independent PPG system suitable for long term and wearable blood pressure monitor.


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.


Sign in / Sign up

Export Citation Format

Share Document