Pulse Transit Time Measurement Research Articles

Wearable Millimeter-Wave Device for Contactless Measurement of Arterial Pulses.

Wearable monitors for measuring vital signs such as blood pressure will greatly impact the medical field. This work presents a millimeter-wave, radar-based system for performing accurate measurements of arterial pulse waveforms without contacting the region that is pulsing. Electromagnetic and radar-system simulation models are utilized to demonstrate the viability and safety of this approach. This is followed by hardware/software implementation and a study on 12 human subjects. Measured radial arterial waveforms exhibit signal strengths that are well above the noise floor of the system and a morphology that would be expected in an arterial pulse. Finally, comparison of the radar-based signals with a reference tonometer indicates a strong correlation between waveforms, as well as similar spectral signatures. The results observed suggest a millimeter-wave based approach for arterial pulse detection is very promising for future applications in pulse wave analysis and pulse transit time measurement for blood pressure tracking.

Cuffless Blood Pressure Monitoring from an Array of Wrist Bio-Impedance Sensors Using Subject-Specific Regression Models: Proof of Concept.

Continuous and beat-to-beat monitoring of blood pressure (BP), compared to office-based BP measurement, provides significant advantages in predicting future cardiovascular disease. Traditional BP measurement methods are based on a cuff, which is bulky, obtrusive and not applicable to continuous monitoring. Measurement of pulse transit time (PTT) is one of the prominent cuffless methods for continuous BP monitoring. PTT is the time taken by the pressure pulse to travel between two points in an arterial vessel, which is correlated with the BP. In this paper, we present a new cuffless BP method using an array of wrist-worn bio-impedance sensors placed on the radial and the ulnar arteries of the wrist to monitor the arterial pressure pulse from the blood volume changes at each sensor site. BP is accurately estimated by using AdaBoost regression model based on selected arterial pressure pulse features such as transit time, amplitude and slope of the pressure pulse, which are dependent on the cardiac activity and the vascular properties of the wrist arteries. A separate model is developed for each subject based on calibration data to capture the individual variations of BP parameters. In this pilot study, data was collected from 10 healthy participants with age ranges from 18 to 30 years after exercising using our custom low-noise bio-impedance sensing hardware. Post-exercise BP was accurately estimated with an average correlation coefficient and root mean square error (RMSE) of 0.77 and 2.6 mmHg for the diastolic BP and 0.86 and 3.4 mmHg for the systolic BP.

Measurement and Analysis of Local Pulse Transit Time for Emotion Recognition

Emotion recognition based on physiological parameters is a research field that pushes forward from lab settings to real-life investigations. Wearable devices facilitate this advance. However, these devices are still functionally limited compared to stationary medical devices. Our goal is to extend the capability of wearable devices by developing a method that measures the pulse transit time (PTT) locally. The PTT is an interesting parameter regarding emotion recognition. A method for local PTT measurement can be implemented using two photoplethysmography (PPG) sensors. However, this method is error-prone. In this paper, the physiological background that is presumably responsible for erroneous PPG-based PTT measurements is discussed. We present an algorithm that is capable to handle the derived physiological effects. The algorithm analyzes and compares the two PPG-signals to adapt to time-varying physiological effects. By using this algorithm, calculating and analyzing of the local PTT in the context of emotion recognition become possible. A study (n = 40) to test the algorithm and investigate the usefulness of local PTT analysis for emotion recognition in combination with other physiological signals was conducted. PTT-based parameters, which were derived from the frequency domain of the signal, showed a statistically significant (p <; 0.05) difference between induced emotional states, if calculated by the developed algorithm. Our findings indicate that parameters derived by our method are significantly affected by emotional stimuli. We suggest that this method can be used to advance emotion recognition investigations in real life as it can potentially be integrated into a single wearable device.

An empirical model for calculating uniaxial compressive strength of oil well cements from ultrasonic pulse transit time measurements

Thirty-five cement samples were tested in an Ultrasonic Cement Analyzer (UCA) at varying curing conditions and for varying curing times, and then uniaxially compressed to failure in a hydraulic press. An attempt was made, using the ultrasonic transit time data measured with a UCA and the uniaxial compressive strength data measured using a hydraulic press, to derive an empirical model capable of accurately predicting uniaxial compressive strength from the ultrasonic transit time. Using the Levenberg-Marquardt algorithm, the experimental data was fit to two models. In addition to the transit time dependence, the first model presented incorporates a term that accounts for the curing time while the second model contains terms that account for both the curing time and cement composition. The results obtained illustrate the complexity of deriving a correlation with general applicability to all well cements. The best performing model based on both curve fit error and prediction performance for the samples tested was the model that accounted only for the curing time dependency of the cement strength development rate in addition to the measured transit time, indicating that the transit time measurement history is sufficient as a tool for characterizing well cement strength development.

Development of Tubular Cardiovascular Phantom System for Pulse Transit Time Simulation

This paper presents on the development of a tubular cardiovascular phantom system to simulate pulse transit time (PTT). The PTT defined as the delay time between two pulses in one cardiac cycle has been shown to be promising method for cuffless continuous blood pressure (BP) measurement. However most of the PTT measurement was performed on human subjects, thus giving a difficulty in validating sensor performance due to variability of BP. Therefore, a cardiovascular phantom system was proposed for simulate the PTT measurement. An electronic controlled module was developed to control pump operation for pulse generation. Plastic optical fibre (POF) sensors were used to measure the pulse signal on the flexible tube and the results were compared with an in-line pressure sensor. In this experiment, the delay time between two pulses were calculated offline using Matlab software and correlated with pulse pressure. The result demonstrate that the pulse delay time recorded by both sensors decreased with increase of pulse rate and pulse pressure. These results on the phantom study showed similar pattern to the human model, thus indicating that the system is able to simulate PTT for sensor validation purposes.

ANALYSIS OF THE INFLUENCE OF TRANSDUCER FREQUENCY ON THE ULTRASONIC MEASUREMENT OF CONCRETE HOMOGENEITY

The paper analyses the influence of transducer frequency on the determination of concrete homogeneity using the ultrasonic pulse velocity test. Transit time measurements were made on a 590×590mm concrete slab, with 110mm in thickness, in a raster of 5×5 points, which means the slab was tested in 25 places. The tests were made using a Pundit PL-200 ultrasonic tester using transducers set at 54, 82, and 150 kHz. Two types of measurements were performed – spot measurements of the ultrasonic pulse transit time at each point and full area scanning. The paper is concluded by an evaluation of the concrete slab’s homogeneity measured by different transducers and techniques in addition to a statistical analysis of how the results are affected by the transducer frequency.

Photoplethysmography for Quantitative Assessment of Sympathetic Nerve Activity (SNA) During Cold Stress.

The differences in the degree of sympathetic nerve activity (SNA) over cutaneous blood vessels, although known to be more prominent in the periphery than the core vasculature, has not been thoroughly investigated quantitatively. Hence, two studies were carried out to investigate the differences in SNA between the periphery and the core during the cold pressor test (CPT) (right-hand immersion in ice water) and cold exposure (whole body exposed to cold air) using photoplethysmography (PPG). Two methods utilizing PPG, namely differential multi-site PTT measurements and low-frequency spectral analysis were explored for quantitative determination of SNA. Each study involved 12 healthy volunteers, and PPG signals were acquired from the right index finger (RIF), left index finger (LIF) (periphery) and the ear canal (core). During CPT, Pulse Transit Time (PTT) was measured to the respective locations and the mean percentage change in PTT during ice immersion at each location was used as an indicator for the extent of SNA. During cold exposure, the low-frequency spectral analysis was performed on the acquired raw PPGs to extract the power of the sympathetic [low-frequency (LF): 0.04–0.15 Hz] and parasympathetic components [high-frequency (HF): 0.15–0.4 Hz]. The ratio of LF/HF components was then used to quantify the differences in the influence of SNA on the peripheral and core circulation. PTT measured from the EC, and the LIF has dropped by 5 and 7%, respectively during ice immersion. The RIF PTT, on the other hand, has dropped significantly (P < 0.05) by 12%. During the cold exposure, the LF/HF power ratio at the finger has increased to 86.4 during the cold exposure from 19.2 at the baseline (statistically significant P = 0.002). While the ear canal LF/HF ratio has decreased to 1.38 during the cold exposure from 1.62 at baseline (P = 0.781). From these observations, it is evident that differential PTT measurements or low-frequency analysis can be used to quantify SNA. The results also demonstrate the effectiveness of the central auto-regulation during both short and long-term stress stimulus as compared to the periphery.

Cuffless and Continuous Blood Pressure Monitoring Using a Single Chest-Worn Device

Continuous blood pressure (BP) monitoring in daily life is needed to enable early detection of hypertension and improve its control. Although pulse transit time (PTT)-based BP estimation represents a promising approach, it still lacks of performance in systolic blood pressure (SBP) estimation and its use in daily life is limited owing to the requirement of bulky systems for measurement of PTT. This study aims at developing a wearable system providing continuous PTT measurement and enhanced SBP estimation for continuous BP monitoring. A single chest-worn device was developed, which measures the photoplethysmogram and seismocardiogram simultaneously, and thereby obtains PTT by time difference between two signals. A multivariate model using the seismocardiogram amplitude (SA) in conjunction with PTT was proposed for SBP estimation, and validated against 30 healthy males (31.47 ± 7.23 years old). Performance of the proposed model was compared with that of conventional univariate models using PTT or pulse arrival time in two types of BP interventions, and for the verification of real use in daily life, performance assessment with calibration and BP monitoring in daily life were conducted. The results suggested that the proposed model (1) outperformed the conventional models, (2) showed potential to be generalized with just a simple calibration, and (3) demonstrated the potential of continuous BP monitoring in daily life. In conclusion, the presented system provides an improved performance of continuous BP monitoring by using a combination of PTT and SA with a convenient and compact single chest-worn device, and thus, it can contribute to mobile healthcare services.

A novel approach for non-invasive measurement of mean arterial pressure using pulse transit time

Recent days many researches are carried out related to the heart of the human. As a result many remedies are found for the various heart disorders. Electrocardiography (ECG) is the exertion of the electrical response from heart by placing the electrodes over the chest. The Einthoven triangle is an imaginary formation of the three leads in the triangle used in electrocardiography; by that technique of placement of electrode we can analysis the electrocardiogram of the heart. The waveform is also known as PQR waveform which contains the information of arterial repolarization, arterial polarization, ventricular repolarization and ventricular polarization. In general the BP monitor is carried out using oscillometry. In the existing system separate techniques and devices are used to measure electrocardiography and BP. The proposed system is to integrate both electrocardiography and blood pressure measurement by means adopting transit pulse time. It is defined as the systematic time lay off betwixt oscillometric pulses and peaks of ECG especially R peaks of it. The major advantage of the system is to exhibit non-zero crossing and gives more accurate result. The mean arterial pressure estimation is done by using MatLab which is the unique estimation method for measuring pulse transit time interval. Thus the non invasive system designed which reduce the cuff deviations and errors in electrocardiography. It can be applied in detecting the arterial disorders at most efficient manner.

Novel retinal artery pulse transit time measurement shows expected blood pressure dependency in rodents

Novel retinal artery pulse transit time measurement shows expected blood pressure dependency in rodents

Small intra-individual variability of the pre-ejection period justifies the use of pulse transit time as approximation of the vascular transit.

BackgroundVascular transit time (VTT) is the propagation time of a pulse wave through an artery; it is a measure for arterial stiffness. Because reliable non-invasive VTT measurements are difficult, as an alternative we measure pulse transit time (PTT). PTT is defined as the time between the R-wave on electrocardiogram and arrival of the resulting pulse wave in a distal location measured with photoplethysmography (PPG). The time between electrical activation of the ventricles and the resulting pulse wave after opening of the aortic valve is called the pre-ejection period (PEP), a component of PTT. The aim of this study was to estimate the variability of PEP at rest, to establish how accurate PTT is as approximation of VTT.MethodsPTT was measured and PEP was assessed with echocardiography (gold standard) in three groups of 20 volunteers: 1) a control group without cardiovascular disease aged <50 years and 2) aged >50 years, and 3) a group with cardiovascular risk factors, defined as arterial hypertension, dyslipidemia, kidney failure and diabetes mellitus.ResultsPer group, the mean PEP was: 1) 58.5 ± 13.0 ms, 2) 52.4 ± 11.9 ms, and 3) 57.6 ± 11.6 ms. However, per individual the standard deviation was much smaller, i.e. 1) 2.0–5.9 ms, 2) 2.8–5.1 ms, and 3) 1.6–12.0 ms, respectively. There was no significant difference in the mean PEP of the 3 groups (p = 0.236).ConclusionIn conclusion, the intra-individual variability of PEP is small. A change in PTT in a person at rest is most probably the result of a change in VTT rather than of PEP. Thus, PTT at rest is an easy, non-invasive and accurate approximation of VTT for monitoring arterial stiffness.

Continuous Blood Pressure Monitoring using Wrist-worn Bio-impedance Sensors with Wet Electrodes.

Continuous blood pressure (BP) monitoring is essential for diagnosis and management of cardiovascular disorders. Currently, BP is measured using cuff-based methods, which are obtrusive and not suitable for continuous monitoring. Estimation of BP using pulse transit time (PTT) is a prominent method that eliminates the need for a cuff. In this paper, we present a new method to estimate BP based on PTT measurements from an array of 2×2 bio-impedance sensors placed on the wrist, which can be integrated into a small wearable device such as a smart watch for continuous BP monitoring. Diastolic and systolic BP were estimated using AdaBoost regression model based on PTT features extracted from the wrist bio-impedance signals. Data was collected from three participants using our custom bio-impedance sensors. Our method can estimate BP accurately with correlation coefficient, mean absolute error (MAE) and standard deviation (STD) of 0.92, 1.71 and 2.46 mmHg for the diastolic BP and 0.94, 2.57 and 4.35 mmHg for the systolic BP.

A Low-cost, Smartphone-only Pulse Transit Time Measurement System Using Cardio-mechanical Signals and Optical Sensors.

This paper presents a smartphone-only solution for measuring pulse transit time (PTT). An application based on an Android smartphone is developed to collect seismocardiogram (SCG), gyrocardiogram (GCG), and photoplethysmography (PPG) recordings. The system does not need any other external system for measurements, so the total cost and system complexity are minimized. PTT metrics are calculated as the time difference between the aortic valve opening points in the SCG or GCG signals recorded by the accelerometer or gyroscope of a smartphone respectively, and the fiducial points in the PPG signal recorded by a modified optical sensor connected to the audio input. A digital signal processing (DSP) system is developed in a post-processing environment and experimentally validated on ten healthy subjects at rest. Our results indicate that a smartphone-only PTT measurement system is feasible and comparable with stand-alone sensor node systems.

Exploration and validation of alternate sensing methods for wearable continuous pulse transit time measurement using optical and bioimpedance modalities.

In this work we explore the viability of a multimodal sensing device that can be integrated in a wearable form factor for daily, non-invasive ambulatory blood pressure (BP) monitoring. A common approach in previous research has been to rely on measuring the pulse transit time (PTT), which has been shown to be correlated with the BP. In this work, we look into the feasibility of measuring PTT using sensors separated by a small distance on one arm so that any eventual realization of the system is convenient to wear and use over long periods of time. Moreover, we investigate the combined use of two different modalities for cardiovascular measurement: the optical photoplethysmogram (PPG) as well as the bio-potential based impedance (Bio-Z) measurement. These two modalities have been previously only studied on their own or in conjunction with the electrocardiogram (ECG) for the purpose of estimating PTT. We measure the PTT from the wrist to the finger using Bio-Z and PPG sensors, and compare it to the conventional PTT measured from the ECG to PPG at the finger, in order to prove that it can be an effective replacement for existing PTT measurement strategies. Moreover, successful measurement of PTT with two different modalities of sensors at close proximity will allow designs with multiple heterogeneous sensors on a more versatile wearable sensing platform that is optimized for power and is more robust to environmental or skin contact changes. This will enable the next generation of smart watches that capture PTT and BP. Experiments were conducted in vivo with simultaneous ECG, Bio-Z and PPG sensors, and results indicate that the PTT calculated from the Bio-Z and PPG sensors placed at a close distance correlates well with the more established PTT measurement using the ECG in conjunction with PPG, with correlation coefficient as high as 0.92.

Reproducibility of photoplethysmography-based local pulse transit time measurement.

There are several previously published approaches of measuring local pulse transit time (PTT). One of these approaches is to use two optical sensors based on photoplethysmography (PPG). However, little information about reproducibility in PPG based PTT measurement is available. Therefore, we performed a small sample size study (n = 5) to investigate quantitative criteria for reproducible PTT measurement. The inflection point as a characteristic feature of the pulse wave showed the most stabile results under varying conditions. Furthermore, we found that correlation between related pulse waves could be used as a threshold for signal quality. We suggest to implement a real-time operator feedback based on the found criteria to ensure reproducible PTT measurements.

Robust Sensing of Distal Pulse Waveforms on a Modified Weighing Scale for Ubiquitous Pulse Transit Time Measurement.

The measurement of aortic pulse transit time (PTT), the time for the arterial pulse wave to travel from the carotid to the femoral artery, can provide valuable insight into cardiovascular health, specifically regarding arterial stiffness and blood pressure (BP). To measure aortic PTT, both proximal and distal arterial pulse timings are required. Recently, our group has demonstrated that the ballistocardiogram signal measured on a modified weighing scale can provide an unobtrusive, yet accurate, means of obtaining a proximal timing reference; however, there are no convenient, reliable methods to extract the distal timing from a subject standing on the modified weighing scale. It is common to use a photoplethysmograph (PPG) attached to a toe to measure this distal pulse, but we discovered that this signal is greatly deteriorated as the subject stands on the scale. In this paper, we propose a novel method to measure the distal pulse using a custom reflective PPG array attached to the dorsum side of the foot (D-PPG). A total of 12 subjects of varying skin tones were recruited to assess the preliminary validation of this approach. Pulse measurements using the D-PPG were taken from seated and standing subjects, and the commercially available PPG were measured for facilitating comparison of timing measurements. We show that the D-PPG was the only sensor to retain the high detection rate of feasible timing values. To further test and optimize the system, various factors such as applied pressure, measurement location, and LED/photodiode configuration were tested.

Pulse Transit Time Measurement Using Seismocardiogram, Photoplethysmogram, and Acoustic Recordings: Evaluation and Comparison.

This work proposes a novel method of pulse transit time (PTT) measurement. The proximal arterial location data are collected from seismocardiogram (SCG) recordings by placing a micro-electromechanical accelerometer on the chest wall. The distal arterial location data are recorded using an acoustic sensor placed inside the ear. The performance of distal location recordings is evaluated by comparing SCG-acoustic and SCG-photoplethysmogram (PPG) measurements. PPG and acoustic performances under motion noise are also compared. Experimental results suggest comparable performances for the acoustic-based and PPG-based devices. The feasibility of each PTT measurement method is validated for blood pressure evaluations and its limitations are analyzed.

Increasing accuracy of pulse transit time measurements by automated elimination of distorted photoplethysmography waves

Photoplethysmography (PPG) is a widely available non-invasive optical technique to visualize pressure pulse waves (PWs). Pulse transit time (PTT) is a physiological parameter that is often derived from calculations on ECG and PPG signals and is based on tightly defined characteristics of the PW shape. PPG signals are sensitive to artefacts. Coughing or movement of the subject can affect PW shapes that much that the PWs become unsuitable for further analysis. The aim of this study was to develop an algorithm that automatically and objectively eliminates unsuitable PWs. In order to develop a proper algorithm for eliminating unsuitable PWs, a literature study was conducted. Next, a ‘7Step PW-Filter’ algorithm was developed that applies seven criteria to determine whether a PW matches the characteristics required to allow PTT calculation. To validate whether the ‘7Step PW-Filter’ eliminates only and all unsuitable PWs, its elimination results were compared to the outcome of manual elimination of unsuitable PWs. The ‘7Step PW-Filter’ had a sensitivity of 96.3% and a specificity of 99.3%. The overall accuracy of the ‘7Step PW-Filter’ for detection of unsuitable PWs was 99.3%. Compared to manual elimination, using the ‘7Step PW-Filter’ reduces PW elimination times from hours to minutes and helps to increase the validity, reliability and reproducibility of PTT data.

Highly wearable cuff-less blood pressure and heart rate monitoring with single-arm electrocardiogram and photoplethysmogram signals

BackgroundLong-term continuous systolic blood pressure (SBP) and heart rate (HR) monitors are of tremendous value to medical (cardiovascular, circulatory and cerebrovascular management), wellness (emotional and stress tracking) and fitness (performance monitoring) applications, but face several major impediments, such as poor wearability, lack of widely accepted robust SBP models and insufficient proofing of the generalization ability of calibrated models.MethodsThis paper proposes a wearable cuff-less electrocardiography (ECG) and photoplethysmogram (PPG)-based SBP and HR monitoring system and many efforts are made focusing on above challenges. Firstly, both ECG/PPG sensors are integrated into a single-arm band to provide a super wearability. A highly convenient but challenging single-lead configuration is proposed for weak single-arm-ECG acquisition, instead of placing the electrodes on the chest, or two wrists. Secondly, to identify heartbeats and estimate HR from the motion artifacts-sensitive weak arm-ECG, a machine learning-enabled framework is applied. Then ECG-PPG heartbeat pairs are determined for pulse transit time (PTT) measurement. Thirdly, a PTT&HR-SBP model is applied for SBP estimation, which is also compared with many PTT-SBP models to demonstrate the necessity to introduce HR information in model establishment. Fourthly, the fitted SBP models are further evaluated on the unseen data to illustrate the generalization ability. A customized hardware prototype was established and a dataset collected from ten volunteers was acquired to evaluate the proof-of-concept system.ResultsThe semi-customized prototype successfully acquired from the left upper arm the PPG signal, and the weak ECG signal, the amplitude of which is only around 10% of that of the chest-ECG. The HR estimation has a mean absolute error (MAE) and a root mean square error (RMSE) of only 0.21 and 1.20 beats per min, respectively. Through the comparative analysis, the PTT&HR-SBP models significantly outperform the PTT-SBP models. The testing performance is 1.63 ± 4.44, 3.68, 4.71 mmHg in terms of mean error ± standard deviation, MAE and RMSE, respectively, indicating a good generalization ability on the unseen fresh data.ConclusionsThe proposed proof-of-concept system is highly wearable, and its robustness is thoroughly evaluated on different modeling strategies and also the unseen data, which are expected to contribute to long-term pervasive hypertension, heart health and fitness management.

Pilot Study: Estimation of Stroke Volume and Cardiac Output from Pulse Wave Velocity

BackgroundTransesophageal echocardiography (TEE) is increasingly replacing thermodilution pulmonary artery catheters to assess hemodynamics in patients at high risk for cardiovascular morbidity. However, one of the drawbacks of TEE compared to pulmonary artery catheters is the inability to measure real time stroke volume (SV) and cardiac output (CO) continuously. The aim of the present proof of concept study was to validate a novel method of SV estimation, based on pulse wave velocity (PWV) in patients undergoing cardiac surgery.MethodsThis is a retrospective observational study. We measured pulse transit time by superimposing the radial arterial waveform onto the continuous wave Doppler waveform of the left ventricular outflow tract, and calculated SV (SVPWV) using the transformed Bramwell-Hill equation. The SV measured by TEE (SVTEE) was used as a reference.ResultsA total of 190 paired SV were measured from 28 patients. A strong correlation was observed between SVPWV and SVTEE with the coefficient of determination (R2) of 0.71. A mean difference between the two (bias) was 3.70 ml with the limits of agreement ranging from -20.33 to 27.73 ml and a percentage error of 27.4% based on a Bland-Altman analysis. The concordance rate of two methods was 85.0% based on a four-quadrant plot. The angular concordance rate was 85.9% with radial limits of agreement (the radial sector that contained 95% of the data points) of ± 41.5 degrees based on a polar plot.ConclusionsPWV based SV estimation yields reasonable agreement with SV measured by TEE. Further studies are required to assess its utility in different clinical situations.