Continuous blood pressure monitoring using ECG and finger photoplethysmogram

Investigation of Optimal Light Source Wavelength for Cuffless Blood Pressure Estimation Using a Single Photoplethysmography Sensor

Routine blood pressure measurement is important for the early detection of various diseases. Recently, cuffless blood pressure estimation methods that do not require cuff pressurization have attracted attention. In this study, we investigated the effect of the light source wavelength on the accuracy of blood pressure estimation using only two physiological indices that can be calculated with photoplethysmography alone, namely, heart rate and modified normalized pulse volume. Using a newly developed photoplethysmography sensor that can simultaneously measure photoplethysmograms at four wavelengths, we evaluated its estimation accuracy for systolic blood pressure, diastolic blood pressure, and mean arterial pressure against a standard cuff sphygmomanometer. Mental stress tasks were used to alter the blood pressure of 14 participants, and multiple linear regression analysis showed the best light sources to be near-infrared for systolic blood pressure and blue for both diastolic blood pressure and mean arterial pressure. The importance of the light source wavelength for the photoplethysmogram in cuffless blood pressure estimation was clarified.

Photoplethysmogram Analysis and Applications: An Integrative Review

Beyond its use in a clinical environment, photoplethysmogram (PPG) is increasingly used for measuring the physiological state of an individual in daily life. This review aims to examine existing research on photoplethysmogram concerning its generation mechanisms, measurement principles, clinical applications, noise definition, pre-processing techniques, feature detection techniques, and post-processing techniques for photoplethysmogram processing, especially from an engineering point of view. We performed an extensive search with the PubMed, Google Scholar, Institute of Electrical and Electronics Engineers (IEEE), ScienceDirect, and Web of Science databases. Exclusion conditions did not include the year of publication, but articles not published in English were excluded. Based on 118 articles, we identified four main topics of enabling PPG: (A) PPG waveform, (B) PPG features and clinical applications including basic features based on the original PPG waveform, combined features of PPG, and derivative features of PPG, (C) PPG noise including motion artifact baseline wandering and hypoperfusion, and (D) PPG signal processing including PPG preprocessing, PPG peak detection, and signal quality index. The application field of photoplethysmogram has been extending from the clinical to the mobile environment. Although there is no standardized pre-processing pipeline for PPG signal processing, as PPG data are acquired and accumulated in various ways, the recently proposed machine learning-based method is expected to offer a promising solution.

A Comparison of Deep Learning Techniques for Arterial Blood Pressure Prediction

Continuous vital signal monitoring is becoming more relevant in preventing diseases that afflict a large part of the world’s population; for this reason, healthcare equipment should be easy to wear and simple to use. Non-intrusive and non-invasive detection methods are a basic requirement for wearable medical devices, especially when these are used in sports applications or by the elderly for self-monitoring. Arterial blood pressure (ABP) is an essential physiological parameter for health monitoring. Most blood pressure measurement devices determine the systolic and diastolic arterial blood pressure through the inflation and the deflation of a cuff. This technique is uncomfortable for the user and may result in anxiety, and consequently affect the blood pressure and its measurement. The purpose of this paper is the continuous measurement of the ABP through a cuffless, non-intrusive approach. The approach of this paper is based on deep learning techniques where several neural networks are used to infer ABP, starting from photoplethysmogram (PPG) and electrocardiogram (ECG) signals. The ABP was predicted first by utilizing only PPG and then by using both PPG and ECG. Convolutional neural networks (ResNet and WaveNet) and recurrent neural networks (LSTM) were compared and analyzed for the regression task. Results show that the use of the ECG has resulted in improved performance for every proposed configuration. The best performing configuration was obtained with a ResNet followed by three LSTM layers: this led to a mean absolute error (MAE) of 4.118 mmHg on and 2.228 mmHg on systolic and diastolic blood pressures, respectively. The results comply with the American National Standards of the Association for the Advancement of Medical Instrumentation. ECG, PPG, and ABP measurements were extracted from the MIMIC database, which contains clinical signal data reflecting real measurements. The results were validated on a custom dataset created at Neuronica Lab, Politecnico di Torino.

Noninvasive Hemoglobin Level Prediction in a Mobile Phone Environment: State of the Art Review and Recommendations

BACKGROUND

There is worldwide demand for an affordable hemoglobin measurement solution, which is a particularly urgent need in developing countries. The smartphone, which is the most penetrated device in both rich and resource-constrained areas, would be a suitable choice to build this solution. Consideration of a smartphone-based hemoglobin measurement tool is compelling because of the possibilities for an affordable, portable, and reliable point-of-care tool by leveraging the camera capacity, computing power, and lighting sources of the smartphone. However, several smartphone-based hemoglobin measurement techniques have encountered significant challenges with respect to data collection methods, sensor selection, signal analysis processes, and machine-learning algorithms. Therefore, a comprehensive analysis of invasive, minimally invasive, and noninvasive methods is required to recommend a hemoglobin measurement process using a smartphone device.

OBJECTIVE

In this study, we analyzed existing invasive, minimally invasive, and noninvasive approaches for blood hemoglobin level measurement with the goal of recommending data collection techniques, signal extraction processes, feature calculation strategies, theoretical foundation, and machine-learning algorithms for developing a noninvasive hemoglobin level estimation point-of-care tool using a smartphone.

METHODS

We explored research papers related to invasive, minimally invasive, and noninvasive hemoglobin level measurement processes. We investigated the challenges and opportunities of each technique. We compared the variation in data collection sites, biosignal processing techniques, theoretical foundations, photoplethysmogram (PPG) signal and features extraction process, machine-learning algorithms, and prediction models to calculate hemoglobin levels. This analysis was then used to recommend realistic approaches to build a smartphone-based point-of-care tool for hemoglobin measurement in a noninvasive manner.

RESULTS

The fingertip area is one of the best data collection sites from the body, followed by the lower eye conjunctival area. Near-infrared (NIR) light-emitting diode (LED) light with wavelengths of 850 nm, 940 nm, and 1070 nm were identified as potential light sources to receive a hemoglobin response from living tissue. PPG signals from fingertip videos, captured under various light sources, can provide critical physiological clues. The features of PPG signals captured under 1070 nm and 850 nm NIR LED are considered to be the best signal combinations following a dual-wavelength theoretical foundation. For error metrics presentation, we recommend the mean absolute percentage error, mean squared error, correlation coefficient, and Bland-Altman plot.

CONCLUSIONS

We addressed the challenges of developing an affordable, portable, and reliable point-of-care tool for hemoglobin measurement using a smartphone. Leveraging the smartphone's camera capacity, computing power, and lighting sources, we define specific recommendations for practical point-of-care solution development. We further provide recommendations to resolve several long-standing research questions, including how to capture a signal using a smartphone camera, select the best body site for signal collection, and overcome noise issues in the smartphone-captured signal. We also describe the process of extracting a signal's features after capturing the signal based on fundamental theory. The list of machine-learning algorithms provided will be useful for processing PPG features. These recommendations should be valuable for future investigators seeking to build a reliable and affordable hemoglobin prediction model using a smartphone.

Sleep Deprivation Deteriorates Heart Rate Variability and Photoplethysmography

Introduction

Sleep deprivation has deleterious effects on cardiovascular health. Using wearable health trackers, non-invasive physiological signals, such as heart rate variability (HRV), photoplethysmography (PPG), and baroreflex sensitivity (BRS) can be analyzed for detection of the effects of partial sleep deprivation on cardiovascular responses.

Methods

Fifteen participants underwent 1 week of baseline recording (BSL, usual day activity and sleep) followed by 3 days with 3 h of sleep per night (SDP), followed by 1 week of recovery with sleep ad lib (RCV). HRV was recorded using an orthostatic test every morning [root mean square of the successive differences (RMSSD), power in the low-frequency (LF) and high-frequency (HF) bands, and normalized power nLF and nHF were computed]; PPG and polysomnography (PSG) were recorded overnight. Continuous blood pressure and psychomotor vigilance task were also recorded. A questionnaire of subjective fatigue, sleepiness, and mood states was filled regularly.

Results

RMSSD and HF decreased while nLF increased during SDP, indicating a decrease in parasympathetic activity and a potential increase in sympathetic activity. PPG parameters indicated a decrease in amplitude and duration of the waveforms of the systolic and diastolic periods, which is compatible with increases in sympathetic activity and vascular tone. PSG showed a rebound of sleep duration, efficiency, and deep sleep in RCV compared to BSL. BRS remained unchanged while vigilance decreased during SDP. Questionnaires showed an increased subjective fatigue and sleepiness during SDP.

Conclusion

HRV and PPG are two markers easily measured with wearable devices and modified by partial sleep deprivation, contradictory to BRS. Both markers showed a decrease in parasympathetic activity, known as detrimental to cardiovascular health.

Effect of Blood Volume Shift Simulated via Head-up Tilt on Photoplethysmography Morphology

PPG can provide information on cardiovascular responses to fluid shifts from upper to lower part of body under the condition of orthostatic stress. The current study investigated ability of PPG derived LVET and other PPG derived features to identify progressive central hypovolemia induced by head up tilt (HUT) and evaluated potential use of LVET as early noninvasive indicator of blood loss. Continuous finger PPG, blood pressure, and electrocardiography were recorded simultaneously during 5-minutes of baseline and HUT of 20°, 40°, and 60° from 15 participants (age: 26.5 ± 3 years; height: 177 ± 8 cm; weight: 72 ± 10 kg, mean ± SD). Beat-by-beat pulse rate (PR), systolic amplitude (SA), systolic time (ST), diastolic time (DT), and PP Interval (PPI) and Ratio of pulse rate over systolic amplitude (PR/SA) were derived for each stage. LVET was derived from each stage. Friedman test followed by post-hoc analysis using Tukey-HSD was conducted to highlight the significance of changes induced by HUT. Application of 60° HUT (i.e. moderate category simulated hypovolemia) resulted in a significant change in PR (80±3 bpm vs 68±3 bpm, p=0.0008), DT (264±7 ms vs 303±4 ms, p=0.0008), ST (110±6 ms vs 117±7 ms, p=0.02), PP interval (764±39 ms vs 869±25 ms, p=0.0045), PR/SA (112±16 vs 82±21, p=0.012) , SA (0.875± 0.2 vs 1.69±0.6, p=0.012) and LVET(292 vs 351ms,p=0.0008) compared to baseline. LVET has a strong association with the change in central blood volume and may be used as a sensitive early marker of progressive hypovolemia. The findings of the study support the hypothesis of differentiating simulated hypovolemia based on PPG alone. Keywords: Hypovolemia, HUT, LVET.

Assessing cognitive load in adolescent and adult students using photoplethysmogram morphometrics

Compared to cardiac parameters and skin conductivities, the photoplethysmogram (PPG) recorded at fingertips and other parts near to peripheral nerve ends have been recently revealed to be yet another sensitive measure for cognitive load assessment. However, there is so far no research on measuring adolescents' cognitive load using physiological signals. A comprehensive study on the effects of PPG morphometrics over a cohort covering both adolescent and adult students is also absent. In this study, we analyze the morphological features of PPG on cognitive load assessment and compare them between adolescent and adult students. Experiments on two-level arithmetic tasks show that the PPG morphometrics reached the same level of significance on the effect of task difficulty/period as heart rate, and different morphological behaviors were also shown between adolescent and adult students during the cognitive task effects, which may imply their physiological differences across age. Physiological signals recorded by wearable devices are also found to be effective in measuring cognitive load.

Design of a non-invasive pulse rate controlled deep vein thrombosis prophylaxis lower limb device

Patients with lower limb dysfunctions have a risk of developing deep vein thrombosis (DVT) symptoms if they are in a sitting posture for a long duration. In addition, unconscious patients undergoing a long hour surgery are also prone to DVT problems which further complicates the health of the patient under treatment. A prototype design in the form of an assistive and portable device to overcome deep vein thrombosis (DVT) is developed for surgical and non-surgical applications. The portable device facilitates the movement of the lower limb around the ankle to promote blood flow and overcome DVT problem. The device is designed using a pair of actuators that translates the linear motion to axial flexion and extension movement of the ankle. The ankle movement is synchronized with the patient's heartbeats to promote blood flow and complete the venous movement. In addition, an electrically driven intermittent pneumatic compression layer is wrapped around the calf muscle to further enhance the blood flow in the lower limb. The integrated device is lightweight and portable which can be issued by the hospital centers to the patients for domestic utilization.

Innovative Multi-Site Photoplethysmography Analysis for Quantifying Pulse Amplitude and Timing Variability Characteristics in Peripheral Arterial Disease

Photoplethysmography (PPG) is a simple-to-perform vascular optics measurement technique that can detect blood volume changes in the microvascular bed of tissue. Beat-to-beat analysis of the PPG waveform enables the study of the variability of pulse features, such as the amplitude and the pulse arrival time (PAT), and when quantified in the time and frequency domains, has considerable potential to shed light on perfusion changes associated with peripheral arterial disease (PAD). In this pilot study, innovative multi-site bilateral finger and toe PPG recordings from 43 healthy control subjects and 31 PAD subjects were compared (recordings each at least five minutes, collected in a warm temperature-controlled room). Beat-to-beat normalized amplitude variability and PAT variability were then quantified in the time-domain using two simple statistical measures and in the frequency-domain bilaterally using magnitude squared coherence (MSC). Significantly reduced normalized amplitude variability (healthy control 0.0384 (interquartile range 0.0217–0.0744) vs. PAD 0.0160 (0.0080–0.0338) (p < 0.0001)) and significantly increased PAT variability (healthy control 0.0063 (0.0052–0.0086) vs. PAD 0.0093 (0.0078–0.0144) (p < 0.0001)) was demonstrated for the toe site in PAD using the time-domain analysis. Frequency-domain analysis demonstrated significantly lower MSC values across a range of frequency bands for PAD patients. These changes suggest a loss of right-to-left body side coherence and cardiovascular control in PAD. This study has also demonstrated the feasibility of using these measurement and analysis methods in studies investigating multi-site PPG variability for a wide range of cardiac and vascular patient groups.

A review on wearable photoplethysmography sensors and their potential future applications in health care

Photoplethysmography (PPG) is an uncomplicated and inexpensive optical measurement method that is often used for heart rate monitoring purposes. PPG is a non-invasive technology that uses a light source and a photodetector at the surface of skin to measure the volumetric variations of blood circulation. Recently, there has been much interest from numerous researchers around the globe to extract further valuable information from the PPG signal in addition to heart rate estimation and pulse oxymetry readings. PPG signal’s second derivative wave contains important health-related information. Thus, analysis of this waveform can help researchers and clinicians to evaluate various cardiovascular-related diseases such as atherosclerosis and arterial stiffness. Moreover, investigating the second derivative wave of PPG signal can also assist in early detection and diagnosis of various cardiovascular illnesses that may possibly appear later in life. For early recognition and analysis of such illnesses, continuous and real-time monitoring is an important approach that has been enabled by the latest technological advances in sensor technology and wireless communications. The aim of this article is to briefly consider some of the current developments and challenges of wearable PPG-based monitoring technologies and then to discuss some of the potential applications of this technology in clinical settings.

Cuffless blood pressure estimation using only a smartphone

Cuffless blood pressure (BP) measurement is an all-inclusive term for a method that aims to measure BP without using a cuff. Recent cuffless technology has made it possible to estimate BP with reasonable accuracy. However, mainstream methods require an electrocardiogram and photoplethysmogram measurements, and frequent calibration procedures using a cuff sphygmomanometer. We therefore developed a far simpler cuffless method, using only heart rate (HR) and modified normalized pulse volume (mNPV) that can be measured using a smartphone, based on the knowledge that ln BP = ln cardiac output (CO) + ln total peripheral resistance (TPR), where CO and TPR are correlated with HR and mNPV, respectively. Here, we show that mean arterial pressure (MAP), systolic BP (SBP), and diastolic BP (DBP) could be estimated using the exponential transformation of linear polynomial equation, (a × ln HR) + (b × ln mNPV) + constant, using only a smartphone, with an accuracy of R > 0.70. This implies that our cuffless method could convert a large number of smartphones or smart watches into simplified sphygmomanometers.

Photoplethysmography: Towards a non-invasive pressure measurement technique

There is a need for non-invasive and continuous blood pressure measurements. This study explored the relationship between Photoplethysmography (PPG) and Pressure-Volume (P-V) changes in an in vitro model. We proposed and compared methods for an estimation of the pulsatile volume, termed as Normalized Pulse Volume (NPV) and Adjusted Pulse Volume (APV). To validate the methods, pressure, Red (R) and InfraRed (IR) PPG signals were recorded continuously in an arterial model utilizing a pulsatile pump. Flow rates were controlled by varying pumping frequencies at low and high stroke volumes. It was found that the optimum method for estimation of the pulsatile volume is through APV, which had a high correlation (r²=0.99, p<;0.001) with the assumed exponential P-V model. APV obtained a significantly better fit when compared to NPV_IR (r²=0.73, z=25.85, p<;0.001) and NPV_R (r²=0.95, z=12.26, p<;0.001). These preliminary findings suggest that APV could be used as a potential non-invasive continuous method of blood pressure measurement.

RheoStim: Development of an Adaptive Multi-Sensor to Prevent Venous Stasis

Chronic venous insufficiency of the lower limbs is often underestimated and, in the absence of therapy, results in increasingly severe complications, including therapy-resistant tissue defects. Therefore, early diagnosis and adequate therapy is of particular importance. External counter pulsation (ECP) therapy is a method used to assist the venous system. The main principle of ECP is to squeeze the inner leg vessels by muscle contractions, which are evoked by functional electrical stimulation. A new adaptive trigger method is proposed, which improves and supplements the current therapeutic options by means of pulse synchronous electro-stimulation of the muscle pump. For this purpose, blood flow is determined by multi-sensor plethysmography. The hardware design and signal processing of this novel multi-sensor plethysmography device are introduced. The merged signal is used to determine the phase of the cardiac cycle, to ensure stimulation of the muscle pump during the filling phase of the heart. The pulse detection of the system is validated against a gold standard and provides a sensitivity of 98% and a false-negative rate of 2% after physical exertion. Furthermore, flow enhancement of the system has been validated by duplex ultrasonography. The results show a highly increased blood flow in the popliteal vein at the knee.

Arteries Stiffen With Age, but Can Retain an Ability to Become More Elastic With Applied External Cuff Pressure

It is accepted that arterial compliance decreases with age, with changes in the arterial pulse shape measured at the periphery. The aim of this study was to determine the relationship between arterial transmural pressure changes and changes in peripheral finger pulse shape characteristics for both older and younger subjects.Finger photoplethysmographic pulses were recorded noninvasively from the right index fingers of 100 healthy normotensive subjects. Their median age was 43 years (range 20-71 years) allowing two distinct age groups to be compared (older group ≥45 and younger group < 45 years). Arterial transmural pressures on the whole right arm were reduced with a 50 cm long cuff inflated to 10, 20, 30, and 40 mmHg. Pulse maximum amplitude and rise time were calculated for each age group, and for each cuff pressure level.Gradual and significant decreases in both pulse maximum amplitude and rise time were found with increasing cuff pressure for both age groups. With an external cuff pressure of 40 mmHg, there was an average maximum amplitude and rise time decrease of 27.1% (P < 0.001) and 7.5% (P < 0.001) respectively. The changes in the older group were significantly greater than those in the younger group for maximum amplitude (30.3% vs 24.4%, P = 0.006), but not for rise time (8.0% vs 6.7%, P = 0.23).Our results show that arterial compliance of the arm artery increases with reduced transmural pressure for both older and younger groups, and demonstrate that the aged arm artery can become more elastic with applied external cuff pressure.

On the analysis of fingertip photoplethysmogram signals

Photoplethysmography (PPG) is used to estimate the skin blood flow using infrared light. Researchers from different domains of science have become increasingly interested in PPG because of its advantages as non-invasive, inexpensive, and convenient diagnostic tool. Traditionally, it measures the oxygen saturation, blood pressure, cardiac output, and for assessing autonomic functions. Moreover, PPG is a promising technique for early screening of various atherosclerotic pathologies and could be helpful for regular GP-assessment but a full understanding of the diagnostic value of the different features is still lacking. Recent studies emphasise the potential information embedded in the PPG waveform signal and it deserves further attention for its possible applications beyond pulse oximetry and heart-rate calculation. Therefore, this overview discusses different types of artifact added to PPG signal, characteristic features of PPG waveform, and existing indexes to evaluate for diagnoses.

Continuous and noninvasive measurement of systolic and diastolic blood pressure by one mathematical model with the same model parameters and two separate pulse wave velocities

There is keen interest in continuous and noninvasive blood pressure (BP) measurement. However, many technologies have a shortcoming of complex mechanical structure. In our study, two arterial pulses are acquired by photoplethysmography (PPG) at ear and toe in order to explore a new method of measuring BP by pulse wave velocity (PWV). We previously validated and reported a BP-PWV mathematical model with measurements from humans with no evidence of cardiovascular disease, but were only able to determine PWV related to diastolic blood pressure (DBP). In this paper, we propose methods of identifying pulse transmit time (PTT) in low, normal and high systolic blood pressure (SBP) conditions. By averaging the PTT's of incident wave and reflected wave for non-systematic error reduction, we obtain a PWV that is suitable for estimating SBP. SBP and DBP are estimated by two separate PWV's based on the previously calibrated models. Experimental measurements are conducted on 26 subjects (age 19 ± 1 and 60 ± 1) with no evidence of cardiovascular disease. The measurement errors (Mean Deviation = 2.16 mmHg (SBP) and 1.49 mmHg (DBP); Standard Deviation = 6.23 mmHg (SBP) and 6.51 mmHg (DBP)) satisfy the accuracy criteria of Association for the Advancement of Medical Instrumentation. The results verify that SBP and DBP can be estimated by one mathematical model with the same model parameters and two separate PWV's.

Evaluation scale to assess the accuracy of cuff-less blood pressure measuring devices

OBJECTIVE

The call for early detection of hypertension and cardiac events creates a heavy demand for devices that can be used for blood pressure (BP) monitoring at home and in ambulatory settings. An emerging type of BP monitors without an occluding cuff has drawn great attentions for this application because it is comfortable and capable of providing continuous readings. For the development the cuff-less devices, it is crucial for the clinicians and engineers to joint efforts in establishing an evaluation standard.

METHODS

This study attempts to contribute to its initiation in two ways. First, a new distribution model for measurement differences between the test device and the reference was proposed. We verified the model using evaluation results from 40 devices, of which 80% of the American Association for the Advancement of Medical Instrumentation and British Hypertension Society reporting results were in agreement, as compared with 50%, if the original normal model was used. We further tested a cuff-less device on 85 patients for 999 datasets and found that the differences between the proposed distribution and that of the device were nonsignificant for systolic BP measurements (Kolmogorov-Smirnov = 0.036, P = 0.15). Second, some evaluation scales were studied for their capability to assess the accuracy of cuff-less devices. For mean absolute difference, a map was developed to relate it with the criteria of American Association for the Advancement of Medical Instrumentation, British Hypertension Society, and European Society of Hypertension protocols, on the basis of the proposed distribution model; for mean absolute percentage difference, it is prominent in evaluating devices that have measurement errors often increasing with BP, which is an issue has not been fully explored in existing standards.

CONCLUSION

This study focused on the statistical aspect of establishing standard to assess the accuracy of cuff-less BP measuring devices. The results of our study on the validation reports of various cuff-based devices and an experimental study on a cuff-less device showed that the t4 distribution is better than the normal distribution in portraying the underlying error distribution of both kinds of devices. Moreover, based on both the theoretical and experimental studies, mean absolute difference or mean absolute percentage difference is recommended as continuous scale to assess the accuracy of cuff-less devices for their own distinctive advantages.

Towards using photo-plethysmogram amplitude to measure blood pressure during sleep

There is considerable interest in non-intrusive and reliable continuous ambulatory blood pressure measurement systems. Pulse amplitude is the peak to trough amplitude of the photo-plethysmogram signal. We compared pulse amplitude with a currently popular parameter, the pulse arrival time (PAT), for estimating continuous systolic blood pressure (SBP). Overnight sleep data from 18 young, healthy subjects (14 M 4 F, age 24+/-5 years, BMI 23.8+/-4.0 kg/m2) was analyzed. We found that pulse amplitude was more effective than PAT for estimating SBP during sleep. Mean coherence between pulse amplitude and SBP was significantly stronger than that for PAT [p<0.001, 95% CI: 0.21-0.25 (finger), 0.11-0.14 (wrist)]. Correlation between pulse amplitude and SBP was significantly stronger than that for PAT [p<0.001, 95% CI: 0.46-0.53 (finger), 0.13-0.20 (wrist)]. SBP estimation errors were significantly lower using pulse amplitude [p<0.001, 95% CI: -1.55 to -1.29 mmHg (finger), -0.53 to -0.36 mmHg (wrist)]. We also found that while pulse amplitude was closely related to SBP, the relationship weakened during and around REM sleep (ANOVA of REM, transitional Wake-REM and transitional REM-Sleep versus other sleep states: F=24.7, p<0.001). These results suggest that pulse amplitude is potentially a more suitable measure than pulse arrival time for estimating continuous blood pressure.

Photoplethysmography, an Easy and Accurate Method for Measuring Ankle Brachial Pressure Index: Can Photoplethysmography Replace Doppler?

Objective: To assess the accuracy of ankle brachial pressure index (ABPI) assessed by photoplethysmography (PPG) compared with continuous wave Doppler (CW-Doppler). Methods: Ankle brachial pressure index was measured in a standard manner using both PPG and Doppler probes. For PPG-ABPI, a PPG probe was placed on the index finger and great toe, and a microcomputer determined the ABPI. These values were compared with the ABPI measured manually using an 8-MHz Doppler probe. Correlation and agreement between PPG and Doppler ABPI were assessed by Lin’s correlation coefficient and Bland—Altman plots. Results: In all, 133 claudicants were assessed. There was a strong correlation between the 2 ABPI methods (β = .79 and 95% limits of agreement of —0.23 to 0.24). Conclusion: Measuring ABPI automatically using the PPG technique is an effective alternative for Doppler ABPI. PPG-ABPI is completely objective, fast, and accurate.

Continuous and noninvasive blood pressure measurement: a novel modeling methodology of the relationship between blood pressure and pulse wave velocity

In this paper, we aim to establish a new mathematical model that relates pulse wave velocity (PWV) to blood pressure (BP) for continuous and noninvasive BP measurement. For the first time, we derive an ordinary differential equation (ODE) expressing the fundamental relation between BP, elastic modulus G and PWV. The general solution of this ODE is the mathematical BP-PWV model. In our model, the elastic modulus G is included in model parameters, unlike the existing theoretical models. This enables us to express the BP-PWV relationship for subjects of different ages and genders. A family of BP-PWV functions for specific age and gender groups can be obtained using statistical methods based on clinical trial data, which serve as the calibrated benchmark models for continuous and noninvasive BP measurement. To illustrate the modeling methodology, we construct benchmark models for people aged 19 and 60 and apply them to continuous diastolic blood pressure (DBP) measurement without individual calibration. The results of clinical tests meet the test standard in ANSI/AAMI SP10, which attests the feasibility of the modeling methodology.