A Novel Method for Continuous, Noninvasive, Cuff-Less Measurement of Blood Pressure: Evaluation in Patients With Nonalcoholic Fatty Liver Disease

A prototype photoplethysmography-based cuffless device shows promising results in tracking changes in blood pressure

Introduction

Non-invasive cuffless blood pressure devices have shown promising results in accurately estimating blood pressure when comparing measurements at rest. However, none of commercially available or prototype cuffless devices have yet been validated according to the appropriate standards. The aim of the present study was to bridge this gap and evaluate the ability of a prototype cuffless device, developed by Aidee Health AS, to track changes in blood pressure compared to a non-invasive, continuous blood pressure monitor (Human NIBP or Nexfin) in a laboratory set up. The performance was evaluated according to the metrics and statistical methodology described in the ISO 81060-3:2022 standard. However, the present study is not a validation study and thus the study was not conducted according to the ISO 81060-3:2022 protocol, e.g., non-invasive reference and distribution of age not fulfilled.

Method

Data were sampled continuously, beat-to-beat, from both the cuffless and the reference device. The cuffless device was calibrated once using the reference BP measurement. Three different techniques (isometric exercise, mental stress, and cold pressor test) were used to induce blood pressure changes in 38 healthy adults.

Results

The mean difference (standard deviation) was 0.3 (8.7) mmHg for systolic blood pressure, 0.04 (6.6) mmHg for diastolic blood pressure, and 0.8 (7.9) mmHg for mean arterial pressure, meeting the Accuracy requirement of ISO 81060-3:2022 (≤6.0 (10.0) mmHg). The corresponding results for the Stability criteria were 1.9 (9.2) mmHg, 2.9 (8.1) mmHg and 2.5 (9.5) mmHg. The acceptance criteria for the Change requirement were achieved for the 85th percentile of ≤50% error for diastolic blood pressure and mean arterial pressure but were higher than the limit for systolic blood pressure (56% vs. ≤50%) and for all parameters for the 50th percentile (32%-39% vs. ≤25%).

Conclusions

The present study demonstrated that the cuffless device could track blood pressure changes in healthy adults across different activities and showed promising results in achieving the acceptance criteria from ISO 81060-3:2022.

A Novel Photo-electro-mechano Sensing Array for the Visualization and Estimation of Tonoarteriogram

Existing cuffless blood pressure (BP) monitoring technologies commonly rely on single-site measurements with unimodal sensor configurations, thereby constraining the precision and visualization of the two-dimensional data. Building upon our previous observations regarding the significant influence of measurement sites on BP evaluation, and leveraging the widely acknowledged utility of electrocardiography (ECG) in BP assessment, in this study, we develop a multimodal photo-electro-mechano tonoarteriographic (TAG) imaging system, enabling continuous visualization of local BP variation and estimation of central BP. The system integrates a 3×3 photoplethysmography (PPG) sensor array, one-lead ECG, and a 2×2 pressure sensor array, allowing to collect simultaneously 15 channel physiological signals. The proposed system was tested with 20 subjects and the experimental results reveal noticeable variations in local pulse transit time (PTT)/BP across different anatomical structures at the measurement site. To further improve the system performance, we designed and tested a flexible 2×4 ultrasound sensor array and demonstrated its feasibility to augment the system's capability for central BP estimation. In summary, the proposed system can not only estimate continuously central BP but also visualize the two-dimensional local BP/PTT variation at the measurement site, holding potential to support clinical decision-making and offering geographic-dependent information for micro-circulation investigations.

Accuracy and User Acceptability of 24-hour Ambulatory Blood Pressure Monitoring by a Prototype Cuffless Multi-Sensor Device Compared to a Conventional Oscillometric Device

OBJECTIVE

24-hour ambulatory blood pressure monitoring (24ABPM) is state of the art in out-of-office blood pressure (BP) monitoring. Due to discomfort and technical limitations related to cuff-based 24ABPM devices, methods for non-invasive and continuous estimation of BP without the need for a cuff have gained interest. The main aims of the present study were to compare accuracy of a pulse arrival time (PAT) based BP-model and user acceptability of a prototype cuffless multi-sensor device (cuffless device), developed by Aidee Health AS, with a conventional cuff-based oscillometric device (ReferenceBP) during 24ABPM.

METHODS

Ninety-five normotensive and hypertensive adults underwent simultaneous 24ABPM with the cuffless device on the chest and a conventional cuff-based oscillometric device on the non-dominant arm. PAT was calculated using the electrocardiogram (ECG) and photoplethysmography (PPG) sensors incorporated in the chest-worn device. The cuffless device recorded continuously, while ReferenceBP measurements were taken every 20 minutes during daytime and every 30 minutes during nighttime. Two-minute PAT-based BP predictions corresponding to the ReferenceBP measurements were compared with ReferenceBP measurements using paired t-tests, bias, and limits of agreement.

RESULTS

Mean (SD) of ReferenceBP compared to PAT-based daytime and nighttime systolic BP (SBP) were 129.7 (13.8) mmHg versus 133.6 (20.9) mmHg and 113.1 (16.5) mmHg versus 131.9 (23.4) mmHg. Ninety-five % limits of agreements were [-26.7, 34.6 mmHg] and [-20.9, 58.4 mmHg] for daytime and nighttime SBP respectively. The cuffless device was reported to be significantly more comfortable and less disturbing than the ReferenceBP device during 24ABPM.

CONCLUSIONS

In the present study, we demonstrated that a general PAT-based BP model had unsatisfactory agreement with ambulatory BP during 24ABPM, especially during nighttime. If sufficient accuracy can be achieved, cuffless BP devices have promising potential for clinical assessment of BP due to the opportunities provided by continuous BP measurements during real-life conditions and high user acceptability.

Central Aortic Blood Pressure Waveform Estimation with a Temporal Convolutional Network

A novel temporal convolutional network (TCN) model is utilized to reconstruct the central aortic blood pressure (aBP) waveform from the radial blood pressure waveform. The method does not need manual feature extraction as traditional transfer function approaches. The data acquired by the SphygmoCor CVMS device in 1,032 participants as a measured database and a public database of 4,374 virtual healthy subjects were used to compare the accuracy and computational cost of the TCN model with the published convolutional neural network and bi-directional long short-term memory (CNN-BiLSTM) model. The TCN model was compared with CNN-BiLSTM in the root mean square error (RMSE). The TCN model generally outperformed the existing CNN-BiLSTM model in terms of accuracy and computational cost. For the measured and public databases, the RMSE of the waveform using the TCN model was 0.55 ± 0.40 mmHg and 0.84 ± 0.29 mmHg, respectively. The training time of the TCN model was 9.63 min and 25.51 min for the entire training set; the average test time was around 1.79 ms and 8.58 ms per test pulse signal from the measured and public databases, respectively. The TCN model is accurate and fast for processing long input signals, and provides a novel method for measuring the aBP waveform. This method may contribute to the early monitoring and prevention of cardiovascular disease.

Accuracy of non-invasive cuffless blood pressure in the intensive care unit: Promises and challenges

Objective

Continuous non-invasive cuffless blood pressure (BP) monitoring may reduce adverse outcomes in hospitalized patients if accuracy is approved. We aimed to investigate accuracy of two different BP prediction models in critically ill intensive care unit (ICU) patients, using a prototype cuffless BP device based on electrocardiogram and photoplethysmography signals. We compared a pulse arrival time (PAT)-based BP model (generalized PAT-based model) derived from a general population cohort to more complex and individualized models (complex individualized models) utilizing other features of the BP sensor signals.

Methods

Patients admitted to an ICU with indication of invasive BP monitoring were included. The first half of each patient's data was used to train a subject-specific machine learning model (complex individualized models). The second half was used to estimate BP and test accuracy of both the generalized PAT-based model and the complex individualized models. A total of 7,327 measurements of 15 s epochs were included in pairwise comparisons across 25 patients.

Results

The generalized PAT-based model achieved a mean absolute error (SD of errors) of 7.6 (7.2) mmHg, 3.3 (3.1) mmHg and 4.6 (4.4) mmHg for systolic BP, diastolic BP and mean arterial pressure (MAP) respectively. Corresponding results for the complex individualized model were 6.5 (6.7) mmHg, 3.1 (3.0) mmHg and 4.0 (4.0) mmHg. Percentage of absolute errors within 10 mmHg for the generalized model were 77.6, 96.2, and 89.6% for systolic BP, diastolic BP and MAP, respectively. Corresponding results for the individualized model were 83.8, 96.2, and 94.2%. Accuracy was significantly improved when comparing the complex individualized models to the generalized PAT-based model in systolic BP and MAP, but not diastolic BP.

Conclusion

A generalized PAT-based model, developed from a different population was not able to accurately track BP changes in critically ill ICU patients. Individually fitted models utilizing other cuffless BP sensor signals significantly improved accuracy, indicating that cuffless BP can be measured non-invasively, but the challenge toward generalizable models remains for future research to resolve.

Blood Pressure Response and Pulse Arrival Time During Exercise Testing in Well-Trained Individuals

Introduction: There is a lack of data describing the blood pressure response (BPR) in well-trained individuals. In addition, continuous bio-signal measurements are increasingly investigated to overcome the limitations of intermittent cuff-based BP measurements during exercise testing. Thus, the present study aimed to assess the BPR in well-trained individuals during a cycle ergometer test with a particular focus on the systolic BP (SBP) and to investigate pulse arrival time (PAT) as a continuous surrogate for SBP during exercise testing.

Materials and Methods: Eighteen well-trained male cyclists were included (32.4 ± 9.4 years; maximal oxygen uptake 63 ± 10 ml/min/kg) and performed a stepwise lactate threshold test with 5-minute stages, followed by a continuous test to voluntary exhaustion with 1-min increments when cycling on an ergometer. BP was measured with a standard automated exercise BP cuff. PAT was measured continuously with a non-invasive physiological measurements device (IsenseU) and metabolic consumption was measured continuously during both tests.

Results: At lactate threshold (281 ± 56 W) and maximal intensity test (403 ± 61 W), SBP increased from resting values of 136 ± 9 mmHg to maximal values of 219 ± 21 mmHg and 231 ± 18 mmHg, respectively. Linear within-participant regression lines between PAT and SBP showed a mean r² of 0.81 ± 17.

Conclusion: In the present study focusing on the BPR in well-trained individuals, we observed a more exaggerated systolic BPR than in comparable recent studies. Future research should follow up on these findings to clarify the clinical implications of the high BPR in well-trained individuals. In addition, PAT showed strong intra-individual associations, indicating potential use as a surrogate SBP measurement during exercise testing.

Blood pressure altering method affects correlation with pulse arrival time

OBJECTIVE

Pulse arrival time (PAT) is a potential main feature in cuff-less blood pressure (BP) monitoring. However, the precise relationship between BP parameters and PAT under varying conditions lacks a complete understanding. We hypothesize that simple test protocols fail to demonstrate the complex relationship between PAT and both SBP and DBP. Therefore, this study aimed to investigate the correlation between PAT and BP during two exercise modalities with differing BP responses using an unobtrusive wearable device.

METHODS

Seventy-five subjects, of which 43.7% had a prior diagnosis of hypertension, participated in an isometric and dynamic exercise test also including seated periods of rest prior to, in between and after. PAT was measured using a prototype wearable chest belt with a one-channel electrocardiogram and a photo-plethysmography sensor. Reference BP was measured auscultatory.

RESULTS

Mean individual correlation between PAT and SBP was -0.82 ± 0.14 in the full protocol, -0.79 ± 0.27 during isometric exercise and -0.77 ± 0.19 during dynamic exercise. Corresponding correlation between PAT and DBP was 0.25 ± 0.35, -0.74 ± 0.23 and 0.39 ± 0.41.

CONCLUSION

The results confirm PAT as a potential main feature to track changes in SBP. The relationship between DBP and PAT varied between exercise modalities, with the sign of the correlation changing from negative to positive between type of exercise modality. Thus, we hypothesize that simple test protocols fail to demonstrate the complex relationship between PAT and BP with emphasis on DBP.

Noninvasive Continuous Blood Pressure Estimation from Pulse Transit Time: A review of the calibration models

Noninvasive continuous blood pressure estimation is a promising alternative to minimally invasive blood pressure measurement using cuff and invasive catheter measurement, because it opens the way to both long-term and continuous blood pressure monitoring in ecological situation. The most current estimation algorithm is based on pulse transit time measurement where at least two measured signals need to be acquired. From the pulse transit time values, it is possible to estimate the continuous blood pressure for each cardiac cycle. This measurement highly depends on arterial properties which are not easily accessible with common measurement techniques; but these properties are needed as input for the estimation algorithm. With every change of input arterial properties, the error in the blood pressure estimation rises, thus a periodic calibration procedure is needed for error minimization. Recent research is focused on simplified constant arterial properties which are not constant over time and uses only linear model based on initial measurement. The elaboration of continuous calibration procedures, independent of recalibration measurement, is the key to improving the accuracy and robustness of noninvasive continuous blood pressure estimation. However, most models in literature are based on linear approximation and we discuss here the need for more complete calibration models.

Multimodal Photoplethysmography-Based Approaches for Improved Detection of Hypertension

Elevated blood pressure (BP) is a major cause of death, yet hypertension commonly goes undetected. Owing to its nature, it is typically asymptomatic until later in its progression when the vessel or organ structure has already been compromised. Therefore, noninvasive and continuous BP measurement methods are needed to ensure appropriate diagnosis and early management before hypertension leads to irreversible complications. Photoplethysmography (PPG) is a noninvasive technology with waveform morphologies similar to that of arterial BP waveforms, therefore attracting interest regarding its usability in BP estimation. In recent years, wearable devices incorporating PPG sensors have been proposed to improve the early diagnosis and management of hypertension. Additionally, the need for improved accuracy and convenience has led to the development of devices that incorporate multiple different biosignals with PPG. Through the addition of modalities such as an electrocardiogram, a final measure of the pulse wave velocity is derived, which has been proved to be inversely correlated to BP and to yield accurate estimations. This paper reviews and summarizes recent studies within the period 2010–2019 that combined PPG with other biosignals and offers perspectives on the strengths and weaknesses of current developments to guide future advancements in BP measurement. Our literature review reveals promising measurement accuracies and we comment on the effective combinations of modalities and success of this technology.

PPG Sensor Contact Pressure Should Be Taken Into Account for Cuff-Less Blood Pressure Measurement

OBJECTIVE

Photo-plethysmography (PPG) sensors are often used to detect pulse transit time (PTT) for potential cuff-less blood pressure (BP) measurement. It is known that the contact pressure (CP) of the PPG sensor markedly alters the PPG waveform amplitude. The objective was to test the hypothesis that PTT detected via PPG sensors is likewise impacted by CP.

METHODS

A device was built to measure the time delay between ECG and finger PPG waveforms (i.e., pulse arrival time (PAT) - a popular surrogate of PTT) and the PPG sensor CP at different CP levels. These measurements and finger cuff BP were recorded while the CP was slowly varied in 17 healthy subjects.

RESULTS

Over a physiologic range of CP, the maximum deviations of PAT detected at the PPG foot and peak were 22±2 and 40±7 ms (p<0.05), which translate to ∼11 and ∼20 mmHg BP error based on the literature. The curve relating PAT detected at the PPG foot to CP was U-shaped with minimum near finger diastolic BP. A conceptual model accounting for finger artery viscoelasticity and nonlinearity explained this curve.

CONCLUSION

Since the regulatory bias error for BP measurement is limited to 5 mmHg, PPG sensor CP should be taken into account for cuff-less BP measurement via PTT.

SIGNIFICANCE

This study suggests that widely pursued PPG-based BP measurement devices including those that detect PTT should maintain the CP or include a CP measurement in the calibration equation for deriving BP.

A Survey of Healthcare Internet-of-Things (HIoT): A Clinical Perspective

In combination with current sociological trends, the maturing development of IoT devices is projected to revolutionize healthcare. A network of body-worn sensors, each with a unique ID, can collect health data that is orders-of-magnitude richer than what is available today from sporadic observations in clinical/hospital environments. When databased, analyzed, and compared against information from other individuals using data analytics, HIoT data enables the personalization and modernization of care with radical improvements in outcomes and reductions in cost. In this paper, we survey existing and emerging technologies that can enable this vision for the future of healthcare, particularly in the clinical practice of healthcare. Three main technology areas underlie the development of this field: (a) sensing, where there is an increased drive for miniaturization and power efficiency; (b) communications, where the enabling factors are ubiquitous connectivity, standardized protocols, and the wide availability of cloud infrastructure, and (c) data analytics and inference, where the availability of large amounts of data and computational resources is revolutionizing algorithms for individualizing inference and actions in health management. Throughout the paper, we use a case study to concretely illustrate the impact of these trends. We conclude our paper with a discussion of the emerging directions, open issues, and challenges.

The use of photoplethysmography for assessing hypertension

The measurement of blood pressure (BP) is critical to the treatment and management of many medical conditions. High blood pressure is associated with many chronic disease conditions, and is a major source of mortality and morbidity around the world. For outpatient care as well as general health monitoring, there is great interest in being able to accurately and frequently measure BP outside of a clinical setting, using mobile or wearable devices. One possible solution is photoplethysmography (PPG), which is most commonly used in pulse oximetry in clinical settings for measuring oxygen saturation. PPG technology is becoming more readily available, inexpensive, convenient, and easily integrated into portable devices. Recent advances include the development of smartphones and wearable devices that collect pulse oximeter signals. In this article, we review (i) the state-of-the-art and the literature related to PPG signals collected by pulse oximeters, (ii) various theoretical approaches that have been adopted in PPG BP measurement studies, and (iii) the potential of PPG measurement devices as a wearable application. Past studies on changes in PPG signals and BP are highlighted, and the correlation between PPG signals and BP are discussed. We also review the combined use of features extracted from PPG and other physiological signals in estimating BP. Although the technology is not yet mature, it is anticipated that in the near future, accurate, continuous BP measurements may be available from mobile and wearable devices given their vast potential.

How Effective Is Pulse Arrival Time for Evaluating Blood Pressure? Challenges and Recommendations from a Study Using the MIMIC Database

Cardiovascular disease (CVD) is the number one cause of non-infectious morbidity and mortality in the world. The detection, measurement, and management of high blood pressure play an essential role in the prevention and control of CVDs. However, owing to the limitations and discomfort of traditional blood pressure (BP) detection techniques, many new cuff-less blood pressure approaches have been proposed and explored. Most of these involve arterial wave propagation theory, which is based on pulse arrival time (PAT), the time interval needed for a pulse wave to travel from the heart to some distal place on the body, such as the finger or earlobe. For this study, the Medical Information Mart for Intensive Care (MIMIC) database was used as a benchmark for PAT analysis. Many researchers who use the MIMIC database make the erroneous assumption that all the signals are synchronized. Therefore, we decided to investigate the calculation of PAT intervals in the MIMIC database and check its usefulness for evaluating BP. Our findings have important implications for the future use of the MIMIC database, especially for BP evaluation.

Monitoring the Relative Blood Pressure Using a Hydraulic Bed Sensor System

We propose a nonwearable hydraulic bed sensor system that is placed underneath the mattress to estimate the relative systolic blood pressure of a subject, which only differs from the actual blood pressure by a scaling and an offset factor. Two types of features are proposed to obtain the relative blood pressure, one based on the strength and the other on the morphology of the bed sensor ballistocardiogram pulses. The relative blood pressure is related to the actual by a scale and an offset factor that can be obtained through calibration. The proposed system is able to extract the relative blood pressure more accurately with a less sophisticated sensor system compared to those from the literature. We tested the system using a dataset collected from 48 subjects right after active exercises. Comparison with the ground truth obtained from the blood pressure cuff validates the promising performance of the proposed system, where the mean correlation between the estimate and the ground truth is near to 90% for the strength feature and 83% for the morphology feature.

Toward Ubiquitous Blood Pressure Monitoring via Pulse Transit Time: Predictions on Maximum Calibration Period and Acceptable Error Limits

OBJECTIVE

Pulse transit time (PTT) is being widely pursued for ubiquitous blood pressure (BP) monitoring. PTT-based systems may require periodic cuff calibrations but can still be useful for hypertension screening by affording numerous out-of-clinic measurements that can be averaged. The objective was to predict the maximum calibration period that would not compromise accuracy and acceptable error limits in light of measurement averaging for PTT-based systems.

METHODS

Well-known mathematical models and vast BP data were leveraged. Models relating PTT, age, and gender to BP were employed to determine the maximum time period for the PTT-BP calibration curve to change by <1 mmHg over physiological BP ranges for each age and gender. A model of within-person BP variability was employed to establish the screening accuracy of the conventional cuff-based approach. These models were integrated to investigate the screening accuracy of the average of numerous measurements of a PTT-based system in relation to the accuracy of its individual measurements.

RESULTS

The maximum calibration period was about 1 year for a 30 year old and declined linearly to about 6 months for a 70 year old. A PTT-based system with a precision error of >12 mmHg for systolic BP could achieve the screening accuracy of the cuff-based approach via measurement averaging.

CONCLUSION

This theoretical study indicates that PTT-based BP monitoring is viable even with periodic calibration and seemingly high measurement errors.

SIGNIFICANCE

The predictions may help guide the implementation, evaluation, and application of PTT-based BP monitoring systems in practice.