Pulse wave carries comprehensive information regarding the human cardiovascular system (CS), which is essential for directly capturing CS parameters. More importantly, cuffless blood pressure (BP) is one of the most critical markers in CS. Accurately measuring BP via the pulse wave for continuous and noninvasive diagnosis of a disease associated with hypertension remains a challenge and highly desirable. Here, a flexible weaving constructed selfpowered pressure sensor (WCSPS) is reported for measurement of the pulse wave and BP in a noninvasive manner. The WCSPS holds an ultrasensitivity of 45.7 mV Pa−1 with an ultrafast response time of less than 5 ms, and no performance degradation is observed after up to 40 000 motion cycles. Furthermore, a low power consumption sensor system is developed for precisely monitoring pulse wave from the fingertip, wrist, ear, and ankles. A practical measurement is performed with 100 people with ages spanning from 24 to 82 years and different health statuses. The discrepancy between the measured BP results using the WCSPS and that provided by the commercial cuff-based device is about 0.87–3.65%. This work demonstrates an efficient and cost-effective way for human health monitoring, which would be a competitive alternative to current complex cardiovascular monitoring systems.

Flexible Weaving Constructed Self-Powered Pressure Sensor Enabling Continuous Diagnosis of Cardiovascular Disease and Measurement of Cuffless Blood Pressure

High blood pressure (BP) is a major cardiovascular risk factor that is treatable, yet hypertension awareness and control rates are low. Ubiquitous BP monitoring technology could improve hypertension management, but existing devices require an inflatable cuff and are not compatible with such anytime, anywhere measurement of BP. We extended the oscillometric principle, which is used by most automatic cuff devices, to develop a cuff-less BP monitoring device using a smartphone. As the user presses her/his finger against the smartphone, the external pressure of the underlying artery is steadily increased while the phone measures the applied pressure and resulting variable-amplitude blood volume oscillations. A smartphone application provides visual feedback to guide the amount of pressure applied over time via the finger pressing and computes systolic and diastolic BP from the measurements. We prospectively tested the smartphone-based device for real-time BP monitoring in human subjects to evaluate usability (n = 30) and accuracy against a standard automatic cuff-based device (n = 32). We likewise tested a finger cuff device, which uses the volume-clamp method of BP detection. About 90% of the users learned the finger actuation required by the smartphone-based device after one or two practice trials. The device yielded bias and precision errors of 3.3 and 8.8 mmHg for systolic BP and -5.6 and 7.7 mmHg for diastolic BP over a 40 to 50 mmHg range of BP. These errors were comparable to the finger cuff device. Cuff-less and calibration-free monitoring of systolic and diastolic BP may be feasible via a smartphone.

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Smartphone-based blood pressure monitoring via the oscillometric finger-pressing method

The year 2016 marks the 200th birth anniversary of Carl Friedrich Wilhelm Ludwig (1816–1895). As one of the most remarkable scientists, Ludwig invented the kymograph, which for the first time enabled the recording of continuous blood pressure (BP), opening the door to the modern study of physiology. Almost a century later, intraarterial BP monitoring through an arterial line has been used clinically. Subsequently, arterial tonometry and volume clamp method were developed and applied in continuous BP measurement in a noninvasive way. In the last two decades, additional efforts have been made to transform the method of unobtrusive continuous BP monitoring without the use of a cuff. This review summarizes the key milestones in continuous BP measurement; that is, kymograph, intraarterial BP monitoring, arterial tonometry, volume clamp method, and cuffless BP technologies. Our emphasis is on recent studies of unobtrusive BP measurements as well as on challenges and future directions.

/pdf/continuous-blood-pressure-measurement-from-invasive-to-4in9xkn5ai.pdf

Continuous Blood Pressure Measurement From Invasive to Unobtrusive: Celebration of 200th Birth Anniversary of Carl Ludwig

Background: Blood pressure (BP) measurements have been used widely in clinical and private environments. Recently, the use of ECG monitors has proliferated; however, they are not enabled with BP estimation. We have developed a method for BP estimation using only electrocardiogram (ECG) signals. Methods: Raw ECG data are filtered and segmented, and, following this, a complexity analysis is performed for feature extraction. Then, a machine-learning method is applied, combining a stacking-based classification module and a regression module for building systolic BP (SBP), diastolic BP (DBP), and mean arterial pressure (MAP) predictive models. In addition, the method allows a probability distribution-based calibration to adapt the models to a particular user. Results: Using ECG recordings from 51 different subjects, 3129 30-s ECG segments are constructed, and seven features are extracted. Using a train-validation-test evaluation, the method achieves a mean absolute error (MAE) of 8.64 mmHg for SBP, 18.20 mmHg for DBP, and 13.52 mmHg for the MAP prediction. When models are calibrated, the MAE decreases to 7.72 mmHg for SBP, 9.45 mmHg for DBP and 8.13 mmHg for MAP. Conclusion: The experimental results indicate that, when a probability distribution-based calibration is used, the proposed method can achieve results close to those of a certified medical device for BP estimation.

https://www.mdpi.com/1424-8220/18/4/1160/pdf

Non-Invasive Blood Pressure Estimation from ECG Using Machine Learning Techniques

Objective: To demonstrate the feasibility of everaging impedance plethysmography (IPG) for detection of pulse transit time (PTT) and estimation of blood pressure (BP). Methods: We first established the relationship between BP, PTT, and arterial impedance ( i.e. , the IPG observations). The IPG sensor was placed on the wrist while the photoplethysmography sensor was attached to the index finger to measure the PTT. With a cuff-based BP monitoring system placed on the upper arm as a reference, our proposed methodology was evaluated on 15 young, healthy human subjects leveraging handgrip exercises to manipulate BP/PTT and compared to several conventional PTT models to assess the efficacy of PTT/BP detections. Results: The proposed model correlated with BP fairly well with group average correlation coefficients of ${\text{0.88}}\pm {\text{0.07}}$ for systolic BP (SBP) and ${\text{0.88}}\pm {\text{0.06}}$ for diastolic BP (DBP). In comparison with the other PTT methods, PTT-IPG-based BP estimation provided a lower root-mean-squared-error of ${\text{8.47}}\pm {\text{0.91}}\,{\text{mmHg}}$ and ${\text{5.02}}\pm {\text{0.73}}\,{\text{mmHg}}$ for SBP and DBP, respectively. Conclusion: We conclude that the measurement of arterial impedance via IPG methods is an adequate indicator to estimate BP. The proposed method appears to offer superiority compared to the conventional PTT estimation approaches. Significance: Using impedance magnitude to estimate PTT offers promise to realize wearable and cuffless BP devices.

Noninvasive Cuffless Blood Pressure Estimation Using Pulse Transit Time and Impedance Plethysmography

This work details noninvasive arterial blood pressure (ABP) waveform estimation based on an arterial vessel cross-sectional area measurement combined with an elasticity measurement of the vessel, represented by pulse wave velocity (PWV), using a two-element ultrasound system. The overall ABP waveform estimation is validated in a custom-designed experimental setup mimicking the heart and an arterial vessel segment with two single element transducers, assuming a constant hemodynamic system. The estimation of local PWV using the flow-area method produces unbiased elasticity estimation of the tube in a pressure waveform comparison. The measured PWV using 16 cardiac cycles of data is 8.47 + 0.63 m/s with an associated scaling error of −1.56 + 14.0% in a direct pressure waveform comparison, showing negligible bias error on average. The distension waveform obtained from a complex cross-correlation model estimator (C3M) reliably traces small pressure changes reflected by the diameter change. The excellent agreement of an estimated pressure waveform to the reference pressure waveform suggests the promising potential of a readily available, inexpensive, and portable ABP waveform monitoring device.

Noninvasive arterial blood pressure waveform monitoring using two- element ultrasound system

This work presents a non-invasive arterial blood pressure (ABP) waveform monitoring technique using ultrasound. A portable ultrasound system to excite ultrasound transducers and acquire data is designed with off-the-shelf components. The insonation angles are identified using a vector Doppler technique based on the cosine dependency of the Doppler signals. The pulse pressure of an estimated waveform at the left common carotid artery is compared to the standard sphygmomanometer measurement in a clinical test. The estimated carotid ABP waveform shows excellent agreement to the finger ABP waveform with expected discrepancy of the systolic peak shape due to different measurement sites. The proposed method also tracks slow blood pressure fluctuations. This validation on human subjects shows potential for a noninvasive blood pressure waveform monitoring device at central arterial sites.

Carotid arterial blood pressure waveform monitoring using a portable ultrasound system

This paper details unfocused imaging using single-element ultrasound transducers for motion tolerant arterial blood pressure (ABP) waveform estimation. The ABP waveform is estimated based on pulse wave velocity and arterial pulsation through Doppler and M-mode ultrasound. This paper discusses approaches to mitigate the effect of increased clutter due to unfocused imaging on blood flow and diameter waveform estimation. An intensity reduction model (IRM) estimator is described to track the change of diameter, which outperforms a complex cross-correlation model (C3M) estimator in low contrast environments. An adaptive clutter filtering approach is also presented, which reduces the increased Doppler angle estimation error due to unfocused imaging. Experimental results in a flow phantom demonstrate that flow velocity and diameter waveforms can be reliably measured with wide lateral offsets of the transducer position. The distension waveform estimated from human carotid M-mode imaging using the IRM estimator shows physiological baseline fluctuations and 0.6-mm pulsatile diameter change on average, which is within the expected physiological range. These results show the feasibility of this low cost and portable ABP waveform estimation device.

Motion Tolerant Unfocused Imaging of Physiological Waveforms for Blood Pressure Waveform Estimation Using Ultrasound

We compare the dynamic Bayesian network and k-nearest neighbor-based predictors for the occurrence of acute hypotensive episodes (AHE) with respect to various data conditions (size, class balance ratio) and problem definition settings (lag, lead time). From our dataset extracted from the large ICU physiological waveform repository of MIMIC2 database, we find that both models are effective for predicting AHE and their performances improve with increasing training dataset size. We also empirically demonstrate that the nearest neighbor method has a better performance for larger datasets in terms of both prediction result and computational time, but it severely degrades for class imbalanced data while the Bayesian network remains robust.

Large-Scale Methodological Comparison of Acute Hypotensive Episode Forecasting Using MIMIC2 Physiological Waveforms

This work presents non-invasive evaluation of the arterial blood pressure (ABP) waveform during the Valsalva maneuver. Ultrasound scanning is conducted to acquire blood flow and arterial distension signals. Motion-tolerant ultrasound measurement schemes are employed by using two wide rectangular transducers. Pulse pressure (PP) estimated at the common carotid artery is compared to that of a finger waveform measured by a volume clamping device. The changes of PP are correlated between the two measurements. A more depressed dicrotic notch during the Valsalva strain is observed, and beat-to-beat variations of PP and a pulse rate caused by respiration and baroreflex is observed during the control. This validation suggests novel opportunities to investigate the pathophysiology of cardiovascular diseases through the noninvasive ABP waveform monitoring during the stress test.

Joohyun Seo

Papers

Noninvasive arterial blood pressure waveform monitoring using two- element ultrasound system

Carotid arterial blood pressure waveform monitoring using a portable ultrasound system

Motion Tolerant Unfocused Imaging of Physiological Waveforms for Blood Pressure Waveform Estimation Using Ultrasound

Large-Scale Methodological Comparison of Acute Hypotensive Episode Forecasting Using MIMIC2 Physiological Waveforms

Monitoring of Pulse Pressure and Arterial Pressure Waveform Changes during the Valsalva Maneuver by a Portable Ultrasound System