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

Methodological Role of Mathematics to Estimate Human Blood Pressure Through Biosensors

This paper presents a non-invasive technique and cuff less method for blood pressure measurement with a hardware prototype implementation. The sophisticated feature called pulse transit time (PTT) is extracted and investigated with a development of a smart system which consists of ECG, PPG sensor to estimate the systolic and diastolic blood pressure with support of advanced signal processing methodologies. The proposed method experiments have been carried out in hospital environment and tested with real time patients to validate the proposed method. The maximum error percentage of the proposed system has been shown to be 5.3% of systolic blood pressure (mmHg) and 4.7% of diastolic blood pressure (mmHg). This system also allows the monitoring of patient hypertension and overcome the limitation of cuff-based hospitalized measurement system

Wearable estimation of central aortic blood pressure.

Arterial hypertension affects a third of the world's population and is a significant risk factor for cardiovascular disease. Blood pressure (BP) is one of the most relevant parameters used for monitoring of possible hypertension states in patients at risk of cardiovascular disease. Hence, there exists a need for new monitoring solutions, which allow to increase the frequency between BP assessments, but also allow to reduce the level of occlusion in the attempts. Moens-Korteweg equation is among the main principles to estimate BP by dispensing of any inflatable cuff. This principle might lead to an indirect estimation of BP by measuring the time it takes the pressure pulse to propagate between two pre-established vascular points, accordingly the pulse transit time (PTT) method. This thesis proposes a wearable PTT-based method to estimate central aortic BP (CABP) and, the main milestones of this work included: proof of concept of the proposed method (pilot work), the development of a wearable device (including two stages of validation), the proposition of a miniaturized version (integrated circuit) of the analog front-end of the wearable hardware, and, the development of a novel PTT-based model (PTTBM, i.e., the mathematical relationship between measured variables and estimated BP) suitable for the proposed wearable methodology to estimate BP. The main contributions found at each milestone are presented. One of the contributions of this thesis is the use of the PTT-principle for estimating CABP instead of the peripheral BP (PBP) (as typically used in the literature). The pilot work showed the feasibility of CABP estimation from the PTT principle by using electrocardiogram (ECG) and ballistocardiogram (BCG) recordings from off-the-shelf equipment. Results showed that CABP was more correlated with the proposed methodology in comparison to all PBP variables assessed; confirming our hypothesis that the CABP is the most suitable parameter to collate through the time elapsed from ECG R-wave to the BCG J-wave. That is, considered featured time (RJ-interval) includes the time of a pulse pressure propagating at an aortic district. Bland-Altman plots showed an almost zero mean error (\u\ < 0.02mmHg) and bounded standard deviation o < 5mmHg for all systolic and mean central BP readings. Pilot work provided a landmark in order to develop a compact device that allows the integration of wireless blood pressure monitoring into a wearable system. Another contribution of this thesis is the proposition of a wearable device for PTT-computing by also including design considerations for the signal conditioning chains for ECG and BCG signals. The proposed design procedure takes care of minimizing the impact of spurious delays between physiological signals, which eventually degrade the PTT computation. Further, such a procedure could be suitable for any PTT-acquisition. Filtering with low and controlled delay is required for this biomedical application, and proposed conditioning chains provide less than 2ms group-delay, showing the effectiveness of the proposed approach. In order to provide the methodology with higher autonomy and integration, a highly miniaturized implementation of the filtering approach was also proposed. It includes the design of proposed architectures in CMOS technology to implement the particular low-delay filtering at reduced bandwidth featuring ultra-low-power characteristics. Results show that less than 2ms delay for the ECG QRS-complex can be achieved with a total current consumption of IDD = 2:1nA at VDD = 1:2V of power supply. Such development meant another significant contribution of this work in the conception of highly autonomous wearable devices for PTT acquisition. The first stage of validations on the wearable CABP estimation showed that, when considering data from one volunteer, results achieved with off-the-shelf equipment could be replicated by using a proposed wearable device, and the method could be further validated by using the wearable version. Additionally, CABP estimation from the proposed wearable device could be feasible by using three feature times (FTs) as CABP surrogates; that is, RI, RJ, and IJ intervals (from ECG and BCG wearable recordings). The first validation of the method also showed that CABP could be accurately predicted by the proposed methodology when in the order of daily calibrations are performed. The second stage of validations involved a study with a group of volunteers, and new alternatives were explored (twentyseven: nine PTTBMs along the three FTs) for the CABP estimation. We found that CABP could be accurately estimated (inside AAMI requirements) through the presented methodology by using four of the explored alternatives, whereas the RI interval, an FT lacking any PTT assessment, emerged as the best surrogate for the CABP estimation. Hence, a principle different from the traditional PTT-based method arises as a more advantageous method for the CABP estimation in the light of evidence reported in this validation, and, to our knowledge, this is the first time that CABP has been successfully estimated from a wearable device. The final significant contribution of this thesis meant the last chain-link in the process to achieve an utterly original method to estimate CABP. A novel PTTBM to estimate CABP is proposed, which uses a ow-driven two-element Windkesel network constructed from FTs extracted from the wearable recordings. When classic PTTBMs are applied, the fitting of parameters often leads to values without a physiological basis. Opposite to that in the proposed PTTBM, the parameters have a clear physiological meaning, and the parameter fitting led to values that are consistent with this meaning and more stable throughout calibrations. In conclusion, this thesis introduces a novel device that exploits an alternative and indirect method for CABP estimation. Variants of the principle used, accordingly, PTT method, have been previously explored to estimate PBP but not for central aortic BP. Additionally, the device was designed to be wearable; that is, it is attached to the clothes, causing low discomfort for the user during the measurement, thus, allowing continuous and ambulatory monitoring of aortic pressure. The developed wearable system, validated in a series of volunteers, showed promising results towards the continuous CABP monitoring.Se estima que casi un tercio de la población adulta mundial sufre de algún grado de hipertensión, siendo esto un factor de riesgo significativo para la enfermedad cardiovascular. La presión arterial (PA) es el parámetro utilizado para evaluar estos posibles estados de hipertensión; actualmente existe una necesidad de generación de nuevas tecnologías que permitan aumentar la frecuencia entre medidas de PA, pero al mismo tiempo de reducir el nivel de oclusión de éstas (técnicas aceptadas están mayoritariamente basadas en la oclusión y son de acceso limitado). El modelo Moens-Korteweg podría proveer los argumentos para la creación de nuevas técnicas para estimar la PA prescindiendo de cualquier brazalete inflable. Más específicamente, podría obtenerse una estimación indirecta de la PA a través de la medición del tiempo que tarda el pulso de presión en propagarse entre dos puntos vasculares predefinidos, método conocido como tiempo de tránsito del pulso (PTT). En la presente tesis se desarrolló un dispositivo vestible que explota este método alternativo e indirecto para la estimación de la PA pero a nivel central, es decir, busca estimar la PA en la aorta (CABP), la principal arteria de la red vascular. Para ello, los principales desarrollos de este trabajo incluyeron : prueba de concepto del método propuesto basado en PTT para estimar CABP, el desarrollo de un dispositivo vestible (incluyendo dos etapas de validaciones para la estimación de la PA), la propuesta de un circuito integrado para el hardware vestible y el desarrollo de un nuevo modelo para la estimación de la PA (PTTBM, es decir, la relación matemática que vincula las variables medidas con el hardware diseñado y la estimación de la PA). A continuación se presentan las principales contribuciones resultantes de cada frente de trabajo. Una de las contribuciones de esta tesis es el uso del principio PTT para estimar CABP en lugar de la BP periférica (PBP) (como se usa típicamente en la literatura). La prueba de concepto mostró la viabilidad de la estimación de CABP a partir del principio PTT mediante la adquisición de señales electrocardiograma (ECG) y balistocardiograma (BCG) utilizando equipos comerciales. Los resultados mostraron que CABP estaba más correlacionado con la metodología propuesta en comparación con todas las variables de PBP evaluadas; confirmando nuestra hipótesis de que la CABP sería la variable más adecuada para estimar a partir del tiempo transcurrido desde la onda R del ECG hasta la onda J del BCG. Es decir, el tiempo considerado (intervalo RJ) incluye un tiempo de propagación del pulso de presión a través de un segmento aórtico. Las gráficas de Bland-Altman mostraron un error medio casi nulo (\u\ < 0.02mmHg) y una precisión o < 5mmHg para las variables de presión sistólica y media centrales. La prueba de concepto proporcionó un hito para desarrollar un dispositivo vestible apuntando a la monitorización inalámbrica de la presión arterial en un sistema imperceptible para el usuario. Otra contribución de esta tesis es la propuesta de este dispositivo vestible para la adquisición de la PTT. El desarrollo incluye consideraciones de instrumentación necesarias para el correcto acondicionamiento de las señales ECG y BCG, de las cuales se obtiene la PTT. En particular, el procedimiento de diseño propuesto busca minimizar el impacto de los retrasos espurios entre las señales fisiológicas, que eventualmente degradan la computación de la PTT. Además, dicho procedimiento podría ser aprovechado por otros desarrolladores del método sin importar las definiciones de PTT que éstos usen. La limitación de banda con bajo retardo es necesario para esta aplicación biomédica, y el hardware de acondicionamiento propuesto proporciona menos de 2 ms de retraso en las se~nales (ECG y BCG) mientras consigue limitar sus bandas a decenas de Hz, lo que muestra la efectividad de la metodología propuesta. Adicionalmente, con el fin de proporcionar a la metodología de una mayor autonomía e integración, se propone una implementación altamente miniaturizada de la sección de filtrado con bajo retraso. Se incluye el diseño de nuevas topologías propuestas en tecnología CMOS para implementar el particular filtro de bajo retraso con reducido ancho de banda, y con características de ultra bajo consumo de potencia. El diseño integrado consigue obtener resultados similares al obtenido anteriormente (con componentes discretos) alcanzando un retraso de menos de 2 ms para el complejo QRS del ECG, pero con un consumo de IDD = 2:1 nA a un VDD = 1:2 V . Tal desarrollo significó otra contribución de este trabajo en el área de circuitos altamente autónomos para instrumentación biomédica. La primera etapa de validaciones en la estimación vestible de la CABP se basó en experimentaciones con un voluntario, mostrando que, la estimación vestible podría alcanzar los mismos resultados que los alcanzados utilizando equipos de investigación, permitiendo así avanzar en la validación del método propuesto utilizando el equipamiento vestible diseñado. Además de esto, se encontró que la estimación de CABP a partir del dispositivo vestible podría ser factible utilizando varios tiempos característicos (FT) extraídos de las señales vestibles ECG y BCG (intervalos RI, RJ e IJ) junto con un popular PTTBM. La primera validación del método también arrojó que la metodología propuesta podría estimar con precisión la CABP cuando el tiempo entre calibraciones es del orden de un día. La segunda etapa de validación implicó un estudio con un grupo de voluntarios, nuevas alternativas se exploraron esta vez (veintisiete: nueve PTTBM con tres FT) para la estimación de CABP. Descubrimos que CABP podría estimarse con precisión (dentro de los requisitos de AAMI) a través de la metodología presentada mediante el uso de cuatro de las alternativas exploradas, mientras que el intervalo RI, siendo un FT que a priori no tiene ninguna vinculación con un PTT, surge como el mejor estimador de la CABP. Se concluye entonces, que un principio diferente del método tradicional basado en PTT podría ser más ventajoso para la estimación de CABP a la luz de la evidencia encontrada en esta validación y, adicionalmente, a nuestro entender, esta es la primera vez que CABP se estima con éxito a partir de un dispositivo vestible. La contribución final de esta tesis significó el último eslabón de la cadena en el proceso de lograr un método completamente original para estimar CABP de punta a punta. Se propone un nuevo PTTBM para estimar CABP, éste es basado en una red Windkesel de dos elementos bajo una excitación de flujo. Estos elementos del PTTBM son construidos a partir de cantidades extraídas a través de procesamiento de las señales vestibles ECG y BCG. Cuando se aplican los PTTBM clásicos, el ajuste de sus parámetros (en calibración) a menudo conducen a valores sin base fisiológica, mostrando a su vez, una dispersión en sus valores a lo largo de distintas calibraciones que podrían ser inaceptables en la práctica. En contraposición, los parámetros del PTTBM propuesto convergen a cantidades con significado fisiologico claro y estable a lo largo de las calibraciones. En conclusión, esta tesis presenta un dispositivo novedoso que explota un método alternativo e indirecto para la estimación de CABP. El método propuesto es basado en la metodología de PTT, que si bien ha sido previamente explotado para estimar PBP, no se ha dirigido éste hacia el monitoreo vestible de la PA aórtica central. En este marco se desarrolla un dispositivo vestible, causando baja molestia en el usuario durante las mediciones, lo que permitiría un monitoreo continuo y ambulatorio real de la presión aórtica central. El sistema vestible desarrollado, validado en una serie de voluntarios, ha mostrado resultados prometedores hacia el monitoreo continuo de CABP

Experimental Demonstration of Accurate Noncontact Measurement of Arterial Pulse Wave Displacements Using 79-GHz Array Radar

In this study, we present a quantitative evaluation of the accuracy of simultaneous array-radar-based measurements of the displacements caused at two parts of the human body by arterial pulse wave propagation. To establish the feasibility of accurate radar-based noncontact measurement of this pulse wave propagation, we perform experiments with four participants using a 79-GHz millimeter-wave ultra-wideband multiple-input multiple-output array radar system and a pair of laser displacement sensors. We evaluate the accuracy of the pulse wave propagation measurements by comparing the displacement waveforms that are measured using the radar system with the corresponding waveforms that are measured using the laser sensors. In addition, to evaluate the estimates of the pulse wave propagation channels, we compare the impulse response functions that are calculated from the displacement waveforms obtained from both the radar data and the laser data. The displacement waveforms and the impulse responses both demonstrated the good agreement between the results of the radar and laser measurements. The normalized correlation coefficient between the impulse responses obtained from the radar and laser data on average was as high as 0.97 for the four participants. The results presented here strongly support the feasibility of accurate radar-based noncontact measurement of arterial pulse wave propagation

Blood pressure wave propagation : a multisensor setup for cerebral autoregulation studies

Objective. Cerebral autoregulation is critically important to maintain proper brain perfusion and supply the brain with oxygenated blood. Non-invasive measures of blood pressure (BP) are critical in assessing cerebral autoregulation. Wave propagation velocity may be a useful technique to estimate BP but the effect of the location of the sensors on the readings has not been thoroughly examined. In this paper, we were interested in studying whether the propagation velocity of a pressure wave in the direction from the heart to the brain may differ compared with propagation from the heart to the periphery, as well as across different physiological tasks and/or health conditions. Using non-invasive sensors simultaneously placed at different locations of the human body allows for the study of how the propagation velocity of the pressure wave, based on pulse transit time (PTT), varies across different directions. Approach. We present a multi-sensor BP wave propagation measurement setup intended for cerebral autoregulation studies. The presented sensor setup consists of three sensors, one placed on each of the neck, chest and finger, allowing simultaneous measurement of changes in BP propagation velocity towards the brain and to the periphery. We show how commonly tested physiological tasks affect the relative changes of PTT and correlations with BP. Main results. We observed that during maximal blow, valsalva and breath hold breathing tasks, the relative changes of PTT were higher when PTT was measured in the direction from the heart to the brain than from the heart to the peripherals. In contrast, during a deep breathing task, the relative change in PTT from the heart to the brain was lower. In addition, we present a short literature review of the PTT methods used in brain research. Significance. These preliminary data suggest that the physiological task and direction of PTT measurement may affect relative PTT changes. The presented three-sensor setup provides an easy and neuroimaging compatible method for cerebral autoregulation studies by allowing measurement of BP wave propagation velocity towards the brain versus towards the periphery

Methods and Algorithms for Cardiovascular Hemodynamics with Applications to Noninvasive Monitoring of Proximal Blood Pressure and Cardiac Output Using Pulse Transit Time

Advanced health monitoring and diagnostics technology are essential to reduce the unrivaled number of human fatalities due to cardiovascular diseases (CVDs). Traditionally, gold standard CVD diagnosis involves direct measurements of the aortic blood pressure (central BP) and flow by cardiac catheterization, which can lead to certain complications. Understanding the inner-workings of the cardiovascular system through patient-specific cardiovascular modeling can provide new means to CVD diagnosis and relating treatment. BP and flow waves propagate back and forth from heart to the peripheral sites, while carrying information about the properties of the arterial network. Their speed of propagation, magnitude and shape are directly related to the properties of blood and arterial vasculature. Obtaining functional and anatomical information about the arteries through clinical measurements and medical imaging, the digital twin of the arterial network of interest can be generated. The latter enables prediction of BP and flow waveforms along this network. Point of care devices (POCDs) can now conduct in-home measurements of cardiovascular signals, such as electrocardiogram (ECG), photoplethysmogram (PPG), ballistocardiogram (BCG) and even direct measurements of the pulse transit time (PTT). This vital information provides new opportunities for designing accurate patient-specific computational models eliminating, in many cases, the need for invasive measurements. One of the main efforts in this area is the development of noninvasive cuffless BP measurement using patient’s PTT. Commonly, BP prediction is carried out with regression models assuming direct or indirect relationships between BP and PTT. However, accounting for the nonlinear FSI mechanics of the arteries and the cardiac output is indispensable. In this work, a monotonicity-preserving quasi-1D FSI modeling platform is developed, capable of capturing the hyper-viscoelastic vessel wall deformation and nonlinear blood flow dynamics in arbitrary arterial networks. Special attention has been dedicated to the correct modeling of discontinuities, such as mechanical properties mismatch associated with the stent insertion, and the intertwining dynamics of multiscale 3D and 1D models when simulating the arterial network with an aneurysm. The developed platform, titled Cardiovascular Flow ANalysis (CardioFAN), is validated against well-known numerical, in vitro and in vivo arterial network measurements showing average prediction errors of 5.2%, 2.8% and 1.6% for blood flow, lumen cross-sectional area, and BP, respectively. CardioFAN evaluates the local PTT, which enables patient-specific calibration and its application to input signal reconstruction. The calibration is performed based on BP, stroke volume and PTT measured by POCDs. The calibrated model is then used in conjunction with noninvasively measured peripheral BP and PTT to inversely restore the cardiac output, proximal BP and aortic deformation in human subjects. The reconstructed results show average RMSEs of 1.4% for systolic and 4.6% for diastolic BPs, as well as 8.4% for cardiac output. This work is the first successful attempt in implementation of deterministic cardiovascular models as add-ons to wearable and smart POCD results, enabling continuous noninvasive monitoring of cardiovascular health to facilitate CVD diagnosis

Pervasive blood pressure monitoring using Photoplethysmogram (PPG) Sensor

Preventive healthcare requires continuous monitoring of the blood pressure (BP) of patients, which is not feasible using conventional methods. Photoplethysmogram (PPG) signals can be effectively used for this purpose as there is a physiological relation between the pulse width and BP and can be easily acquired using a wearable PPG sensor. However, developing real-time algorithms for wearable technology is a significant challenge due to various conflicting requirements such as high accuracy, computationally constrained devices, and limited power supply. In this paper, we propose a novel feature set for continuous, real-time identification of abnormal BP. This feature set is obtained by identifying the peaks and valleys in a PPG signal (using a peak detection algorithm), followed by the calculation of rising time, falling time and peak-to-peak distance. The histograms of these times are calculated to form a feature set that can be used for classification of PPG signals into one of the two classes: normal or abnormal BP. No public dataset is available for such study and therefore a prototype is developed to collect PPG signals alongside BP measurements. The proposed feature set shows very good performance with an overall accuracy of approximately 95\%. Although the proposed feature set is effective, the significance of individual features varies greatly (validated using significance testing) which led us to perform weighted voting of features for classification by performing autoregressive modeling. Our experiments show that the simplest linear classifiers produce very good results indicating the strength of the proposed feature set. The weighted voting improves the results significantly, producing an overall accuracy of about 98%. Conclusively, the PPG signals can be effectively used to identify BP, and the proposed feature set is efficient and computationally feasible for implementation on standalone devices.N/

Wireless Wearable Photoplethysmography Sensors for Continuous Blood Pressure Monitoring

Blood Pressure (BP) is a crucial vital sign taken into consideration for the general assessment of patient’s condition: patients with hypertension or hypotension are advised to record their BP routinely. Particularly, hypertension is emphasized by stress, diabetic neuropathy and coronary heart diseases and could lead to stroke. Therefore, routine and long-term monitoring can enable early detection of symptoms and prevent life-threatening events. The gold standard method for measuring BP is the use of a stethoscope and sphygmomanometer to detect systolic and diastolic pressures. However, only discrete measurements are taken. To enable pervasive and continuous monitoring of BP, recent methods have been proposed: pulse arrival time (PAT) or PAT difference (PATD) between different body parts are based on the combination of electrocardiogram (ECG) and photoplethysmography (PPG) sensors. Nevertheless, this technique could be quite obtrusive as in addition to at least two contacts/electrodes to measure the differential voltage across the left arm/leg/chest and the right arm/leg/chest, ECG measurements are easily corrupted by motion artefacts. Although such devices are small, wearable and relatively convenient to use, most devices are not designed for continuous BP measurements. This paper introduces a novel PPG-based pervasive sensing platform for continuous measurements of BP. Based on the principle of using PAT to estimate BP, two PPG sensors are used to measure the PATD between the earlobe and the wrist to measure BP. The device is compared with a gold standard PPG sensor and validation of the concept is conducted with a preliminary study involving 9 healthy subjects. Results show that the mean BP and PATD are correlated with a 0.3 factor. This preliminary study shows the feasibility of continuous monitoring of BP using a pair of PPG placed on the ear lobe and wrist with PATD measurements is possible