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The cardiac output monitoring devices based on pulse wave analysis (PWA) became a standard of hemodynamic management in many selected patients in critical and perioperative care. They are known as “minimally invasive” because the only prerequisite is a conventional arterial catheter. The technology is based on the arterial pressure curve (pulse wave) mathematical analysis. The PWA monitors are either calibrated or noncalibrated. Nowadays, four different technologies/mathematical models are marketed. EV1000 with FloTrac sensor (Edwards Lifesciences, Irvine, USA) uses mathematical/statistical analysis of the arterial curve. It derives stroke volume from small oscillations of arterial pressure values multiplied by a coefficient related to vessel impedance. PulsioFlex (Getinge, Gothenburg, Sweden) is based on dynamically changing aortic compliance, using integration of the systolic part of the arterial curve multiplied by the k constant, which is an internal factor corresponding to arterial impedance. LiDCO Rapid (LiDCO, London, UK) uses a pulse power algorithm—the arterial pressure curve is transformed into a volume curve according to the law of conservation of energy and mass. The last device, using the pressure recording analytical method (MostCare, Vytech Health, Padova, Italy), is based on pressure curve analysis; however, unlike all the others, it also uses the diastolic part of a curve (corresponding to continual blood flow). It calculates systemic impedance from pressure values, which are acquired at a very high frequency (1000 Hz). This chapter reviews the basic technology considerations as well as the appropriate use of these devices.

It is fair to conclude that people with a disorder in the brain and/or cardiovascular system are more likely to experience physical condition changes while driving, which may cause health-induced traffic accidents as a result. In response, we developed a sound sensing system that uses stochastic resonance to continuously capture the trunk acoustic pulse wave (or APW) transmitted through the body. We extracted a pressure waveform derived from the apical beat and the ejection wave to the chest and a pressure waveform generated by the abdominal aorta from the APW. We compared the information obtained from electrocardiogram and blood pressure readings and duly examined the possibility of predicting fluctuations in physical condition via the APW. The pressure waveform extracted from the APW was similar to the data created by heart rate and blood pressure fluctuations and showed a tendency to be disturbed when an arrhythmia occurred. Therefore, the APW could show changes in cardiovascular dynamics and fluctuations in systolic blood pressure and highlight an arrhythmia.

The pulse signal obtained non-invasively through an oscillometric method can accurately measure the Cardio-Ankle Vascular Index (CAVI) and Pulse Wave Velocity (PWV), two valuable physiological markers of arterial stiffness and cardiovascular health. The VOPITB device is designed to obtain these markers whose accuracy heavily depends on the correctness of feature extraction from pulse wave signals. Typically, a threshold method is obtained, leading to excessive detection success dependency on the established level. To overcome this limitation two signal processing methods are proposed, one based on a modified version of the Pan-Tompkins algorithm and the other centered on a Wavelet approach. A statistical study is presented assessing the accuracy of both methods. The new algorithms are presented as an alternative to the simple thresholding method.

In this article the integrated set of measured values and computational in-formative parameters for the mobile diagnostic devices used for monitoring and diagnostics of cardiovascular system of the person is brought. Methods of definition of current values of controllable parameters are examined, their merits and demerits are revealed. For the most effective estimation of a condition of cardiovascular system of the person (definition of parameters of central and peripheral hemodynamics, control parameters of transport of oxygen) it is necessary to use the complex method including volumetric compression oscillometry, electrocardiography, the blood pressure measurement by pulse wave together with a method of an estimation of requirement of an organism of the patient in oxygen. This mobile device can be used for the early diagnosis of COVID-19. The functional scheme of mobile diagnostic device is presented. The scheme includes the set of blocks, which are optimal by price and quality. All modules have built-in batteries, equipped with non-contact charging system that supports wireless communication channel, and boxed in waterproof, ergonomic case. Results of testing of separate blocks of mobile diagnostic device are described in the article.

This paper proposes an approach to control continuous-time single-input single-output (SISO) time-delay processes having output disturbances employing a linear quadratic regulator (LQR) predictive controller in the discrete-time domain. To demonstrate the validity of such an approach, this work performs the control of SISO stable with large time delay, unstable, non-minimum phase, oscillatory, and integrating benchmark time–delay processes, in other words, processes that have been used by the researches to demonstrate various published control approaches. In all cases, a pulse train disturbance signal on the output is rejected, while the controlled outputs follow pulse-shape reference signals.

Operational Modal Analysis (OMA) is a popular and effective method to identify the dynamic characteristics of a structure for Condition Monitoring (CM). It is well known that most of OMA methods are under the assumption that the excitation loads are stationary white noise. In practice however, this is not true, the excitation with pulse train and harmonic loads are common for mechanical systems with rotation parts, such as wind turbine and vehicle tested on the roller rig. In order to investigate the effects of pulse train and harmonic loads on the OMA, a quarter vehicle model was developed to simulate a Y25 bogie tested on the roller rig. Moreover, Correlation signal Subset based Stochastic Subspace Identification (CoS-SSI) was employed as the OMA technique in this study. The simulation results indicated that pulse train excitation has no effects on the OMA, whereas harmonic loads have significant effects. On the one hand, harmonic loads will result in false modes, on the other hand, the harmonic frequency will overwhelm the true modes of tested systems when the harmonic frequency is close to system resonance frequency. Therefore, cepstrum editing process was introduced in detail, and employed to filter out the harmonic effects before the OMA process. It has been proved that cepstrum editing is an easy but powerful approach to address the challenge of OMA in the presence of harmonics.

The context of this work concerns the development of a connected smartwatch for the continuous daily monitoring of physiological parameters to prevent cardiovascular diseases, and for the follow-up of the efficiency of treatments, against hypertension for example. This paper focuses on a particular parameter, the blood pressure (BP), to be automatically measured from the Photoplethysmogram (PPG) signal, to be acquired using a smartwatch. The proposed method is based on the automatic pulse wave detection from the PPG signal. Then, using the Lasso algorithm, a relation has been established between the blood pressure and the spectral representation of the normalized pulse wave, combined with other physiological information (age, body mass index and hear rate). The proposed method has been evaluated on a recent large public database of 219 subjects, covering a large range of ages (20–89), body mass indices and of blood pressures. Experimental results show acceptable performances in terms of accuracy. Compared to a recent related work depicting a slightly lower estimation error, a strength of our approach regards its robustness with respect to the signal quality, this being crucial for a use in daily routine in real IoT conditions, as it is the case in this context of smartwatch.

The paper is devoted to the algorithmic solution of quality control over the pneumatic blood pressure sensor positioning. Previously, this problem was solved by the operator based on his subjective assessment of the presence/absence of a pulse wave in the observed signal and its quality estimation. Recent studies have led us to a simple algorithm for automatically evaluating the accuracy of positioning. The algorithm is based on the value of the variability of the intervals of side peaks that the multiscale autocorrelation function can manifest as part of its structure. Since this value is closely related to such a characteristic of the signal as its quasi–periodicity, the algorithm essentially estimates the degree of periodicity of the signal, which is high in the presence of a pulse wave and small in its absence. In addition to the general principle of quasi–periodicity estimation much empirical information has been accumulated on the necessary preliminary normalization of the signal, the censorship of the side peaks to be considered, on the numerical values of the comparison thresholds, etc. The main ideas of the algorithm are illustrated by examples of processing real data obtained by positioning the developed pneumatic sensor.

In this paper, we propose a method to visualize blood flow of palm in different muscle tense state using RGB high-speed camera. Recently, new modalities are needed to develop a more accurate system to non-contact multi-modal affect analysis. Then, we focus on muscle tense. The muscle tense is caused by stress. Hence, the muscle tense is one of the effective modalities for non-contact multi-modal affect analysis. However, it is very difficult to measure muscle tense in the real environment because it requires a contact-type sensor. Therefore, we use iPPG to visualize the pulse wave during muscle tense from the skin video taken with the RGB video camera. As a result of this experiment, we found that it was possible to recognize the difference in pulse wave during muscle tense from the video that visualized the pulse wave. From this result, the realization of non-contact measurement of muscle tense can be expected.

Despite the intensive development of the dynamical systems theory and artificial intelligence, which is quite a powerful theoretical apparatus, an adequate description of chaotic processes at cardiovascular systems is a rather complicated problem. In this paper, the dynamical systems theory is applied to cardiovascular studies by processing the recorded signals with stochastic neural networks as well as dynamic chaos methods. The method of investigation is the reconstruction of dynamic systems attractor. Phase-temporal characteristics of human pulse waves were discussed, the new concept of the stochastic-graph of the pulse wave was shown. The attractor of heart pulse waves was reconstructed and its correlation dimension was estimated.

Pulse rate variability (PRV) is a small change in the heart beat cycle that can be obtained from the pulse signal. PRV has important application value in clinical diagnosis, disease monitoring, and prevention. PRV can be conveniently extracted from the fingertip pulse signal obtained by a photoplethysmography (PPG) pulse sensor. However, this method requires clamping the fingertip during the measurement, which is uncomfortable for the monitored person and is not conducive to continuous PRV detection in family monitoring or in a specific environment, such as driving. Thus, in this paper, we propose a pulse sensor with a soft polyvinylidene fluoride (PVDF) piezoelectric film. The non-invasive pulse signals can be collected by lightly pressing the fingertip on the sensor. In the experiment, two PVDF pulse sensors were used to collect the pulse waves from the left wrist and left forefinger; simultaneously, an infrared PPG pulse sensor measures the pulse wave of the right forefinger. The pulse waves measured by the three methods were further filtered to extract PRV signals and compare the differences. The results show that the PRV signal obtained by the PVDF sensor pressing measurement method has good consistency with the PRV signal obtained by PPG measurement, and the PVDF pulse sensor can be conveniently applied in wearable devices and portable medical devices to obtain the PRV.

The results of diagnosis of the arterial vascular system by the pulse wave recorded by the oscillometric method in a group of athletes engaged in rowing and having high sports categories, as well as the control group have been presented. The reaction of muscle tone to the occlusion of the brachial artery to determine the functional state of the endothelium was studied. To carry out screening diagnostics, we have proposed a method for assessing the functional state of the vascular system by the second derivative of the pulse wave amplitude. The algorithm of the digital signal processing of the pulse wave and the calculation of the index of the functional state of tone of the vascular system of the athletes has been developed. The pulse wave parameters were measured using a software and hardware complex based on the NI ELVIS station. The results of testing athletes for endothelial dysfunction were confirmed by duplex ultrasound scanning of the arterial bed on the device of expert class Philips HD 15 XE. The change in volumetric blood flow after reactive hyperemia was calculated relative to the initial value in two groups of patients. The correspondence between the reduction of the peak value of the volume blood flow obtained by duplex ultrasound scanning of the arterial bed and the reaction to the occlusion of the artery, leading to a decrease in the second derivative of the pulse wave amplitude, measured by the oscillometric method, was shown.

Partial discharges occur because of insulation defects, when the electric field amplitude locally exceeds the dielectric strength of the cavities inside the insulating material. The thermal, chemical and electrical phenomena associated with the partial discharges are dangerous for insulation systems of high voltage equipment, as they can accelerate the aging process. Therefore, partial discharge tests are nowadays prescribed as routine tests for most of the high voltage devices. The calibration of a partial discharge measuring system is carried out to determine its scale factor before every test. The calibration is performed with partial discharge calibrator. IEC 60270 describes methods used for the evaluation of the actual charge generated by the calibrator. However, some factors that may influence the performance test results regarding the influence of circuit components, partial discharge measuring system’s linearity, bandwidth and pulse train response on calibration are not specified. This paper presents an improved method for performance testing of partial discharge calibrators. A reference partial discharge calibrator was used, and the traceability of calibration was established. Various effects on calibration procedure were investigated such as the influence of circuit components, partial discharge measuring system’s linearity, bandwidth and pulse train response on calibration. Performed tests in this paper showed that these factors cannot be neglected and therefore an improved method for performance testing of partial discharge calibrators is proposed which considers mentioned factors and minimizes their influence on the calibration procedure.

Hypertension is an important risk factor for stroke and cardiovascular diseases. Ambulatory blood pressure (ABP) measurement is used to estimate the continuous blood pressure. However, the cuff method ABP must have a cuff setting around the upper arm and occluding the arm’s blood circulation during the recording period, which makes some of inconveniences, including feel uncomfortable and affects the quality of sleep. The cuff-less method of ABP measurement based on the Pulse Transit Time (PTT) with electrocardiogram (ECG) and photoplethysmogram (PPG) has solved the limitation and presented potential healthcare applications. This study applies five different blood pressure regression models with the major parameter (PTT) and minor parameters (heart rate, pulse wave interval and pulse width) for estimating continuous blood pressure by regression analysis. MIMIC II clinical database is used by the correlation and consistency analysis for different blood pressure models to compare the similarity of the real and estimated blood pressure variation. The best model among the applied blood pressure models is \( \text{PTT}_{{\text{ALL}}} - \text{BP} \) that can perform the average correlation in 0.87 and the average RRratio in 0.68. The blood pressure regression model of \( \text{PTT}_{{\text{ALL}}} - \text{BP} \) provides a successful analysis model for the estimation of long-term monitoring blood pressure trend. monitor for the real and estimated blood pressure have the same trend.

In the paper a reachability property of continuous-time linear systems with rectangular type inputs vector is addressed. Necessary and sufficient conditions for the existence of that type of input signals that steer the system from zero initial conditions to desired final state in assumed time are derived and proved. The computation method of the input signals vector set that are the solution to the problem is presented. Next, a minimum energy control problem is considered. Using an integral control performance index the minimum energy input vector is chosen from the set of consistent inputs. The considerations are illustrated by a numerical example of electrical circuit with pulse wave voltage sources, where the input signals that minimise assumed performance index are computed and applied to steer the electrical circuit to desired final state in given time.

The pulse wave contains very rich cardiovascular physiological and pathological information, its waveform amplitude and shape can reflect the physiological and pathological state of human cardiovascular system such as heart rate and blood pressure. Monitoring of pulse wave has important clinical diagnostic value in traditional Chinese medicine and modern medicine. However, the characteristics of weak pulse signal and vulnerable to interference make the extraction of useful fingertip pulse signals a difficult task. Here we propose a type of sensor based on polyvinylidene fluoride (PVDF) piezoelectric thin film that can collect fingertip pulse signal; By zero-phase filtering and de-noising, the baseline wander and interference in fingertip pulse signal can be successfully eliminated; In order to verify the validity, practicality of the fingertip pulse signal, the pulse signal with the fingertip is compared with those obtained with the wrist artery, and the characteristics of these two pulse signals are finally further analyzed in time domain and frequency domain. It is shown that the proposed piezoelectric film sensor can effectively detect the pulse fingertip signal. It is also shown the fingertip pulse signal amplitude is smaller than those obtained with the radial artery, but the measured pulse number in unit time with the fingertip is consistent with the radial artery measured result. From the analysis in frequency domain, the pulse fingertip signal focus on the low frequency component, and contains the main physiological information of human body, it is also more convenient access than the radial artery signal.

Measurement technologies of arterial parameters are mostly based on processing blood pulse wave which is an important representation of cardiac activity. The pulse wave is structured with forward and reflected waves which are affected by individual physiological parameters such as the blood intensity, the elasticity of the aorta, artery elasticity and the reflection location. The pulse wave is also an important parameter in invasive cuff-less blood pressure measurement methods. However, different physiological circumstances can lead to pulse waveforms with different characteristics including the curve factors, amplitude and time landmarks. In this study, the pulse wave signal is obtained by bio-impedance (BImp) via shoulder and photoplethysmography (PPG) from the left ear. Four age groups, as well as three (body mass index) BMI groups, are considered as physiological circumstances and the effect of them on five characteristics factors of the pulse wave, are compared. Overall, the results displayed a significant effect of the aging and BMI on the pulse wave’s characteristics.

While there are plenty of studies on clinical diagnosis of Parkinson’s disease, little literature is available on the possibility of simple tests that can help distinguish Parkinson’s disease sufferers from healthy individuals. In our study, by making use of pulse wave data, we identify physiological patterns characteristic of Parkinson’s disease patients. We observe that the sample entropy values of pulse waves, with certain parameters fixed, is statistically different between Parkinson’s disease sufferers and healthy individuals. We also find significant difference between the two groups in values of the largest Lyapunov exponent computed from the same pulse wave data. In addition, we introduce an Android tablet that in which the real-time measurement and analysis functions are incorporated. With this device, it takes only 5 s to produce a test result.

For over 90 years, researchers and clinicians have worked on systems to noninvasively measure pulse wave velocity, with the ultimate goal of measuring continuous, cuffless blood-pressure. The design of multisensor systems to make two or more measurements of the pulse wave along the human arterial tree has become the hallmark of these efforts. Pulse arrival time measurements are traditionally made by detecting a first fiducial point on the electrocardiogram (ECG) waveform, and second fiducial point on a distal pulsatile waveform, such as the photoplethysmogram (PPG) or impedance cardiogram (ICG). By looking at the time difference between these two fiducial points, an approximation for pulse wave velocity can be calculated. Some other challenges exist in transforming the pulse arrival times into absolute blood pressure, but these have been largely overcome, as evidenced by the clinical-grade systems that are commercially available in the marketplace today.

Measuring blood pressure in real time using wearable sensors mounted directly on the patient’s body is promising tool for assessing the state of the cardiovascular system and signalling symptoms of cardiovascular diseases. To solve this problem, we developed a new type of wearable arterial blood pressure monitoring sensor. Constructively, this sensor can be embedded in a flexible bracelet for measuring the pressure in the underlying radial artery. Due to the very small measuring pads (less than 1 mm\(^{2}\)) and, consequently, the ability to accurately position the contact pad directly over the artery, it is possible to ensure high quality of blood pressure measurement. However, since the artery itself is generally not visible, the correct positioning of the sensor is a non-trivial problem. In the paper we propose the solution of the problem – the positioning based on monitoring the pulse wave signals using three channels from closely spaced pads of a three-chamber pneumatic sensor.

Heart rate variability (HRV) indicates that the body is under internal or external stressors. Higher HRV parameters usually means that the body has a ability to cope with those stressors. The paper presents the results of the heart rate variability analysis obtained for a group of healthy adults. 70 adults had been examined. Photoplethysmogram signal had been acquired and processed. The aim of this study was to recognize the relationship between HRV and BMI, WHR and physical activity as an aid in drawing conclusions about what type and intensity of physical activity guarantees the safety of the exercising person. Obtained results show a visible change in the values of parameters after exercise for both women and men.

The arterial pulse has been the most basic sign of life for centuries. The radial pulse palpation has been pictured in the crest of the Royal Academy College of Physicians since 1628. The history of the arterial pulse entails the discovery of pulse, blood pressure and/or flow, and their measurements. This chapter begins with a review the description of the pulse and the related discoveries of pulse and blood pressure and/or flow since the ancient period until the late 1970s where the concept of haemodynamics and importance of pressure and flow pulsatility as well as methods to analyse the pulse in both time and frequency domains gained wider acceptance. Human aging is associated with an increase in blood pressure, particularly systolic and pulse pressures, and this is attributable to the loss of distensibility of the human aorta of which its function is to cushion pulsation from the ejecting heart. Stiffening of the major elastic arteries due to aging will cause the speed of the travelling pulse to be higher, and the reflected pulse wave from periphery to occur earlier, therefore will increase the amplitude of pressure. To understand how arterial haemodynamics is altered by the ageing process and cardiovascular disease is vital and this involves accurate measurement of central (or aortic) pressure. Finally, the chapter briefly considers the demand and technology to develop cuffless blood pressure measuring devices. This development could allow a device that can measure blood pressure accurately, with ease, comfortably and continuously.

This study selected the Region of Interest in the video to record the positions of the hand and wrist with a non-contact method, then filtered out the video noise and amplified the invisible changes through Eulerian Video Magnification and restored the pulse wave signal with the independent component analysis after the separation of the RGB channels. In the 10 sets of measurement data of 5 people, it has been found that when the spatial decomposition of Gaussian Pyramid was applied to the palm, the data of the estimated pulse rate in spectrum was closest to the data obtained from Pulse Oximeter with the correlation analysis of R-squared 0.886 and the agreement analysis of mean deviation 3.57 BPM. In additional to capturing pulse waves at different locations around the palm and wrist, the method applied in this study can estimate heart rate or pulse rate and improve the feasibility of monitoring non-contact pulse waves with RGB camera.

This paper deals with the model and learning rules of a pulsed neuron, which provide the linear filtering of signals represented by pulse trains. To reduce the number of training parameters of a pulsed neuron we propose using a bank of orthogonal filters as a model of synaptic connections. For this model of pulsed neuron, we derive a supervised learning rule in a general form that can include various orthogonal basis functions. The rules minimize the mean square error between the desired and the actual output signal of a linear filter realized on the base of the pulsed neuron model. We derive two special learning rules: with set of exponential complex orthogonal functions and set of block-pulse orthogonal functions. For both set of these functions, we demonstrate rule’s properties by computer simulation of linear filters that implement high-pass filtering and double integration of the input signal transformed to pulse train. We show the impulse and frequency responses of the filters as well as the dependencies of the normalized mean square error on the number of training iterations.

Pulse wave propagation, reflection and transmission along human aorta is studied on the 92-tube cadaveric model from aortic root to bifurcation. The branching coefficients, optimal coefficients by Murray, wave reflection coefficients by J. Lighthill have been computed and compared to the result computed on the 19-tube model of aorta derived from the 55-tube model of hyman systemic arterial tree by Westerhof. Variations in the local wave speed along the aorta have been computed on the model and compared to the continuous measurement data. It is shown the aorta is an optimal waveguide ensuring almost zero local wave reflections at the branches except for the aortic bifurcation, subclavian, carotid and kidney arteries. It is first shown that most of the branches have a negative wave reflection, which promotes blood acceleration and reduces the post-load on the heart due to the suction effect. The calculated values of the branching coefficients and pulse wave velocities correspond to the experimental measurements. The wave reflections at the kidney arteries depend on their individual geometry. The proposed approach can be used for preliminary estimation of the hemodynamic parameters caused by the wave propagation along individual aorta using the MRI study, and prediction of the risk of development of the cardiovascular diseases provided by abnormal hemodynamic.

It is crucial for those performing an echocardiographic examination to understand how the controls on an ultrasound machine alter the display. Without this knowledge, it is impossible to consistently optimize images. Unskilled manipulations may misrepresent diagnostic information and result in missed diagnoses. This chapter aims to describe controls found on most ultrasound machines, how they affect the image, and how they are used to optimize the ultrasound image.

With the basic introductory material about the Fourier transform covered in the last two chapters, this chapter drills into some heavy-duty examples including the stair signum function, odd negative exponential, sines/cosines times negative exponential, cropped cosine, cosine squared, cropped t, |t|, t2, and t4 functions, functions of the form f(t)/g(t), arctan function, hat function, tapered pulse, asymmetric triangular function, 3-step stair, truncated pulse train, and the ramped unit step function. Heavy use of applications to drill the idea of the Fourier transform in ones mind and get plenty practice and experience in carrying on the transform. In the chapter we rely heavily on using the Fourier transform properties, developed in the last chapter. We wrap the chapter by demonstrating the flexibility of the Fourier transform by deriving the FT of the unit step function using at least seven methods.

Echocardiography allows for a comprehensive assessment of cardiac structure and function by incorporating data from two dimensional (2-D), three dimensional (3-D), M-mode, pulse wave, continuous wave, color flow, and tissue Doppler echo. This chapter will cover the assessment of left ventricular (LV) size and systolic function by two-dimensional echocardiography (2DE), 3-dimensional echocardiography (3DE), and M-mode echo. A guideline-based approach to assessing left atrial, aortic, and inferior vena cava size will also be presented. Next, a stepwise approach to the comprehensive assessment of LV diastolic function utilizing 2DE, pulse wave and tissue Doppler echo will be presented. Finally, hemodynamic principles will be introduced that enable measurement of cardiac output and quantitative assessment of valvular heart disease. These principles will be further elaborated in subsequent chapters dedicated to the assessment of valvular heart disease.