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Cardiovascular diseases are a leading global cause of mortality. The current standard diagnostic methods, such as imaging and invasive procedures, are relatively expensive and partly connected with risks to the patient. Bioimpedance measurements hold the promise to offer rapid, safe, and low-cost alternative diagnostic methods. In the realm of cardiovascular diseases, bioimpedance methods rely on the changing electrical conductivity of blood, which depends on the local hemodynamics. However, the exact dependence of blood conductivity on the hemodynamic parameters is not yet fully understood, and the existing models for this dependence are limited to rather academic flow fields in straight pipes or channels. In this work, we suggest two closely connected anisotropic electrical conductivity models for blood in general three-dimensional flows, which consider the orientation and alignment of red blood cells (RBCs) in shear flows. In shear flows, RBCs adopt preferred orientations through a rotation of their membrane known as tank-treading motion. The two models are built on two different assumptions as to which hemodynamic characteristic determines the preferred orientation. The models are evaluated in two example simulations of blood flow. In a straight rigid vessel, the models coincide and are in accordance with experimental observations. In a simplified aorta geometry, the models yield different results. These differences are analyzed quantitatively, but a validation of the models with experiments is yet outstanding. [ABSTRACT FROM AUTHOR]

The miniaturization and energy optimization of sensors opens up new possibilities in the field of sleep research. Wearable sensors are capable of recording vital parameters during sleep in a simple and unobtrusive manner. In order to analyze sleep architecture and sleep disorders, continuous monitoring of movements and cardiorespiratory parameters in high resolution is of central importance. In this paper a novel wearable sensor device based on impedance plethysmography (IPG) is presented, which is able to continuously monitor movements and cardiac pa rameters at the wrist. The sensor is designed to realize high resolution measure - ments up to 48 hours constantly. Measurements during sleep show that up to 98% of the pulse intervals are correctly detected. Furthermore, the comparison of the heart rate variability (HRV) parameters between IPG and the gold standard ECG demonstrate the potential of the sensor as a valid tool for ambulant sleep analysis. [ABSTRACT FROM AUTHOR]

Introduction: Gestational diabetes, which is defined as any degree of glucose intolerance first seen during pregnancy, is increasing in prevalence in India. Gestational diabetes and Type 2 diabetes share the common pathophysiological factor of insulin resistance; mothers with gestational diabetes are more prone to developing Type 2 diabetes. The hyperglycemia and metabolic abnormalities in Type 2 diabetes are associated with microvascular complications such as, retinopathy, nephropathy, and neuropathy, including autonomic neuropathy. Autonomic neuropathy, especially cardiac autonomic neuropathy because of diabetes, is an important cause of mortality and morbidity. Impedance Plethysmography (IPG) is based on the principle that the volume of the arterial and venous pulses can be derived from the electric properties of blood. The peripheral pulse thus analysed shows morphological patterns that are specific for different diseases. Although various morphological patterns have been mapped with different diseases, the waveform of gestational diabetes has not yet been explored. Hence, this study aimed to find whether gestational diabetes affected peripheral blood flow in a way that could be detected by IPG, resulting in a specific waveform pattern. Additionally, as previous research on the effect of gestational diabetes on the autonomic nervous system shows conflicting results, this study aimed to determine whether gestational diabetes is associated with autonomic dysfunction that can be detected by IPG. Materials and Methods: This was is a case--control study conducted on 98 antenatal mothers. The IPG patterns of 50 mothers with gestational diabetes were compared with demographic, clinical data, and IPG waveforms of 48 age-matched controls. Results: We found that the heart rate variability, an indicator of autonomic nervous system function, was impaired in mothers with gestational diabetes. We did not find that gestational diabetes was associated with a specific waveform on IPG. Conclusion: Gestational diabetes is associated with autonomic dysfunction in the form of impaired heart rate variability that can be detected by IPG. [ABSTRACT FROM AUTHOR]

Introduction: Gestational diabetes, which is defined as any degree of glucose intolerance first seen during pregnancy, is increasing in prevalence in India. Gestational diabetes and Type 2 diabetes share the common pathophysiological factor of insulin resistance; mothers with gestational diabetes are more prone to developing Type 2 diabetes. The hyperglycemia and metabolic abnormalities in Type 2 diabetes are associated with microvascular complications such as, retinopathy, nephropathy, and neuropathy, including autonomic neuropathy. Autonomic neuropathy, especially cardiac autonomic neuropathy because of diabetes, is an important cause of mortality and morbidity. Impedance Plethysmography (IPG) is based on the principle that the volume of the arterial and venous pulses can be derived from the electric properties of blood. The peripheral pulse thus analysed shows morphological patterns that are specific for different diseases. Although various morphological patterns have been mapped with different diseases, the waveform of gestational diabetes has not yet been explored. Hence, this study aimed to find whether gestational diabetes affected peripheral blood flow in a way that could be detected by IPG, resulting in a specific waveform pattern. Additionally, as previous research on the effect of gestational diabetes on the autonomic nervous system shows conflicting results, this study aimed to determine whether gestational diabetes is associated with autonomic dysfunction that can be detected by IPG. Materials and Methods: This was is a case–control study conducted on 98 antenatal mothers. The IPG patterns of 50 mothers with gestational diabetes were compared with demographic, clinical data, and IPG waveforms of 48 age-matched controls. Results: We found that the heart rate variability, an indicator of autonomic nervous system function, was impaired in mothers with gestational diabetes. We did not find that gestational diabetes was associated with a specific waveform on IPG. Conclusion: Gestational diabetes is associated with autonomic dysfunction in the form of impaired heart rate variability that can be detected by IPG.

Recording of peripheral pulse serves as a very important and essential non-invasive tool used widely by doctors for the diagnosis of various diseases. The morphology of pulse is seen to vary as a function of time in a given individual and also from individual to individual. There are many variations in morphological patterns of peripheral pulse in different disease conditions, which lead to difficulty in accurate diagnosis. The peripheral pulse waveforms are extracted from radial arteries as time series data using a peripheral pulse analyzer which is designed on the principle of impedance plethysmography. It was first introduced by Nyober in the mid-nineteen hundreds and ameliorated further by Kubicek. It involves the recording of the instantaneous blood volume by the measurement of electrical impedance as a function of time. Therefore, the study of peripheral pulse morphology has gained much attention in the past few years among researchers. Physiological variability is one of the recent investigations added during the last two decades for the objective assessment of autonomic function and the assessment of prognosis in severe sicknesses namely myocardial infarction, diabetic neuropathy, etc. In addition to heart rate variability studied worldwide, few researchers have studied blood pressure variability and peripheral blood flow variability. In this computer era, artificial intelligence and machine learning techniques have become more important day-by-day, and different types of algorithms were used for the identification of hidden patterns from plethysmographic observations on the radial pulse such as support vector machine as well as crisp and fuzzy clustering. Eight patterns were classified with a yield of 80%–90% and helped with the diagnosis of disorders such as myocardial infarction, pulmonary tuberculosis, coronary artery disorders, cirrhosis of the liver, and bronchial asthma. This paper briefly describes the use of machine learning techniques for the classification of peripheral pulse morphologies.

Screening and diagnosing abdominal aortic aneurysms (AAA) are currently dependent on imaging studies such as ultrasound or computed tomography angiography. All imaging studies offer distinct advantages but also suffer from inherent limitations such as examiner dependency or ionizing radiation. Bioelectrical impedance analysis has previously been investigated with respect to its use in the detection of several cardiovascular and renal pathologies. The present pilot study assessed the feasibility of AAA detection based on bioimpedance analysis. In this single-center exploratory pilot study, measurements were conducted among three different cohorts: patients with AAA, end-stage renal disease patients without AAA, and healthy controls. The device used in the study, CombynECG, is an open-market accessible device for segmental bioelectrical impedance analysis. The data was preprocessed and used to train four different machine learning models on a randomized training sample (80% of the full dataset). Each model was then evaluated on a test set (20% of the full dataset). The total sample included 22 patients with AAA, 16 chronic kidney disease patients, and 23 healthy controls. All four models showed strong predictive performance in the test partitions. Specificity ranged from 71.4 to 100%, while sensitivity ranged from 66.7 to 100%. The best-performing model had 100% accuracy for classification when applied to the test sample. Additionally, an exploratory analysis to approximate the maximum AAA diameter was conducted. An association analysis revealed several impedance parameters that might possess predictive ability with respect to aneurysm size. AAA detection via bioelectrical impedance analysis is technically feasible and appears to be a promising technology for large-scale clinical studies and routine clinical screening assessments. [ABSTRACT FROM AUTHOR]

Cardiovascular diseases are a leading global cause of mortality. The current standard diagnostic methods, such as imaging and invasive procedures, are relatively expensive and partly connected with risks to the patient. Bioimpedance measurements hold the promise to offer rapid, safe, and low-cost alternative diagnostic methods. In the realm of cardiovascular diseases, bioimpedance methods rely on the changing electrical conductivity of blood, which depends on the local hemodynamics. However, the exact dependence of blood conductivity on the hemodynamic parameters is not yet fully understood, and the existing models for this dependence are limited to rather academic flow fields in straight pipes or channels. In this work, we suggest two closely connected anisotropic electrical conductivity models for blood in general three-dimensional flows, which consider the orientation and alignment of red blood cells (RBCs) in shear flows. In shear flows, RBCs adopt preferred orientations through a rotation of their membrane known as tank-treading motion. The two models are built on two different assumptions as to which hemodynamic characteristic determines the preferred orientation. The models are evaluated in two example simulations of blood flow. In a straight rigid vessel, the models coincide and are in accordance with experimental observations. In a simplified aorta geometry, the models yield different results. These differences are analyzed quantitatively, but a validation of the models with experiments is yet outstanding.

In this paper we are introducing innovative solutions applied in impedance plethysmography concerning improvement of the rheagraph characteristics and the efficiency increase of the developing rheograms using computer methods. The described methods have been developed in order to ensure the stability of parameters and to extend the functionality of the rheographic system based on digital signal processing, which applies to the compensation of the base resistance with a digital potentiometer, digital synthesis of quadrature excitation signals and the performance of digital synchronous detection. The emphasis was put on methods for determination of hemodynamic parameters by computer processing of the rheograms. As a result–three methods for respiratory artifacts elimination have been proposed: based on the discrete cosine transform, the discrete wavelet transform and the approximation of the zero line with spline functions. Additionally, computer methods for physiological indicators determination, including those based on wavelet decomposition, were also proposed and described in this paper. The efficiency of various rheogram compression algorithms was tested, evaluated and presented in this work. [ABSTRACT FROM AUTHOR]

Continuous blood pressure (BP) measurement is crucial for long-term cardiovascular monitoring, especially for prompt hypertension detection. However, most of the continuous BP measurements rely on the pulse transit time (PTT) from multiple-channel physiological acquisition systems that impede wearable applications. Recently, wearable and smart health electronics have become significant for next-generation personalized healthcare progress. This study proposes an intelligent single-channel bio-impedance system for personalized BP monitoring. Compared to the PTT-based methods, the proposed sensing configuration greatly reduces the hardware complexity, which is beneficial for wearable applications. Most of all, the proposed system can extract the significant BP features hidden from the measured bio-impedance signals by an ultra-lightweight AI algorithm, implemented to further establish a tailored BP model for personalized healthcare. In the human trial, the proposed system demonstrates the BP accuracy in terms of the mean error (ME) and the mean absolute error (MAE) within 1.7 ± 3.4 mmHg and 2.7 ± 2.6 mmHg, respectively, which agrees with the criteria of the Association for the Advancement of Medical Instrumentation (AAMI). In conclusion, this work presents a proof-of-concept for an AI-based single-channel bio-impedance BP system. The new wearable smart system is expected to accelerate the artificial intelligence of things (AIoT) technology for personalized BP healthcare in the future. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Wearable and unobtrusive sensing devices are rapidly evolving for long-term cardiovascular monitoring. However, most of the cardiovascular device requires multi-channel physiological signals acquisition, especially in continuous blood pressure (BP) measurement using pulse transition time (PTT) based methods. The multi-devices implementation could impede wearable applications. Objective: This study developed a wearable neck patch device using single-channel impedance plethysmography (IPG) sensing for cardiovascular monitoring, including continuous BP and heart rate (HR) measurement. Methods: IPG-based BP model was derived based on the Bramwell-Hill equation. A patch IPG device was designed and installed above the carotid artery of the subject neck. To validate the BP and HR functions of our device, the Bland-Altman plots were performed to evaluate the estimation error between the reference and the proposed devices within 20 healthy subjects. Results: The BP performance indicates that systolic BP (SBP) estimation error was -0.16 ± 2.97 mmHg and 2.43 ± 1.71 mmHg in terms of mean error (ME) and mean absolute error (MAE), and 0.09 ± 3.30 mmHg and 2.83 ± 1.68 mmHg for diastolic BP (DBP) estimation. Moreover, the HR accuracy has the ME and MAE of 0.02 ± 0.17 bpm and 0.14 ± 0.08 bpm; mean percentage error (MPE) and mean absolute percentage error (MAPE) obtained 0.04 ± 0.23 % and 0.19 ± 0.12 %. Based on statistical results, the BP and HR function of our device satisfied with AAMI/ANSI criteria below 5 ± 8 mmHg and ± 5 bpm or ± 10%. Conclusion: This study implemented a wearable neck patch device with single-channel IPG acquisition that provided two significant cardiovascular parameters of continuous BP and HR, and its performance agreed with standard criteria based on validation with reference sensors. Significance: The proposed proof-of-concept IPG neck patch device has a high potential for wearable applications and low-cost manufacturing in cardiovascular monitoring.

In this paper we are introducing innovative solutions applied in impedance plethysmography concerning improvement of the rheagraph characteristics and the efficiency increase of the developing rheograms using computer methods. The described methods have been developed in order to ensure the stability of parameters and to extend the functionality of the rheographic system based on digital signal processing, which applies to the compensation of the base resistance with a digital potentiometer, digital synthesis of quadrature excitation signals and the performance of digital synchronous detection. The emphasis was put on methods for determination of hemodynamic parameters by computer processing of the rheograms. As a result–three methods for respiratory artifacts elimination have been proposed: based on the discrete cosine transform, the discrete wavelet transform and the approximation of the zero line with spline functions. Additionally, computer methods for physiological indicators determination, including those based on wavelet decomposition, were also proposed and described in this paper. The efficiency of various rheogram compression algorithms was tested, evaluated and presented in this work.

Continuous blood pressure (BP) measurement is crucial for long-term cardiovascular monitoring, especially for prompt hypertension detection. However, most of the continuous BP measurements rely on the pulse transit time (PTT) from multiple-channel physiological acquisition systems that impede wearable applications. Recently, wearable and smart health electronics have become significant for next-generation personalized healthcare progress. This study proposes an intelligent single-channel bio-impedance system for personalized BP monitoring. Compared to the PTT-based methods, the proposed sensing configuration greatly reduces the hardware complexity, which is beneficial for wearable applications. Most of all, the proposed system can extract the significant BP features hidden from the measured bio-impedance signals by an ultra-lightweight AI algorithm, implemented to further establish a tailored BP model for personalized healthcare. In the human trial, the proposed system demonstrates the BP accuracy in terms of the mean error (ME) and the mean absolute error (MAE) within 1.7 ± 3.4 mmHg and 2.7 ± 2.6 mmHg, respectively, which agrees with the criteria of the Association for the Advancement of Medical Instrumentation (AAMI). In conclusion, this work presents a proof-of-concept for an AI-based single-channel bio-impedance BP system. The new wearable smart system is expected to accelerate the artificial intelligence of things (AIoT) technology for personalized BP healthcare in the future.

Impedance plethysmography of extremities typically involves band electrodes around limbs to monitor changes in blood volume. This often causes monitored blood variations to only generate minuscule impedance values relative to the measured baseline, attributed to the tissue surrounding the artery or vein of interest. Smaller, ECG type electrodes can provide a larger signal, however their output is very easily affected by the placement of the electrodes relative to the targeted vasculature. This paper presents a novel method to adjust the active surface of electrodes, introducing Dynamically Re-sizeable Electrodes (DRE), to only target the exact area of interest, forming localised electrodes, without having to manually re-position them. Elongated rectangular electrodes were partitioned into smaller electrode segments, interconnected through custom circuitry. For the development and assessment of the DRE system, work was carried out both experimentally in-vitro on gelatine phantoms using custom switching circuits and through finite element modelling (FEM) simulations in COMSOL. A scanning sequence made use of DRE in single segment variable tetra-pole (SSVT) mode proved capable to identify the transcutaneous location of the blood vessel of interest and the specific electrode segments located in its vicinity. Impedance measurements were then taken using these segments connected to form localised electrodes only placed over the targeted vessel. The resulting localised electrodes exhibited up to $\text{28}\%$ increased sensitivity to blood variations relative to larger electrodes. [ABSTRACT FROM AUTHOR]

Objective: Arterial stiffness is an important marker to predict cardiovascular events. Common measurement techniques to determine the condition of the aorta are limited to the acquisition of the arterial pulse wave at the extremities. The goal of this paper is to enable non-invasive measurements of the aortic pulse wave velocity, instead. An additional aim is to extract further information, related to the conditions of the aorta, from the pulse wave signal instead of only its velocity. Methods: After discussing the problems of common pulse wave analysis procedures, an approach to determine the frequency response of the aorta is presented. Therefore, the aorta is modeled as an electrical equivalent circuit. To determine the specific numeric values of this system, a measurement approach is presented, which is based on non-invasive bioimpedance plethysmography measurements above the aortic arch and at the inguinal region. The conversion of the measurement results to the system parameters is realized by a digital algorithm, which is proposed in this paper as well. To evaluate the approach, a study on three subjects is performed. Results: The measurement results demonstrate that the proposed approach yields realistic frequency responses. For better approximation of the aortic system function, more complex models are recommended to investigate in the future. Since this paper is limited to three subjects without a ground truth, further measurements will be necessary. Significance: The proposed approach could solve the problems of current methods to determine the condition of the aorta. Its application is non-invasive, harmless, and easy to execute. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Highly integrated analog frontends for biosignal acquisition facilitate the development of complex yet small vital sign monitors capable of passive sensing. However, the established gold standards for sensor positioning cover large areas of the patient's body. Especially when measuring respiration, an important parameter in postoperative care and sleep monitoring, masks, belts or nasal cannulas are used. Therefore, estimation techniques such as photoplethysmography (PPG) derived respiration have emerged. Fingertip PPG is a widely used modality acquired optically at the peripheral vascular system. While miniaturized reflective PPG systems are available, their integration can prove problematic in certain scenarios, especially with textiles. We propose impedance plethysmography as a well integrable alternative to PPG for the estimation of absolute respiratory flow and rate. Employing nested cross-validation and wrapper techniques in a model and feature selection framework, we analyzed different polynomial and multilayer perceptron regression models as well as feature sets. In a pilot study, we achieved relative errors of 1.5 % for respiratory rate and 59 % for flow estimation using seven time-domain features of the acquired impedance signal. We conclude that impedance plethysmography can be a promising alternative for highly integrated and unobtrusive respiratory rate estimation as well as rough flow estimation. [ABSTRACT FROM AUTHOR]

Measurement of the stroke volume (SV) and its changes over time can be very helpful for diagnosis of dysfunctions in the blood circulatory system and monitoring their treatments. Impedance cardiography (ICG) is a simple method of measuring the SV based on changes in the instantaneous mean impedance of the thorax. This method has received much attention in the last two decades because it is noninvasive, easy to be used, and applicable for continuous monitoring of SV as well as other hemodynamic parameters. The aim of this study was to develop a low-cost portable ICG system with high accuracy for monitoring SV. The proposed wireless system uses a tetrapolar configuration to measure the impedance of the thorax at 50 kHz. The system consists of carefully designed precise voltage-controlled current source, biopotential recorder, and demodulator. The measured impedance was analyzed on a computer to determine SV. After evaluating the system's electronic performance, its accuracy was assessed by comparing its measurements with the values obtained from Doppler echocardiography (DE) on 5 participants. The implemented ICG system can noninvasively provide a continuous measure of SV. The signal to noise ratio of the system was measured above 50 dB. The experiments revealed that a strong correlation (r = 0.89) exists between the measurements by the developed system and DE (P < 0.05). ICG as the sixth vital sign can be measured simply and reliably by the developed system, but more detailed validation studies should be conducted to evaluate the system performance. There is a good promise to upgrade the system to a commercial version domestically for clinical use in the future.

Impedance plethysmography provides a way to measure respiratory activity by sensing the change of thoracic impedance caused by inspiration and expiration. This measurement imposes little pressure on the body and uses the human body as the sensor, thereby reducing the need for adjustments as body position changes and making it suitable for long-term or ambulatory monitoring. The empirical mode decomposition (EMD) can decompose a signal into several intrinsic mode functions (IMFs) that disclose nonstationary components as well as stationary components and, similarly, capture respiratory episodes from thoracic impedance. However, upper-body movements usually produce motion artifacts that are not easily removed by digital filtering. Moreover, large motion artifacts disable the EMD to decompose respiratory components. In this paper, motion artifacts are detected and replaced by the data mirrored from the prior and the posterior before EMD processing. A novel intrinsic respiratory reconstruction index that considers both global and local properties of IMFs is proposed to define respiration-related IMFs for respiration reconstruction and instantaneous respiratory estimation. Based on the experiments performing a series of static and dynamic physical activates, our results showed the proposed method had higher cross correlations between respiratory frequencies estimated from thoracic impedance and those from oronasal airflow based on small window size compared to the Fourier transform-based method.

Chronic venous insufficiency of the lower limbs is a disease which is caused by an increased blood pressure inside the veins of the leg and the resulting increase of the contained blood volume. This work focuses on developing a device which uses impedance plethysmography, also known as impedance phlebography, to obtain information about the blood volume in the lower leg and provides the possibility to measure the impedance semi contact-less, e.g. through compression stockings. Furthermore a real-time beat-to-beat interval detection algorithm was implemented. Finally, the function of the developed impedance measuring system and the whole system was verified by comparing it with a gold standard. In comparison to the conductive coupling, the system performed similarly. The analysis showed that the developed system is suitable for semi-capacitive IPG. The algorithm was implemented conservatively since it provided a good false-positive rate of 0 %, but only a moderate sensitivity of about 68 %. Reliable and continuous measurement of the pulse signal was only possible in periods of immobility.

Purpose: Accurate assessment of cardiac function is important during pregnancy. Echocardiography and impedance cardiography (ICG) are commonly used noninvasive methods to measure stroke volume (SV) and cardiac output (CO). The difference in stroke volume (ΔSV) or cardiac output (ΔCO) measured at baseline and after passive leg raising (PLR) is a measure of preload reserve that predicts volume responsiveness. However, the agreement between these two methods in measuring preload reserve during pregnancy is unclear. The aim of our study was to investigate the correlation and the agreement between Doppler echocardiography and ICG in assessing preload reserve in pregnant women.Methods: In this prospective observational cross-sectional study, preload reserve was assessed by measuring the SV and CO during baseline and 90 s after PLR simultaneously by Doppler echocardiography and ICG in healthy pregnant women during the second and third trimesters. Bland-Altman analysis was used to determine the agreement between the two methods. Bias was calculated as the mean difference between two methods and precision as 1.96 SD of the difference.Results: A total of 53 pregnant women were included. We found a statistically significant correlation between ΔSV (R = 0.56, p < 0.0001) and ΔCO (R = 0.39, p = 0.004) measured by ICG and Doppler echocardiography. The mean bias for ΔSV was 2.52 ml, with a precision of 18.19 ml. The mean bias for ΔCO was 0.21 l/min, with a precision of 1.51 l/min.Conclusion: There was a good agreement and a statistically significant correlation between ICG and Doppler echocardiography for measuring preload reserve. [ABSTRACT FROM AUTHOR]

Pulse wave analysis is an important method used to gather information about the cardiovascular system. Instead of detecting the pulse wave via pressure sensors, bioimpedance measurements can be performed to acquire minuscule changes in the conductivity of the tissue, caused by the pulse wave. This work presents a microcontroller-based bioimpedance measurement system, which has the capability to acquire impedance measurements from up to four independent channels simultaneously. By combining a problem-specific analog measurement circuit with a 24 bits analog-to-digital converter, the system is capable of acquiring 1000 impedances per second with a signal-to-noise ratio in a range from 92 to 96 dB. For data storage and analysis, the digitized data are sent via universal serial bus to a host PC. A graphical user interface filters and plots the data of all channels in real-time. The performance of the system regarding measuring constant impedances, as well as impedance changes over time is demonstrated. Two different applications for pulse wave analysis via multichannel bioimpedance measurements are presented. Additionally, first measurement results from a human subject are shown to demonstrate the system's applicability of analyzing the pulse wave morphology as well as the aortic pulse wave velocity. [ABSTRACT FROM AUTHOR]

Background and objective: In the diagnosis of peripheral artery disease (PAD), the ankle-brachial index (ABI) is considered as the standard, and other noninvasive methods have received too little attention. Therefore, the aim of the study was to determine the diagnostic accuracy of impedance plethysmography in diagnosing PAD and to compare this method with other methods. Materials and methods: A total of 66 patients with a mean age of 76.1 ± 9.6 years who had been treated for various cardiovascular diseases at Kaunas Clinical Hospital during 2011–2012 were enrolled into the study. All the patients were screened for PAD. Impedance plethysmography was performed with a new-generation Niccomo™ device. The receiver operating characteristic analysis was employed to determine the diagnostic accuracy of 4 parameters of impedance plethysmography: crest time (CT), crest width (CW), pulse amplitude (Pampl), and alternating blood flow (ABF). Results: There were a significant correlation between the ABI and the CT (r = −0.699, P

Purpose: We hypothesized that skin blood flow (SBF) of fingers are modulated during concentrated finger perception and that the changes in SBF reflect fluctuations in finger volume (FV). The aim of this study, therefore, was examine the relationship between the changes in SBF and FV during Braille reading. Methods: We measured SBF of the finger, cutaneous vascular conductance (CVC), FV, and arterial blood pressure during Braille reading performed under blind conditions in thirty healthy subjects. The subjects were instructed to read a flat plate with raised letters (Braille reading) for 15 seconds using their forefinger, and to touch a blank plate as a control for the Braille discrimination procedure. Results: Arterial blood pressure slightly increased during Braille reading but remained unchanged during the touching of the blank plate. SBF, CVC, and FV were reduced during Braille reading (decreased by -26%, -29%, and -0.3 mL/100 mL respectively). Furthermore, a significant relationship was observed between the changes in SBF and FV (r=.613) during Braille reading. Conclusion: These results suggested that SBF of fingers is modulated during concentrated finger perception, and that the variability of blood flow reflects the response in FV. [ABSTRACT FROM AUTHOR]