Analysis of the effect of CPAP on hemodynamics using clinical data and a theoretical model: CPAP therapy decreases cardiac output mechanically but increases it via afterload reduction.

BACKGROUND: Noninvasive positive pressure ventilation (NIPPV) has been established as an effective treatment for heart failure. Positive airway pressure such as continuous positive airway pressure (CPAP) increases cardiac output (CO) in some patients but decreases it in others. However, the mechanism behind such unpredictable responses remains undetermined. METHODS AND RESULTS: We measured hemodynamic parameters of 38 cases using Swan-Ganz catheter before and after CPAP in chronic heart failure status. In those whose CO increased by CPAP, pulmonary vascular resistance (PVR) was significantly decreased and SpO2 significantly increased, but the other parameters were not changed. On the other hand, PVR was not changed, but systemic vascular resistance (SVR) was increased in those whose CO decreased by CPAP. To explain this phenomenon, we simulated the cardiovascular system using a cardiac model of time-varying elastance. In this model, it was indicated that CPAP decreases CO irrespective of cardiac function or filling status under constant PVR condition. However, when reduction of PVR by CPAP was taken into account, an increase in CO was expected especially in the hypervolemic and low right ventricle (RV) systolic function cases. CONCLUSIONS: CPAP would increase CO only where PVR can be reduced by CPAP therapy, especially in the case with hypervolemia and/or low RV systolic function. Understanding the underlying mechanism should help identify the patients for whom NIPPV would be effective.

Uncertainty in Blood Pressure Measurement Estimated Using Ensemble-Based Recursive Methodology.

Automated oscillometric blood pressure monitors are commonly used to measure blood pressure for many patients at home, office, and medical centers, and they have been actively studied recently. These devices usually provide a single blood pressure point and they are not able to indicate the uncertainty of the measured quantity. We propose a new technique using an ensemble-based recursive methodology to measure uncertainty for oscillometric blood pressure measurements. There are three stages we consider: the first stage is pre-learning to initialize good parameters using the bagging technique. In the second stage, we fine-tune the parameters using the ensemble-based recursive methodology that is used to accurately estimate blood pressure and then measure the uncertainty for the systolic blood pressure and diastolic blood pressure in the third stage.

An integrated blood pressure measurement system for suppression of motion artifacts.

Accuracy in blood pressure (BP) estimation is essential for proper diagnosis and management of hypertension. Motion artifacts are considered external sources of inaccuracy and can be due to sudden arm motion, muscle tremor, shivering, and transport vehicle vibrations. In the proposed work, a new algorithmic stage is integrated in a non-invasive BP monitor. This stage suppresses the effect of the motion artifact and adjusts the pressure estimation before displaying it to users. The proposed stage is based on a 3-axis accelerometer signal, which helps in the accurate detection of the motion artifact. Both transient motion artifacts and artifact due to vibrations are suppressed using algorithms based on Empirical Mode Decomposition (EMD). Measurements with human subjects show that the proposed algorithms considerably improved the accuracy of the blood pressure estimates in comparison with the commonly-used conventional oscillometric algorithm that does not include an EMD-based stage for artifact suppression, and allowed the estimates to meet the requirements of the international ANSI/AAMI/ISO standard.

Characteristic Ratio-Independent Arterial Stiffness-Based Blood Pressure Estimation.

Noninvasive blood pressure (BP) measurement is an important tool for managing hypertension and cardiovascular disease. However, automated noninvasive BP measurement devices, which are usually based on the oscillometric method, do not always provide accurate estimation of BP. It has been found that change in arterial stiffness (AS) is an underlying mechanism of disagreement between an oscillometric BP monitor and a sphygmomanometer. This problem is addressed by incorporating parameters related to AS in the algorithm for BP measurement. Pulse transit time (PTT) is first used to estimate AS parameters, which are fixed into a model of the oscillometric envelope. This model can then be used to perform curve fitting to the measured signal using only four parameters: systolic BP, diastolic BP, mean BP, and lumen area at zero transmural pressure. The proposed technique is independent of the experimentally determined characteristic ratios that are commonly used in existing oscillometric methods. The accuracy of the proposed technique was evaluated by comparing with the same model without incorporation of AS, and with reference BP device measurements. The new method achieved standard deviation of error less than 8 mmHg and mean error less than 5 mmHg. The results show consistency with ANSI/AAMI SP-10 standard for noninvasive BP measurement techniques.

Event Recognition for Contactless Activity Monitoring Using Phase-Modulated Continuous Wave Radar.

OBJECTIVES: The use of remote sensing technologies such as radar is gaining popularity as a technique for contactless detection of physiological signals and analysis of human motion. This paper presents a methodology for classifying different events in a collection of phase modulated continuous wave radar returns. The primary application of interest is to monitor inmates where the presence of human vital signs amidst different, interferences needs to be identified. METHODS: A comprehensive set of features is derived through time and frequency domain analyses of the radar returns. The Bhattacharyya distance is used to preselect the features with highest class separability as the possible candidate features for use in the classification process. The uncorrelated linear discriminant analysis is performed to decorrelate, denoise, and reduce the dimension of the candidate feature set. Linear and quadratic Bayesian classifiers are designed to distinguish breathing, different human motions, and nonhuman motions. The performance of these classifiers is evaluated on a pilot dataset of radar returns that contained different events including breathing, stopped breathing, simple human motions, and movement of fan and water. RESULTS: Our proposed pattern classification system achieved accuracies of up to 93% in stationary subject detection, 90% in stop-breathing detection, and 86% in interference detection. CONCLUSION: Our proposed radar pattern recognition system was able to accurately distinguish the predefined events amidst interferences. SIGNIFICANCE: Besides inmate monitoring and suicide attempt detection, this paper can be extended to other radar applications such as home-based monitoring of elderly people, apnea detection, and home occupancy detection.

Oscillometric blood pressure estimation by combining nonparametric bootstrap with Gaussian mixture model.

BACKGROUND: Blood pressure (BP) is one of the most important vital indicators and plays a key role in determining the cardiovascular activity of patients. METHODS: This paper proposes a hybrid approach consisting of nonparametric bootstrap (NPB) and machine learning techniques to obtain the characteristic ratios (CR) used in the blood pressure estimation algorithm to improve the accuracy of systolic blood pressure (SBP) and diastolic blood pressure (DBP) estimates and obtain confidence intervals (CI). The NPB technique is used to circumvent the requirement for large sample set for obtaining the CI. A mixture of Gaussian densities is assumed for the CRs and Gaussian mixture model (GMM) is chosen to estimate the SBP and DBP ratios. The K-means clustering technique is used to obtain the mixture order of the Gaussian densities. RESULTS: The proposed approach achieves grade "A" under British Society of Hypertension testing protocol and is superior to the conventional approach based on maximum amplitude algorithm (MAA) that uses fixed CR ratios. The proposed approach also yields a lower mean error (ME) and the standard deviation of the error (SDE) in the estimates when compared to the conventional MAA method. In addition, CIs obtained through the proposed hybrid approach are also narrower with a lower SDE. CONCLUSIONS: The proposed approach combining the NPB technique with the GMM provides a methodology to derive individualized characteristic ratio. The results exhibit that the proposed approach enhances the accuracy of SBP and DBP estimation and provides narrower confidence intervals for the estimates.

Bayesian fusion algorithm for improved oscillometric blood pressure estimation.

A variety of oscillometric algorithms have been recently proposed in the literature for estimation of blood pressure (BP). However, these algorithms possess specific strengths and weaknesses that should be taken into account before selecting the most appropriate one. In this paper, we propose a fusion method to exploit the advantages of the oscillometric algorithms and circumvent their limitations. The proposed fusion method is based on the computation of the weighted arithmetic mean of the oscillometric algorithms estimates, and the weights are obtained using a Bayesian approach by minimizing the mean square error. The proposed approach is used to fuse four different oscillometric blood pressure estimation algorithms. The performance of the proposed method is evaluated on a pilot dataset of 150 oscillometric recordings from 10 subjects. It is found that the mean error and standard deviation of error are reduced relative to the individual estimation algorithms by up to 7 mmHg and 3 mmHg in estimation of systolic pressure, respectively, and by up to 2 mmHg and 3 mmHg in estimation of diastolic pressure, respectively.

Estimated confidence interval from single blood pressure measurement based on algorithmic fusion.

BACKGROUND: Current oscillometric blood pressure measurement devices generally provide only single-point estimates for systolic and diastolic blood pressures and rarely provide confidence ranges for these estimates. A novel methodology to obtain confidence intervals (CIs) for systolic blood pressure (SBP) and diastolic blood pressure (DBP) estimates from a single oscillometric blood pressure measurement is presented. METHODS: The proposed methodology utilizes the multiple regression technique to fuse optimally a set of SBP and DBP estimates obtained through different algorithms. However, the set of SBP and DBP estimates is a small number to determine the CI of each individual subject. To address this issue, the weighted bootstrap approach based on the multiple regression technique was used to generate a pseudo sample set for the SBP and the DBP. In this paper, the multiple regression technique can estimate the best-fitting surface of an efficient function that relates the input sample set as an independent vector to the auscultatory nurse measurement as a dependent vector to estimate regression coefficients. Consequently, the coefficients are assigned to an eight-sample set obtained from the fusion of different algorithms as optimally weighted parameters. CIs are also estimated using the conventional methods on the set of fused SBP and DBP estimates for comparison purposes. RESULTS: The proposed method was applied to an experimental dataset of 85 patients. The results indicated that the proposed approach provides better blood pressure estimates than the existing algorithms and, in addition, is able to provide CIs for a single measurement. CONCLUSIONS: The CIs derived from the proposed scheme are much smaller than those calculated by conventional methods except for the pseudo maximum amplitude-envelope algorithm for both the SBP and the DBP, probably because of the decrease in the standard deviation through the increase in the pseudo measurements using the weighted bootstrap method for each subject. The proposed methodology is likely the only one currently available that can provide CIs for single-sample blood pressure measurements.

Oscillometric Blood Pressure Estimation: Past, Present, and Future.

The use of automated blood pressure (BP) monitoring is growing as it does not require much expertise and can be performed by patients several times a day at home. Oscillometry is one of the most common measurement methods used in automated BP monitors. A review of the literature shows that a large variety of oscillometric algorithms have been developed for accurate estimation of BP but these algorithms are scattered in many different publications or patents. Moreover, considering that oscillometric devices dominate the home BP monitoring market, little effort has been made to survey the underlying algorithms that are used to estimate BP. In this review, a comprehensive survey of the existing oscillometric BP estimation algorithms is presented. The survey covers a broad spectrum of algorithms including the conventional maximum amplitude and derivative oscillometry as well as the recently proposed learning algorithms, model-based algorithms, and algorithms that are based on analysis of pulse morphology and pulse transit time. The aim is to classify the diverse underlying algorithms, describe each algorithm briefly, and discuss their advantages and disadvantages. This paper will also review the artifact removal techniques in oscillometry and the current standards for the automated BP monitors.

Model of human breathing reflected signal received by PN-UWB radar.

Human detection is an integral component of civilian and military rescue operations, military surveillance and combat operations. Human detection can be achieved through monitoring of vital signs. In this article, a mathematical model of human breathing reflected signal received in PN-UWB radar is proposed. Unlike earlier published works, both chest and abdomen movements are considered for modeling the radar return signal along with the contributions of fundamental breathing frequency and its harmonics. Analyses of recorded reflected signals from three subjects in different postures and at different ranges from the radar indicate that ratios of the amplitudes of the harmonics contain information about posture and posture change.

Coefficient-free blood pressure estimation based on pulse transit time-cuff pressure dependence.

Oscillometry is a popular technique for automatic estimation of blood pressure (BP). However, most of the oscillometric algorithms rely on empirical coefficients for systolic and diastolic pressure evaluation that may differ in various patient populations, rendering the technique unreliable. A promising complementary technique for automatic estimation of BP, based on the dependence of pulse transit time (PTT) on cuff pressure (CP) (PTT-CP mapping), has been proposed in the literature. However, a theoretical grounding for this technique and a nonparametric BP estimation approach are still missing. In this paper, we propose a novel coefficient-free BP estimation method based on PTT-CP dependence. PTT is mathematically modeled as a function of arterial lumen area under the cuff. It is then analytically shown that PTT-CP mappings computed from various points on the arterial pulses can be used to directly estimate systolic, diastolic, and mean arterial pressure without empirical coefficients. Analytical results are cross-validated with a pilot investigation on ten healthy subjects where 150 simultaneous electrocardiogram and oscillometric BP recordings are analyzed. The results are encouraging whereby the mean absolute errors of the proposed method in estimating systolic and diastolic pressures are 5.31 and 4.51 mmHg, respectively, relative to the Food and Drug Administration approved Omron monitor. Our work thus shows promise toward providing robust and objective BP estimation in a variety of patients and monitoring situations.

Augmented blood pressure measurement through the noninvasive estimation of physiological arterial pressure variability.

Current noninvasive blood pressure (BP) measurement methods, such as the oscillometric method, estimate the systolic and diastolic blood pressure (SBP and DBP) at two random instants in time and do not take into account the natural variability in BP. The standard for automated BP devices sets a maximum allowable system error of ±5 mmHg, even though natural BP variability often exceeds these limits. This paper proposes a new approach using simultaneous recordings of the oscillometric and continuous arterial pulse waveforms to augment the conventional noninvasive measurement by providing (1) the mean SBP and DBP over the measurement interval and the associated confidence intervals of the mean, (2) the standard deviation of SBP and DBP over the measurement interval, which indicates the degree of fluctuation in BP and (3) an indicator as to whether or not the oscillometric reading is an outlier. Recordings with healthy subjects demonstrate the potential utility of this approach to characterize BP, to detect outlier measurements, and that it does not suffer from bias relative to the conventional oscillometric method.

Electrocardiogram-assisted blood pressure estimation.

Accurate automatic noninvasive assessment of blood pressure (BP) presents a challenge due to conditions like arrhythmias, obesity, and postural changes that tend to obfuscate arterial amplitude pulsations sensed by the cuff. Researchers tried to overcome this challenge by analyzing oscillometric pulses with the aid of a higher fidelity signal-the electrocardiogram (ECG). Moreover, pulse transit time (PTT) was employed to provide an additional method for BP estimation. However, these methods were not fully developed, suitably integrated, or tested. To address these issues, we present a novel method whereby ECG-assisted oscillometric and PTT (measured between ECG R-peaks and maximum slope of arterial pulse peaks) analyses are seamlessly integrated into the oscillometric BP measurement paradigm. The method bolsters oscillometric analysis (amplitude modulation) with more reliable ECG R-peaks provides a complementary measure with PTT analysis (temporal modulation) and fuses this information for robust BP estimation. We have integrated this technology into a prototype that comprises a BP cuff with an embedded conductive fabric ECG electrode, associated hardware, and algorithms. A pilot study has been undertaken on ten healthy subjects (150 recordings) to validate the performance of our prototype against United States Food and Drug Administration approved Omron oscillometric monitor (HEM-790IT). Our prototype achieves mean absolute difference of less than 5 mmHg and grade A as per the British Hypertension Society protocol for estimating BP, with the reference Omron monitor.

Blood pressure estimation using maximum slope of oscillometric pulses.

A new oscillometric pulse index (OPI) derived from the maximum slope (MS) of each pulse in the oscillometric blood pressure waveform is proposed for blood pressure estimation. Maximum slope for each pulse is obtained using the first derivative of the pulse and an envelope of the values corresponding to the maximum slopes is obtained. The maximum of the envelope is taken as the mean arterial pressure (MAP) and the systolic blood pressure (SBP) and diastolic blood pressure (DBP) estimates are obtained as a fraction of the MAP, similar to the traditional maximum amplitude algorithm (MAA). The proposed algorithm is tested on 18 healthy subjects. The MAP, SBP and DBP estimates obtained from the proposed algorithm are compared with those obtained from a commercial blood pressure device and with the estimates obtained using the MAA and morphological qualitative measures available in the literature.

Blood pressure estimation using oscillometric pulse morphology.

A novel pulse morphology-based approach for estimation of blood pressure from non-invasive oscillometric blood pressure measurement is presented. Quantitative measures that describe the pulse morphology are utilized to obtain the estimates of mean arterial, systolic, and diastolic pressures. Preliminary results obtained from a small set of measurements are used to demonstrate the feasibility of the proposed approach. The estimates obtained through pulse morphology-based approach is compared with those obtained from a commercial blood pressure device.