Static state hemodynamic variables estimation model for the moving-actuator type total artificial heart. Part II - Aortic pressure estimation

Aortic pressure (AoP) estimation is a very important study for the artificial heart. In this paper, we developed a AoP estimation model for the moving-actuator type total artificial heart (MH-TAH) that was being developed at Seoul National University Hospital. The proposed model is simple and provides beat-by-beat mean AoP estimation. Moreover, it uses non-invasively acquired signals. Model parameters were adjusted with in vitro data by least mean square (LMS) algorithm. Results showed that the proposed scheme gives a mean estimation error of about 8 (mmHg). This ensures the suitability of the proposed model. The proposed approach can also be applied to the model setup of pulmonary arterial pressure (PAP) estimation by using the symmetric characteristics between AoP and PAP.     

Signal processing technique for non-invasive real-time estimation of cardiac output by inductance cardiography (thoracocardiography)

Inductance cardiography (thoracocardiography) non-invasively monitors changes in stroke volume by recording ventricular volume curves with an inductive plethysmographic transducer encircling the chest at the level of the heart. Clinical application of this method has been hampered, as data analysis has not been feasible in real time. Therefore a novel, real-time signal processing technique for inductance cardiography has been developed. Its essential concept consists in performance of multiple tasks by several, logically linked signal processing modules that have access to common databases. Based on these principles, a software application was designed that performs acquisition, display, filtering and ECG-triggered ensemble averaging of inductance signals and separates cardiogenic waveforms from noise related to respiration and other sources. The resulting ventricular volume curves are automatically analysed. Performance of the technique for monitoring cardiac output in real time was compared with thermodilution in four patients in an intensive care unit. The bias (mean difference) among 76 paired thoracocardiographic and thermodilution derived changes in cardiac output was 0%; limits of agreement (±2 SD of the bias) were ±25%. It is concluded that the proposed signal processing technique for inductance cardiography holds promise for non-invasive, real-time estimation of changes in cardiac output.     

Closed-form kinetic parameter estimation solution to the truncated data problem

In a dedicated cardiac single photon emission computed tomography (SPECT) system, the detectors are focused on the heart and the background is truncated in the projections. Reconstruction using truncated data results in biased images, leading to inaccurate kinetic parameter estimates. This paper has developed a closed-form kinetic parameter estimation solution to the dynamic emission imaging problem. This solution is insensitive to the bias in the reconstructed images that is caused by the projection data truncation. This paper introduces two new ideas: (1) it includes background bias as an additional parameter to estimate, and (2) it presents a closed-form solution for compartment models. The method is based on the following two assumptions: (i) the amount of the bias is directly proportional to the truncated activities in the projection data, and (ii) the background concentration is directly proportional to the concentration in the myocardium. In other words, the method assumes that the image slice contains only the heart and the background, without other organs, that the heart is not truncated, and that the background radioactivity is directly proportional to the radioactivity in the blood pool. As long as the background activity can be modeled, the proposed method is applicable regardless of the number of compartments in the model. For simplicity, the proposed method is presented and verified using a single compartment model with computer simulations using both noiseless and noisy projections.     

Estimation of the following cardiac output using sympathetic tone and hemodynamics for the control of a total artificial heart.

A sympathetic neurogram is potentially useful for the development of a real time total artificial heart (TAH) control system. We used sympathetic tone and hemodynamic derivatives to estimate the following cardiac output in acute animal experiments using adult mongrel dogs. Moving averages of the mean left atrial pressure and mean aortic pressure were used as parameters of the preload and afterload, respectively. Renal sympathetic nerve activity (RSNA) was employed as a parameter of sympathetic tone. Equations for the following cardiac output were calculated using multiple linear regression analysis of the time series data. A significant correlation was observed between the estimated and following measured cardiac output. These results suggest the potential usefulness of the sympathetic neurogram for the real time TAH automatic control system.     

Cardiac output requirements and maximum dimensions for a neonate total artificial heart.

Two equally important issues need to be addressed during the early stages of the design of an implantable total artificial heart (TAH): proper anatomical fit and cardiac output capacity. As part of a first-time feasibility study to develop a neonate-size TAH, two studies were conducted to establish useful anatomical and physiological standards. The first (Study A) was conducted to determine the maximum dimensions of a neonate-size TAH. Twelve preserved hearts from full-term neonates with the hypoplastic left heart syndrome were examined. A second study (Study B) was designed to determine the acceptable minimum stroke volume compatible with minimum neonate cardiac output requirements. This study was based on a combination of: a) reported cardiac output studies in healthy term neonates, and term neonates with heart failure, b) body weight range, and c) limiting factors of TAH technology, e.g., valvular regurgitation and leveling off of the maximum cardiac output value at a specific heart rate and filling pressure. The proposed neonatal standards for TAH technology are presented.     

Enhanced cardiac thermal dilution measurement of cardiac output, volumes, regurgitation, valve effective diameters, ventricular power and efficiency -- Feasibility analysis using digital simulation.

Cardiac output is measured by the thermal dilution method which uses a quadruple lumen catheter, with a thermistor on the tip, through the right atrium, right ventricle and into the pulmonary artery. Cold saline is injected into the right atrium and the resulting pulmonary artery temperature profile is integrated. The same procedure performed with three thermistors and three pressure sensors located on the catheter to measure temperature and pressure in the atrium, ventricle and artery respectively will produce a set of temperature and pressure curves with shapes determined by injectate temperature, injectate volume, heart rate, systolic time interval, body temperature, cardiac output, volumes, flow rates and valve openings. A digital computer program has been developed to optimize the fit of a lumped parameter model to the thermodilution curves in order to determine heart rate, systolic time as a fraction of cardiac cycle, right atrial systolic and diastolic volumes, ventricular systolic and diastolic volumes, cardiac output, inflow valve forward and reverse flow rates and effective diameters, outflow valve forward and reverse flow rates and effective diameters, ventricular power and efficiency. The program has been tested over a range of operating conditions including noise in the temperature and pressure signals, randomly varying heart rate and cardiac cycle. All of the data for the tests were produced by a digital computer simulation of a pulsatile artificial heart. The results of these tests indicate that the enhanced thermal dilution analysis method is feasible.     

Heat and mass transfer of a thermal indicator in pulsatile flow through the cardio-pulmonary system. II. Identification of cardiac output

Hamilton's celebrated formula for cardiac output measurement is simple but its validity is dependent on several methodologic requirements which are not generally fulfilled, particularly in thermal dilution. A quite different method, based on a physico-mathematical model of the indicator dispersion in the circulation, is proposed. It allows direct derivation of cardiac output once the model's parameters have been identified. Combined deconvolution and least squares procedures are used with truncated data for this identification. Numerical tests and application to clinical observations are presented. Both limitations and possibilities of further developments in estimation of pulsatile flow conditions from TD technique are discussed.     

Ovalis TAH: development and in vitro testing of a new electromechanical energy converter for a total artificial heart

A new electromechanical energy converting system has been developed to yield an efficient and durable orthotopic total artificial heart (TAH). The energy converter we developed transforms the unidirectional rotational motion of the motor into a longitudinal forward-reverse movement of an internal geared oval, linked directly to pusher plates on both sides. To ensure a permanent positive connection between the drive gear and the internally geared wheel, a ball bearing runs inside an oval shaped guide track. Motor, gear unit, and conical pusher plates are seated between alternately ejecting and filling ventricles. The unidirectional motion of the brushless DC motor affords easier motor control, reduces energy demand, and ensures longer life of the motor when compared with a bidirectional motion system. In vitro testing has been performed on a mock circulation loop. The overall system efficiency of the TAH Ovalis was 27-39% (mean, 36%) for the pump output range of 2-7 L/min. The maximum output of 7 L/min can be obtained with a pump rate of 130 min(-1) and an afterload pressure of 140 mm Hg. For an average sized human with a mean cardiac output of 6 L/min at a mean aortic pressure of 120 mm Hg, 5 watts of input power would be required. The size of the prototype is 560 cm3, the weight is 950 g. Our first in vitro studies demonstrated the excellent efficiency and pump performance of this new electromechanical energy converter. The results prove the feasibility of this new concept's use as an energy converter for a total artificial heart.     

Clinical use of the total artificial heart

We report here our first experience with the use of a total artificial heart in a human being. The heart was developed at the University of Utah, and the patient was a 61-year-old man with chronic congestive heart failure due to primary cardiomyopathy, who also had chronic obstructive pulmonary disease. Except for dysfunction of the prosthetic mitral valve, which required replacement of the left-heart prosthesis on the 13th postoperative day, the artificial heart functioned well for the entire postoperative course of 112 days. The mean blood pressure was 84 +/- 8 mm Hg, and cardiac output was generally maintained at 6.7 +/- 0.8 liters per minute for the right heart and 7.5 +/- 0.8 for the left, resulting in postoperative diuresis and relief of congestive failure. The postoperative course was complicated by recurrent pulmonary insufficiency, several episodes of acute renal failure, episodes of fever of unidentified cause (necessitating multiple courses of antibiotics), hemorrhagic complications of anticoagulation, and one generalized seizure of uncertain cause. On the 92nd postoperative day, the patient had diarrhea and vomiting, leading to aspiration pneumonia and sepsis. Death occurred on the 112th day, preceded by progressive renal failure and refractory hypotension, despite maintenance of cardiac output. Autopsy revealed extensive pseudomembranous colitis, acute tubular necrosis, peritoneal and pleural effusion, centrilobular emphysema, and chronic bronchitis with fibrosis and bronchiectasis. The artificial heart system was intact and uninvolved by thrombosis or infectious processes. This experience should encourage further clinical trials with the artificial heart, but we emphasize that the procedure is still highly experimental. Further experience, development, and discussion will be required before more general application of the device can be recommended.     

A data mining framework for time series estimation

Time series estimation techniques are usually employed in biomedical research to derive variables less accessible from a set of related and more accessible variables. These techniques are traditionally built from systems modeling approaches including simulation, blind decovolution, and state estimation. In this work, we define target time series (TTS) and its related time series (RTS) as the output and input of a time series estimation process, respectively. We then propose a novel data mining framework for time series estimation when TTS and RTS represent different sets of observed variables from the same dynamic system. This is made possible by mining a database of instances of TTS, its simultaneously recorded RTS, and the input/output dynamic models between them. The key mining strategy is to formulate a mapping function for each TTS–RTS pair in the database that translates a feature vector extracted from RTS to the dissimilarity between true TTS and its estimate from the dynamic model associated with the same TTS–RTS pair. At run time, a feature vector is extracted from an inquiry RTS and supplied to the mapping function associated with each TTS–RTS pair to calculate a dissimilarity measure. An optimal TTS–RTS pair is then selected by analyzing these dissimilarity measures. The associated input/output model of the selected TTS–RTS pair is then used to simulate the TTS given the inquiry RTS as an input. An exemplary implementation was built to address a biomedical problem of noninvasive intracranial pressure assessment. The performance of the proposed method was superior to that of a simple training-free approach of finding the optimal TTS–RTS pair by a conventional similarity-based search on RTS features.     

Comparison between artificial neural network and multilinear regression models in an evaluation of cognitive workload in a flight simulator

In this study, the performances of artificial neural network (ANN) analysis and multilinear regression (MLR) model-based estimation of heart rate were compared in an evaluation of individual cognitive workload. The data comprised electrocardiography (ECG) measurements and an evaluation of cognitive load that induces psychophysiological stress (PPS), collected from 14 interceptor fighter pilots during complex simulated F/A-18 Hornet air battles. In our data, the mean absolute error of the ANN estimate was 11.4 as a visual analog scale score, being 13–23% better than the mean absolute error of the MLR model in the estimation of cognitive workload.     

应用神经网络检测叶轮式人工心脏输出流量的可行性研究

简介人工心脏输出流量的几种测量方法,并针对叶轮式人工心脏,提出应用神经网络进行检测的方法。根据实验结果,应用神经网络进行检测具有可行性。     

Exposure and organ dose estimation in diagnostic radiology

This paper discusses a methodology which uses a specially developed computer program that enables estimation of output parameters of an x-ray machine from a single test exposure. Exposure at skin entrance values can be estimated, as well as using the data from the program for organ dose estimates. To perform the estimation procedure, curves and analytical expressions for the curves are presented for conversion of half-value layers to total filtration and for conventional mR/mAs output curves. Results are given showing that the estimation procedure is reasonably accurate.     

An improved windowing technique for heart rate variability power spectrum estimation

Spectral analysis of heart rate variability (HRV) is an accepted method for assessment of cardiac autonomic function and its relationship to numerous disorders and diseases. Discrete Fourier transform (DFT) based methods are widely used for their easy applicability, computational speed and the possibility for direct interpretation of results. This study assesses the limitations of windowing of the RR interval series for power spectrum estimation using DFT for heart rate variability studies. The mean value of the RR interval series should be subtracted before windowing. This may leave a small residual DC component after windowing, but the RR interval series is properly tapered to zero at the beginning and end of the window. However, if the windowed RR interval series has a non-zero mean then subtracting this mean will create an abrupt transition between the first and last data points, and the padded zeros. This is equivalent to superimposing upon the RR interval series a rectangular pulse of the same length as the window, with a height equal to the subtracted mean value. In the present paper an approach to overcome the above effects of the window in reducing the signal energy and introducing low frequency components into the spectrum has been suggested and incorporated. Results have been compared for DC biasing of windowed data spectrum, bias of windowed data removed by subtraction of mean from data, and data preprocessed to remove windowed mean level and to maintain mean power. Thus the preprocessing of RR interval series with this method improves the accuracy of HRV analysis methods. The study was carried out by smoothing the complete RR interval series by single Hann window and by 50% overlapping the data segments of 256 data points followed by DFT. Overlapping the data segments provides equal weight to all values in the RR interval series and a smoothed spectral estimate with clearly dominant peaks in low- and high-frequency regions.     

An improved windowing technique for heart rate variability power spectrum estimation

Spectral analysis of heart rate variability (HRV) is an accepted method for assessment of cardiac autonomic function and its relationship to numerous disorders and diseases. Discrete Fourier transform (DFT) based methods are widely used for their easy applicability, computational speed and the possibility for direct interpretation of results. This study assesses the limitation of windowing of the RR interval series of power spectrum estimation using DFT for heart rate variability studies. The mean value of the RR interval series should be subtracted before windowing. This may leave a small residual DC component after windowing, but the RR interval series is properly tapered to zero at the beginning and end of the window. However, if the windowed RR interval series has a non-zero mean then subtracting this mean will create an abrupt transition between the first and last data points, and the padded zeros. This is equivalent to superimposing upon the RR interval series a rectangular pulse of the same length as the window, with a height equal to the subtracted mean value. In the present paper an approach to overcome the above effects of the window in reducing the signal energy and introducing the low frequency component into spectrum has been suggested and incorporated. Result have been compared for DC biasing of windowed data spectrum, bias of windowed data removed by substraction of mean data, and data processed to remove windowed mean level and to maintain mean power. Thus the preprocessing of RR interval series with this method improves the accuracy of HRV analysis methods. The study was carried out by smoothing the complete RR interval series by single Hann window and by 50% overlapping the data segments of 256 data points followed by the DFT. Overlapping the data segments provides equal weight to all values in the RR interval series and smoothed spectral estimate with clearly dominant peaks in low- and high-frequency regions.     

轴流泵式全人工心脏的体外测试及对负荷反应特性

目的 在体外模拟循环台测试轴流泵式全人工心脏的基本负荷反应特性，为探索生理性控制方案提供基础。方法 轴流泵式全人工心脏样机采用2个轴流泵共同设置在刚性外壳中，直径65 mm，长度70 mm。于模拟循环台上串联连接组成全人工心脏的2个轴流泵，在外周动脉和肺动脉阻力不变的条件下观测前、后负荷变化对心脏输出量的影响。结果 在前负荷固定不变的条件下，增加后负荷时心脏输出流量逐步下降，增大泵转速可对抗后负荷对输出量的抑制，泵转速设定为右心泵8 500 r/min、左心泵11 000 r/min时，心脏输出压力为13.3 kPa（100 mmHg）和输出量6 L/min。当后负荷增大到26.7 kPa（200 mmHg）时心输出量下降为0 L/min。在后负荷固定不变的条件下，前负荷的增加不导致心脏输出量明显改变。设定左心泵转速为11 000 r/min、右心泵转速8 500 r/min时前负荷由0.27 kPa（2 mmHg）增加到1.87 kPa（14 mmHg），流量基本维持在7 L/min。结论 轴流泵式全人工心脏对后负荷增加表现出明显的流量抑制趋势，此趋势可通过调节泵转速改善。轴流泵式全人工心脏对前负荷反应不明显，有别于自然心脏，其机制及调节意义尚待进一步研究。     

Online estimation of cardiac output from respiratory data using a gradient method

This paper presents a method for estimating cardiac output, using only respiratory measurements and a mathematical model fo the respiratory system. Direct measurement of cardiac output requires the surgical insertion of a flow-meter around the pulmonary artery, and hence is restricted to procedures with experimental animals. In man, cardiac output is generally estimated using indirect means, such as by measuring the concentration of a dye in the arterial circulation as a result of its injection into the venous circulation. The degree cf dilution of the dye (after adequate mixing) can be used to estimate the flow. The technique presented in this paper is also an indirect noninvasive procedure based on CO₂ measurements. It differs from other indirect methods primarily in that it uses an on-line dynamic model of the respiratory system and makes use of a parameter-estimation algorithm. The method is based on the fact that cardiac output is a parameter in the respiratory system. A mathematical model of this system is simulated on a computer and forced (on-line) with a signal proportional to the subject's total ventilation. the output of the model is a signal representing the end-tidal exhaled partial pressure of carbon dioxide, PCO₂. The computer generated end-tidal PC O₂ is compared with the measured PC O₂ obtained from CO₂ analyser. The comparison is based on the squared difference between these two signals at the end of each breath. This error measure is minimised automatically by the computer adjusting the model cardiac output. Experimental procedures and computer techniques are presented. The resulting values of cardiac output in the model were compared with experimental data obtained using dye-dilution techniques with five mongrel dogs weighing 10–15 kg. The computer-generated estimates are shown to agree with experimental data to within 15%, with over half of the estimates agreeing within 4%.     

In vitro testing of a new driver for the pneumatic total artificial heart with inherent cardiac output measuring system

Based upon the Utah pneumatic driver, a new model for use in animal experiments was designed. It enabled measurement of cardiac output, optimal percentage of systole as well as diagnosis of some of the causes of the decrease of cardiac output of the pneumatic total artificial heart, such as valvular stenosis due to pannus formation. This driver is based on the expansion of a known amount of 'driving-air' during the systolic period. In the calculation of the cardiac output, the in vitro experiments yielded an error range of +/- 3.5%. The analysis of the driving-air pressure tracing during its decompression (systolic period) gave accurate information about the optimal percentage of systole for each frequency and the inflow and outflow resistances.     

Minute-to-minute covariations in cardiovascular activity of conscious dogs.

Cardiovascular activity of chronically instrumented conscious dogs was monitored continuously during daily sessions of rest or of intermittent aversive stimulation. Data analysis of minute-to-minute averages revealed that cardiovascular variables changed in patterns, rather than as isolated independent events. Variations in cardiac output were highly positively correlated with concurrent variations in heart rate in all subjects under both conditions (mean r = +0.93). Variations in heart rate were two to five times as great as stroke volume, which was remarkably constant (coefficient of variation averaged only 4.6%). Variations in mean arterial pressure were consistently correlated with the variations in cardiac output (mean r = + 0.66) and heart rate (mean r = +0.68), but were poorly correlated with the small changes in stroke volume (mean r = -0.17) and total peripheral resistance (mean r = -0.16).     

Fetal ultrasound image segmentation system and its use in fetal weight estimation

A semi-automated fetal ultrasound image segmentation system is developed to improve the estimation of fetal weight (EFW). Four standardized fetal parameters are measured by the proposed segmentation system: biparietal diameter, head circumference, abdominal circumference and femur length. Computerized measurements of 215 fetuses are compared with manual measurements in term of fitness analysis and difference analysis. Among 215 cases, computerized measurements of 103 fetuses within 3 days of delivery are utilized in the fetal weight estimation. The EFW based on computerized measurements and manual measurements are compared by using regression analysis, artificial neural network and support vector regression. By using different estimation methods, the computerized measurements decrease the EFW errors about 40–70 g. The lowest mean absolute percentage error of EFW decrease from 6.71% for manual measurements to 4.66% for computerized measurements. The proposed fetal ultrasound image segmentation system can provide more accurate EFW in antepartum examination.