[Show abstract][Hide abstract]ABSTRACT: Objective:
Heart rate turbulence (HRT) has been successfully explored for cardiac risk stratification. While HRT is known to be influenced by the heart rate (HR) and the coupling interval (CI), non-concordant results have been reported on how the CI influences HRT. The purpose of this study is to investigate HRT changes in terms of CI and HR by means of a specially designed protocol.
A dataset was acquired from 11 patients with structurally normal hearts for which CI was altered by different pacing trains and HR by isoproterenol during electrophysiological study (EPS). The protocol was designed so that, first, the effect of HR changes on HRT, and, second, the combined effect of HR and CI could be explored. As a complement to the EPS dataset, a database of 24-h Holters from 61 acute myocardial infarction (AMI) patients was studied for the purpose of assessing risk. Data analysis was performed by using different nonlinear ridge regression models, and the relevance of model variables was assessed using resampling methods. The EPS subjects, with and without isoproterenol, were analyzed separately.
The proposed nonlinear regression models were found to account for the influence of HR and CI on HRT, both in patients undergoing EPS without isoproterenol and in low-risk AMI patients, whereas this influence was absent in highrisk AMI patients. Moreover, model coefficients related to CI were not statistically significant, p > 0:05, on EPS subjects with isoproterenol.
The observed relationship between CI and HRT, being in agreement with the baroreflex hypothesis, was statistically significant (p < 0:05), when decoupling the effect of HR and normalizing the CI by the HR.
The results of this work can help to provide new risk indicators that take into account physiological influence on HRT, as well as to model how this influence changes in different cardiac conditions.
[Show abstract][Hide abstract]ABSTRACT: Objective:
The atrioventricular (AV) node plays a central role in atrial fibrillation (AF) as it influences the conduction of impulses from the atria into the ventricles. In the present paper, the statistical dual pathway AV node model, previously introduced by us, is modified so that it accounts for atrial impulse pathway switching even if the preceding impulse did not cause a ventricular activation.
The proposed change in model structure implies that the number of model parameters subjected to maximum likelihood estimation is reduced from five to four. The model is evaluated using the data acquired in the RATe control in Atrial Fibrillation (RATAF) study, involving 24- h ECG recordings from 60 patients with permanent AF.
When fitting the models to the RATAF database, similar results were obtained for both the present and the previous model, with a median fit of 86%. The results show that the parameter estimates characterizing refractory period prolongation exhibit considerably lower variation when using the present model, a finding that may be ascribed to fewer model parameters.
The new model maintains the capability to model RR intervals, while providing more reliable parameters estimates.
The model parameters are expected to convey novel clinical information, and may be useful for predicting the effect of rate control drugs.
Article · Dec 2015 · IEEE Transactions on Biomedical Engineering
[Show abstract][Hide abstract]ABSTRACT: The atrioventricular (AV) node plays a central role during atrial fibrillation (AF). We have recently proposed a statistical AV node model defined by parameters characterizing the arrival rate of atrial impulses, the probability of an impulse choosing the slower of the two AV nodal pathways, the refractory periods of the pathways, and the prolongation of refractory periods. All model parameters are estimated from the RR series using maximum likelihood estimation, except for the mean arrival rate of atrial impulses which is estimated by the AF frequency derived from the f-waves. The aim of this study is to assess the relationship between the probability γ of an atrial impulse to arrive at the slow pathway with the probability α (used in the model) of an impulse to pass through that pathway. A theoretical equation was derived to relate α with γ and viceversa, highlighting the dependence on both refractory periods and their prolongation. Results based on simulations show that the equation was correct, with an average absolute error of 0.0034 ± 0.0008.
[Show abstract][Hide abstract]ABSTRACT: Although patients undergoing hemodialysis treatment often suffer from cardiovascular disease, monitoring of cardiac rhythm is not performed on a routine basis. Without requiring any extra sensor, this study proposes a method for extracting a cardiac signal from the built-in extracorporeal venous pressure sensor of the hemodialysis machine. The extraction is challenged by the fact that the cardiac component is much weaker than the pressure component caused by the peristaltic blood pump. To further complicate the extraction problem, the cardiac component is difficult to separate when the pump and heart rates coincide. The proposed method estimates a cardiac signal by subtracting an iteratively refined blood pump model signal from the signal measured at the extracorporeal venous pressure sensor. The method was developed based on simulated pressure signals, and evaluated on clinical pressure signals acquired during hemodialysis treatment. The heart rate estimated from the clinical pressure signal was compared to that derived from a photoplethysmographic (PPG) reference signal, resulting in a difference of 0.070.84 beats per minute. The accuracy of the heartbeat occurrence times was studied for different strengths of the cardiac component, using both clinical and simulated signals. The results suggest that the accuracy is sufficient for analysis of heart rate and certain arrhythmias.
Article · Dec 2014 · IEEE transactions on bio-medical engineering
[Show abstract][Hide abstract]ABSTRACT: Purpose: The atrial fibrillatory rate (AFR) has been suggested to be predictive of conversion to sinus rhythm (SR). We analyzed the effects on AFR and related variables after infusion with the combined potassium and sodium channel blocker AZD7009, known to be highly effective in converting AF of <90 days duration to SR.
Methods: Patients with AF of <90 days duration were randomized to one of three intravenous dose regimens of AZD7009 or to placebo. The study population consisted of 35 patients. Fourteen converters to SR in two 15 min regimens were matched to non-converters. Another 21 patients on an AZD7009 30 min regimen converted to SR and 21 did not convert. ECG was recorded continuously from 5 minutes before and up to 5 hours after the infusion. After QRST cancellation the resulting atrial fibrillatory signal was subjected to spectral analysis involving noise-selective averaging in consecutive 1-min segments. The AFR, the exponential decay (ED) and the standard deviation of the AFR (AFR-SD) were studied.
Results: The mean AFR at baseline was 397±57 (range 253-584) fibrillations per minute (fpm) and 410±33 (range 363 - 469) fpm in patients randomized to AZD7009 and placebo, respectively. The AFR decreased significantly within 2 minutes of the start of infusion and the mean AFR before conversion was 231 fpm, having decreased by -162 fpm (41%). In non-converters the mean AFR at the end of infusion was 296 fpm, having decreased by -104 fpm (26%). The rate of decrease was higher in converters, -88 vs. -66 fpm at 5 min, p=0.02, and -133 vs. -111 fpm at 10 min, p=0.048. The median time to conversion on AZD7009 was 19 (8-64) minutes. There were no converters on placebo. The AFR-SD and the ED both decreased as signs of higher AF rhythm organization. For placebo the mean AFR was 410±33 fpm before and 409±30 fpm after the infusion. A small left atrial area was the only of 25 tested variables that predicted conversion to SR in the 30-min AZD7009 regimen, in addition to treatment with AZD7009.
Conclusion: AZD7009 produced a significantly more rapid decrease of the AFR in converters than in non-converters, but the AFR at baseline was not predictive of conversion. A small left atrial area was the only baseline predictor of conversion to SR.
[Show abstract][Hide abstract]ABSTRACT: The atrioventricular (AV) node plays a central role during atrial fibrillation (AF). We have recently proposed a statistical AV node model defined by parameters characterizing the arrival rate of atrial impulses, the probability of an impulse choosing either one of the dual AV nodal pathways, the refractory periods of the pathways, and the prolongation of refractory periods. All model parameters are estimated from the RR series using maximum likelihood (ML) estimation, except for the mean arrival rate of atrial impulses which is estimated by the AF frequency derived from the f-waves. The aim of this study is to present a unified approach to ML estimation which also involves the shorter refractory period, thus avoiding our previous Poincaré plot analysis which becomes biased. In addition, the number of RR intervals required for accurate parameter estimation is presented. The results show that the shorter refractory period can be accurately estimated, and that the resulting estimates converge to the true values when about 500 RR intervals are available.
Article · Jul 2013 · Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
[Show abstract][Hide abstract]ABSTRACT: The goal of the study is to determine whether photoplethysmography (PPG) can replace ECG-based detection of heart rate turbulence. Using the PPG, classification of ventricular premature beats (VPBs) is accomplished with a linear classifier. The two conventional parameters turbulence onset and slope are studied together with a recently introduced parameter characterizing turbulence shape. Performance is studied on a dataset with 4131 VPBs, recorded from a total of 27 patients in different clinical contexts (hemodialysis treatment, intensive care monitoring, and electrophysiological study). The sensitivity/ specificity of VPB classification was found to be 90.5/99.9%, with an accuracy of 99.3%, suggesting that classification of VPBs can be reliable made from the PPG. The main difference between the two types of turbulence analysis stems from the fact that the pulse transit time varies largely immediately after the VPB. Out of the 22 patients which had a sufficient number of VPBs, the outcome of ECG- and PPG-based analysis was identical in 21. It is concluded that the PPG may serve as a surrogate technique for the ECG in turbulence analysis.
Article · Jun 2013 · IEEE transactions on bio-medical engineering
[Show abstract][Hide abstract]ABSTRACT: The purpose of the present study is to evaluate the effect of rate control drugs on the AV node characteristics during atrial fibrillation (AF) using a model-based approach. A statistical model of the AV nodal function is employed, defined by parameters which characterize the arrival rate of atrial impulses, the refractoriness of the fast and the slow AV-nodal pathway and the probability of atrial impulse to pass through either of the two pathways. The RATAF (RATe control in Atrial Fibrillation) study database consists of recordings from 60 patients with permanent AF at baseline and on treatment with metoprolol, verapamil, diltiazem and carvedilol, respectively. The resulting model parameter estimates indicate that the refractory period of the slow pathway as well as that of the fast pathway increased significantly during treatment with all four drugs. The results suggest that the proposed AV-node model can be used for non-invasive evaluation of the effect of rate control drugs.
[Show abstract][Hide abstract]ABSTRACT: The goal of this study is to determine whether peripheral blood volume fluctuations triggered by ventricular premature beats (VPBs) are significantly related to hypotensive symptoms during dialysis treatment. Patients treated with hemodialysis often suffer from cardiovascular disorders and uremic neuropathy, increasing the propensity to homeostatic imbalance that, in turn, may result in intradialytic hypotension, cramps, nausea, dizziness, headache and other complications. VPBs, being abundant in hemodialysis patients, can be viewed as an internal disturbance leading to imbalance through acute blood pressure drop and prolonged tissue deoxygenation. The present study investigates and quantifies VPB-induced relative peripheral blood volume changes, measured from the fingertip photoplethysmographic (PPG) waveform, and their significance for characterization of physiological recovery of a disturbed circulatory state. The mean decrease in PPG amplitude, corresponding to an initial post-ectopic drop in blood volume delivered to the periphery, was 4 ± 3% in asymptomatic treatments, whereas 17 ± 3% in symptomatic dialysis treatments. This result indicates that significant differences exist between the two groups of treatment, providing a potential for development of intradialytic risk predictors.
[Show abstract][Hide abstract]ABSTRACT: Intradialytic hypotension (IDH) is the most common complication during hemodialysis; early prediction and prevention of IDH would dramatically improve the living conditions for patients with end stage renal disease. A recently published study suggests that a decrease in the envelope of the photoplethysmograpy (PPG) signal can be used for predicting acute symptomatic IDH. In the present study, the PPG based method is extended by introducing a patient dependent detection threshold, which involves information on heart rate variability (HRV) and heart rate turbulence (HRT) from the current dialysis session. This is motivated since several studies have found significant differences in HRV and HRT between hypotension-prone and hypotension-resistant patients. Recordings from 15 patients during 38 hemodialysis sessions were used to evaluate the method. Symptomatic IDH was correctly predicted in 9 out of 14 cases, while 5 out of 24 cases were falsely predicted. The performance was better for acute symptomatic IDH, 5 out of 5 cases were correctly predicted. The present method represents a novel approach to combining information derived from ECG and PPG signals.
[Show abstract][Hide abstract]ABSTRACT: This paper introduces a number of advancements of our recently proposed model of atrioventricular (AV) node function during atrial fibrillation (AF). The model is defined by parameters characterizing the arrival rate of atrial impulses, the probability of an impulse choosing either one of the two AV nodal pathways, the refractory periods of these pathways, and their prolongation. In the updated model, the characterization of AV nodal pathways is made more detailed and the number of pathways is determined by the Bayesian information criterion. The performance is evaluated on ECG data acquired from twenty-five AF patients during rest and head-up tilt test. The results show that the refined AV node model provides significantly better fit than did the original model. During tilt, the AF frequency increased (6.25 ±0.58 Hz vs. 6.32 ±0.61 Hz, p < 0.05, rest vs. tilt) and the prolongation of the refractory periods decreased for both pathways (slow pathway: 0.23 ±0.20 s vs. 0.11 ±0.10 s, p < 0.001, rest vs. tilt; fast pathway: 0.24±0.31 s vs. 0.16±0.19 s, p < 0.05, rest vs. tilt). These results show that AV node characteristics can be assessed noninvasively for the purpose of quantifying changes induced by autonomic stimulation.
[Show abstract][Hide abstract]ABSTRACT: Determination of heart status during dialysis can improve patient monitoring. Pressure sensors in the dialysis machine measures the heart pulses that propagates in the body and enter the extracorporeal blood circuit. A peristaltic blood pump, located in the same circuit, introduces strong periodic pressure pulses that interfere with the much weaker cardiac component. These signal characteristics make the extraction of the heart activity challenging. In the present study, we explore the possibility to extract and analyze the cardiac component using simulated data. The accuracy of the timing of each heartbeat is analyzed. Additionally, the heart component is extracted from patient pressure recordings, and compared to the heart rate computed from a photoplethysmogram. The results show that heart timings can be accurately determined using the pressure sensors of a dialysis machine.
[Show abstract][Hide abstract]ABSTRACT: The aim of this work is to develop a method for detection of brief episode paroxysmal atrial fibrillation (PAF). The proposed method utilizes four different features: RR interval irregularity, absence of P waves, presence of f-waves and noise level. The obtained features are applied to the Mamdani-type fuzzy inference method for decisionmaking. The performance was evaluated on one hundred 90 s long surrogate ECG signals with brief PAF episodes (5–30 beats). The robustness to noise in ECGs where noise level in each set is incremented in steps of 0.01 mV from 0 to 0.2 mV was examined as well. When compared to the coefficient of sample entropy, our method showed considerably better performance for low and moderate noise levels (< 0.06 mV) with an area under the receiver operating characteristic curve of 0.9 and 0.94, respectively. Similar performance is expected for higher noise levels as atrial activity is less used in the detection process. Finally, the results suggest that our method is more robust to false alarms due to ectopic beats or other irregular rhythms than the method under comparison.
[Show abstract][Hide abstract]ABSTRACT: Episodes of hypotension during hemodialysis treatment constitutes an important clinical problem which has received considerable attention in recent years. Despite the fact that numerous approaches to reducing the frequency of intradialytic hypotension (IDH) have been proposed and evaluated, the problem has not yet found a definitive solution-an observation which, in particular, applies to episodes of acute, symptomatic hypotension. This overview covers recent advances in methodology for predicting and preventing IDH. Following a brief overview of well-established hypotension-related variables, including blood pressure, blood temperature, relative blood volume, and bioimpedance, special attention is given to electrocardiographic and photoplethysmographic (PPG) variables and their significance for IDH prediction. It is concluded that cardiovascular variables which reflect heart rate variability, heart rate turbulence, and baroreflex sensitivity are important to explore in feedback control hemodialysis systems so as to improve their performance. The analysis of hemodialysis-related changes in PPG pulse wave properties hold considerable promise for improving prediction.
[Show abstract][Hide abstract]ABSTRACT: A novel method for QRST cancellation during atrial fibrillation (AF) is introduced for use in recordings with two or more leads. The method is based on an echo state neural network which estimates the time-varying, nonlinear transfer function between two leads, one lead with atrial activity and another lead without, for the purpose of canceling ventricular activity. The network has different sets of weights that define the input, hidden, and output layers, of which only the output set is adapted for every new sample to be processed. The performance is evaluated on ECG signals, with simulated f-waves added, by determining the root mean square error between the true f-wave signal and the estimated signal, as well as by evaluating the dominant AF frequency. When compared to average beat subtraction (ABS), being the most widely used method for QRST cancellation, the performance is found to be significantly better with an error reduction factor of 0.24-0.43, depending on f-wave amplitude. The estimates of dominant AF frequency are considerably more accurate for all f-wave amplitudes than the AF estimates based on ABS. The novel method is particularly well suited for implementation in mobile health systems where monitoring of AF during extended time periods is of interest.
Article · Aug 2012 · IEEE transactions on bio-medical engineering
[Show abstract][Hide abstract]ABSTRACT: Advanced analysis of atrial fibrillation (AF) intra — cardiac electrograms aims to establish clinical targets for ablation. Frequency domain approaches, such as Dominant Frequency Analysis (DFA), estimate the dominant frequency to identify cardiac sites with high activation rates as ablation targets. However, they often discard relevant information in the spectrum, such as the harmonic structure or the spectral envelope. Moreover, these methods do not provide a complete characterization of complex atrial fibrillation signals. We propose to use the correntropy function to estimate the fundamental frequency, instead of dominant frequency, in order to quantify the activation rate of AF signals. We also propose to use the correntropy method combined with Fourier Organization Analysis (FOA), a method previously proposed to model fibril-latory signals, in order to estimate more than one fundamental frequency in complex signals which can be the result of the interaction of multiple wavefronts. The proposed approach was benchmarked by using pseudo-real AF signals for assessing their performance in a controlled environment. Two datasets of AF real signals were assembled, one with regular and simple signals, and another one with complex signals. Correntropy estimation of fundamental frequency, combined with FOA, allowed not only to characterize the periodicity of AF signals, but also to study more complex signals by modelling them with more than one component.
[Show abstract][Hide abstract]ABSTRACT: A novel method for QRST cancellation during atrial fibrillation (AF) is introduced for use in recordings with two or more leads. The method is based on an echo state neural network (ESN) which estimates the time-varying, nonlinear transfer function between two leads, one lead with atrial activity and another lead without, for the purpose of canceling ventricular activity. The performance is evaluated on ECG signals, with simulated f-waves of low amplitude added, by determining the root mean square error P between the true f-wave signal and the estimated signal, as well as by evaluating the dominant AF frequency. When compared to average beat subtraction (ABS), being the most widely used method for QRST cancellation, the performance is found to be significantly better with equal to mean and standard deviation of PESN 24.8±7.3 and PABS 34.2±17.9 μV (p
[Show abstract][Hide abstract]ABSTRACT: This paper introduces a model of the atrioventricular node function during atrial fibrillation (AF), and describes the related ECG-based estimation method. The proposed model is defined by parameters that characterize the arrival rate of atrial impulses, the probability of an impulse choosing either one of the two atrioventricular nodal pathways, the refractory periods of these pathways, and the prolongation of the refractory periods. These parameters are estimated from the RR intervals using maximum likelihood estimation, except for the shorter refractory period which is estimated from the RR interval Poincaré plot, and the mean arrival rate of atrial impulses by the AF frequency. Simulations indicated that 200-300 RR intervals are generally needed for the estimates to be accurate. The model was evaluated on 30-min ECG segments from 36 AF patients. The results showed that 88% of the segments can be accurately modeled when the estimated probability density function (PDF) and an empirical PDF were at least 80% in agreement. The model parameters were estimated during head-up tilt test to assess differences caused by sympathetic stimulation. Both refractory periods decreased as a result of stimulation, and the likelihood of an impulse choosing the pathway with the shorter refractory period increased.
Article · Aug 2011 · IEEE transactions on bio-medical engineering