Human heartbeat intervals are known to have nonlinear and nonstationary dynamics. In this paper, we propose a model of R–R interval dynamics based on a nonlinear Volterra–Wiener expansion within a point process framework. Inclusion of second-order nonlinearities into the heartbeat model allows us to estimate instantaneous heart rate (HR) and heart rate variability (HRV) indexes, as well as the dynamic bispectrum characterizing higher order statistics of the nonstationary non-Gaussian time series. The proposed point process probability heartbeat interval model was tested with synthetic simulations and two experimental heartbeat interval datasets. Results show that our model is useful in characterizing and tracking the inherent nonlinearity of heartbeat dynamics. As a feature, the fine temporal resolution allows us to compute instantaneous nonlinearity indexes, thus sidestepping the uneven spacing problem. In comparison to other nonlinear modeling approaches, the point process probability model is useful in revealing nonlinear heartbeat dynamics at a fine timescale and with only short duration recordings.
Adaptive filters; approximate entropy (ApEn); heart rate variability (HRV); nonlinearity test; point processes; scaling exponent; Volterra series expansion
Traditional ways of teaching techniques of physical examinations in the first clinical courses are rather demanding in terms of teacher involvement and a pool of patients suitable for demonstrations. For a long time, various audio-visual tools have been used to save teachers' and students' time and patients' patience. The modern technology of WWW publishing of multimedia allows good access to such teaching materials - and there already exist several collections of heart sounds, breath sounds etc. The aim of our project is to design and set up a comprehensive multimedia textbook of internal propedeutics that would present various physiological and pathological findings (auscultation, inspection, basic imaging) in the context of diagnostic patient investigation - the status praesens - as it is taught in the first clinical courses.
Unlike classical textbooks, hypertext presentation allows to ogranize the material into several structures - reflecting various approaches: systemic (digestive, cardiovascular etc.) approach, nosological, differential diagnoses, etc. To identify and implement the various useful approaches is the most difficult part of the task. The accompanying illustrative material is being prepared with the use of modern technologies - digital camera, scanner, video-camera and digitizer, digital audio recording, etc.
In the first year of the project, the skeleton of the multimedia presentation is being constructed - corresponding to the various approaches to the subject. Concurrently, suitable illustrative material is being gathered from cases of the Internal Clinic. Various existing WWW presentations dealing with heart and breath sounds and other relevant investigations have been searched and listed.
Experience and feedback from other projects of this type confirm that a rather elaborate logical and technical construction of multimedia textbooks is rewarded by a good acceptance by both students and teachers. Good access to Internet, sufficient for multimedia transfers, however, is a necessary prerequisite. Internal propedeutics is a very suitable field for internet-based multimedia textbooks: instant access to audio and video recordings is much welcome in development of clinical skills. The project is supported by a grant of the Czech Universities Development Fund.
Medical Education; Distance Education; Internet; Multimedia; Internal Medicine; Physical Examination
BACKGROUND AND OBJECTIVE:
Patients have reported that they perceive their own heart sounds differently after open cardiac surgery than before the surgery. The present study was designed to investigate whether changes in heart sounds can be quantitatively measured.
Heart sounds were recorded from 57 patients undergoing coronary artery bypass graft (CABG) surgery and from a control group of 10 subjects. The so-called Hjorth descriptors and the main frequency peak were compared before and after surgery to determine whether the characteristics of the heart sounds had changed.
At a group level, the first heart sound was found to be significantly different after CABG surgery. Generally, the heart sounds shifted toward a lower frequency after surgery in the CABG group. No significant changes were found in the control group.
Heart sounds are altered after CABG surgery. The changes are objectively quantifiable and may also be subjectively perceived by the patients.
Cardiac surgery; Counselling; Heart sound; Phonocardiography
Auscultation of the heart is accompanied by both electrical activity and sound. Heart auscultation provides clues to diagnose many cardiac abnormalities. Unfortunately, detection of relevant symptoms and diagnosis based on heart sound through a stethoscope is difficult. The reason GPs find this difficult is that the heart sounds are of short duration and separated from one another by less than 30 ms. In addition, the cost of false positives constitutes wasted time and emotional anxiety for both patient and GP. Many heart diseases cause changes in heart sound, waveform, and additional murmurs before other signs and symptoms appear. Heart-sound auscultation is the primary test conducted by GPs. These sounds are generated primarily by turbulent flow of blood in the heart. Analysis of heart sounds requires a quiet environment with minimum ambient noise. In order to address such issues, the technique of denoising and estimating the biomedical heart signal is proposed in this investigation. Normally, the performance of the filter naturally depends on prior information related to the statistical properties of the signal and the background noise. This paper proposes Kalman filtering for denoising statistical heart sound. The cycles of heart sounds are certain to follow first-order Gauss–Markov process. These cycles are observed with additional noise for the given measurement. The model is formulated into state-space form to enable use of a Kalman filter to estimate the clean cycles of heart sounds. The estimates obtained by Kalman filtering are optimal in mean squared sense.
heart sound; murmurs; ECG; Kalman filters; acoustic cardiac signals
A new method and application is proposed to characterize intensity and pitch of human heart sounds and murmurs. Using recorded heart sounds from the library of one of the authors, a visual map of heart sound energy was established. Both normal and abnormal heart sound recordings were studied. Representation is based on Wigner-Ville joint time-frequency transformations. The proposed methodology separates acoustic contributions of cardiac events simultaneously in pitch, time and energy. The resolution accuracy is superior to any other existing spectrogram method. The characteristic energy signature of the innocent heart murmur in a child with the S3 sound is presented. It allows clear detection of S1, S2 and S3 sounds, S2 split, systolic murmur, and intensity of these components. The original signal, heart sound power change with time, time-averaged frequency, energy density spectra and instantaneous variations of power and frequency/pitch with time, are presented. These data allow full quantitative characterization of heart sounds and murmurs. High accuracy in both time and pitch resolution is demonstrated. Resulting visual images have self-referencing quality, whereby individual features and their changes become immediately obvious.
Zebrafish (Danio rerio), due to its optical accessibility and similarity to human, has emerged as model organism for cardiac research. Although various methods have been developed to assess cardiac functions in zebrafish embryos, there lacks a method to assess heartbeat regularity in blood vessels. Heartbeat regularity is an important parameter for cardiac function and is associated with cardiotoxicity in human being. Using stereomicroscope and digital video camera, we have developed a simple, noninvasive method to measure the heart rate and heartbeat regularity in peripheral blood vessels. Anesthetized embryos were mounted laterally in agarose on a slide and the caudal blood circulation of zebrafish embryo was video-recorded under stereomicroscope and the data was analyzed by custom-made software. The heart rate was determined by digital motion analysis and power spectral analysis through extraction of frequency characteristics of the cardiac rhythm. The heartbeat regularity, defined as the rhythmicity index, was determined by short-time Fourier Transform analysis.
The heart rate measured by this noninvasive method in zebrafish embryos at 52 hour post-fertilization was similar to that determined by direct visual counting of ventricle beating (p > 0.05). In addition, the method was validated by a known cardiotoxic drug, terfenadine, which affects heartbeat regularity in humans and induces bradycardia and atrioventricular blockage in zebrafish. A significant decrease in heart rate was found by our method in treated embryos (p < 0.01). Moreover, there was a significant increase of the rhythmicity index (p < 0.01), which was supported by an increase in beat-to-beat interval variability (p < 0.01) of treated embryos as shown by Poincare plot.
The data support and validate this rapid, simple, noninvasive method, which includes video image analysis and frequency analysis. This method is capable of measuring the heart rate and heartbeat regularity simultaneously via the analysis of caudal blood flow in zebrafish embryos. With the advantages of rapid sample preparation procedures, automatic image analysis and data analysis, this method can potentially be applied to cardiotoxicity screening assay.
Heartbeat intervals are known to have nonlinear and non-stationary dynamics. In this paper, we propose a nonlinear Volterra-Wiener expansion modeling of human heartbeat dynamics within a point process framework. Inclusion of second-order nonlinearity allows us to estimate dynamic bispectrum. The proposed probabilistic model was examined with two recorded heartbeat interval data sets. Preliminary results show that our model is beneficial to characterize the inherent nonlinearity of the heartbeat dynamics.
The aim of this article is focused on the design of an obstacle detection system for assisting visually impaired people. A dense disparity map is computed from the images of a stereo camera carried by the user. By using the dense disparity map, potential obstacles can be detected in 3D in indoor and outdoor scenarios. A ground plane estimation algorithm based on RANSAC plus filtering techniques allows the robust detection of the ground in every frame. A polar grid representation is proposed to account for the potential obstacles in the scene. The design is completed with acoustic feedback to assist visually impaired users while approaching obstacles. Beep sounds with different frequencies and repetitions inform the user about the presence of obstacles. Audio bone conducting technology is employed to play these sounds without interrupting the visually impaired user from hearing other important sounds from its local environment. A user study participated by four visually impaired volunteers supports the proposed system.
visually impaired; obstacle detection; stereo camera; ground plane estimation; audio warning
Timbre is a key perceptual feature that allows discrimination between different sounds. Timbral sensations are highly dependent on the temporal evolution of the power spectrum of an audio signal. In order to quantitatively characterize such sensations, the shape of the power spectrum has to be encoded in a way that preserves certain physical and perceptual properties. Therefore, it is common practice to encode short-time power spectra using psychoacoustical frequency scales. In this paper, we study and characterize the statistical properties of such encodings, here called timbral code-words. In particular, we report on rank-frequency distributions of timbral code-words extracted from 740 hours of audio coming from disparate sources such as speech, music, and environmental sounds. Analogously to text corpora, we find a heavy-tailed Zipfian distribution with exponent close to one. Importantly, this distribution is found independently of different encoding decisions and regardless of the audio source. Further analysis on the intrinsic characteristics of most and least frequent code-words reveals that the most frequent code-words tend to have a more homogeneous structure. We also find that speech and music databases have specific, distinctive code-words while, in the case of the environmental sounds, this database-specific code-words are not present. Finally, we find that a Yule-Simon process with memory provides a reasonable quantitative approximation for our data, suggesting the existence of a common simple generative mechanism for all considered sound sources.
Measures of heart rate variability (HRV) are widely used to assess autonomic nervous system (ANS) function. HRV can be recorded via electrocardiography (ECG), which is both non-invasive and widely available. However, ECG needs three electrodes touching the body of the subjects, which makes them feel nervous and uncomfortable, thus potentially affecting the recording. Contact-free detection of the heartbeat via a microwave sensor constitutes another means of determining the timing of cardiac cycles by continuous monitoring of mechanical contraction of the heart. This technique can measure the heartbeat without any electrodes touching human body and penetrate the clothes at some distances, which in some instances may prove a practical basis for HRV analysis. Comparison of 5-minute recordings demonstrated that there were no significant differences in the temporal, frequency domains and in non-linear dynamic analysis of HRV measures derived from heartbeat and ECG, which suggested this technique may prove a practical alternative to ECG for HRV analysis.
heart rate variability; contact-free; heartbeat; microwave sensor
Function of the heart begins long before its formation is complete. Analyses in mouse and zebrafish have shown that myocardial function is not required for early steps of organogenesis, such as formation of the heart tube or chamber specification. However, whether myocardial function is required for later steps of cardiac development, such as endocardial cushion (EC) formation, has not been established. Recent technical advances and approaches have provided novel inroads toward the study of organogenesis, allowing us to examine the effects of both genetic and pharmacological perturbations of myocardial function on EC formation in zebrafish. To address whether myocardial function is required for EC formation, we examined silent heart (sih−/−) embryos, which lack a heartbeat due to mutation of cardiac troponin T (tnnt2), and observed that atrioventricular (AV) ECs do not form. Likewise, we determined that cushion formation is blocked in cardiofunk (cfk−/−) embryos, which exhibit cardiac dilation and no early blood flow. In order to further analyze the heart defects in cfk−/− embryos, we positionally cloned cfk and show that it encodes a novel sarcomeric actin expressed in the embryonic myocardium. The Cfks11 variant exhibits a change in a universally conserved residue (R177H). We show that in yeast this mutation negatively affects actin polymerization. Because the lack of cushion formation in sih- and cfk-mutant embryos could be due to reduced myocardial function and/or lack of blood flow, we approached this question pharmacologically and provide evidence that reduction in myocardial function is primarily responsible for the defect in cushion development. Our data demonstrate that early myocardial function is required for later steps of organogenesis and suggest that myocardial function, not endothelial shear stress, is the major epigenetic factor controlling late heart development. Based on these observations, we postulate that defects in cardiac morphogenesis may be secondary to mutations affecting early myocardial function, and that, in humans, mutations affecting embryonic myocardial function may be responsible for structural congenital heart disease.
Cardiac anomolies can result from very early defects in heart development. In zebrafish, such defects have been shown to be caused by a new gene called cardiofunk
Elevated sympathetic activation is a characteristic feature of heart failure (HF). Excessive sympathetic activation under resting conditions has been shown to increase from the early stages of the disease, and is related to prognosis. Direct recording of multiunit efferent muscle sympathetic nerve activity (MSNA) by microneurography is the best method for quantifying sympathetic nerve activity in humans. To date, this technique has been used to evaluate the actual central sympathetic outflow to the periphery in HF patients at rest and during exercise; however, because the firing occurrence of sympathetic activation is mainly synchronized by pulse pressure, multiunit MSNA, expressed as burst frequency (bursts/min) and burst incidence (bursts/100 heartbeats), may have limitations for the quantification of sympathetic nerve activity. In HF, multiunit MSNA is near the maximum level, and cannot increase further than the heartbeat. Single-unit MSNA analysis in humans is technically demanding, but provides more detailed information regarding central sympathetic firing. Although a great deal is known about the response of multiunit MSNA to stress, little information is available regarding the responses of single-unit MSNA to physiological stress and disease. The purposes of this review are to describe the differences between multiunit and single-unit MSNA during stress and to discuss the advantages of single-unit MSNA recording in improving our understanding the pathology of increased sympathetic activity in HF.
sympathetic nerve activity; heart failure; exercise; arrhythmia
Respiratory sinus arrhythmia (RSA) is largely mediated by the autonomic nervous system through its modulating influence on the heartbeat. We propose an algorithm for quantifying instantaneous RSA as applied to heart beat interval and respiratory recordings under dynamic respiration conditions. The blood volume pressure derived heart beat series (pulse intervals, PI) are modeled as an inverse Gaussian point process, with the instantaneous mean PI modeled as a bivariate regression incorporating both past PI and respiration values observed at the beats. A point process maximum likelihood algorithm is used to estimate the model parameters, and instantaneous RSA is estimated by a frequency domain transfer function approach. The model is statistically validated using Kolmogorov-Smirnov (KS) goodness-of-fit analysis, as well as independence tests. The algorithm is applied to subjects engaged in meditative practice, with distinctive dynamics in the respiration patterns elicited as a result. Experimental results confirm the ability of the algorithm to track important changes in cardiorespiratory interactions elicited during meditation, otherwise not evidenced in control resting states.
Recently, shift-invariant tensor factorisation algorithms have been proposed for the purposes of sound source separation of
pitched musical instruments. However, in practice, existing algorithms require the use of log-frequency spectrograms to allow
shift invariance in frequency which causes problems when attempting to resynthesise the separated sources. Further, it is difficult
to impose harmonicity constraints on the recovered basis functions. This paper proposes a new additive synthesis-based
approach which allows the use of linear-frequency spectrograms as well as imposing strict harmonic constraints, resulting in
an improved model. Further, these additional constraints allow the addition of a source filter model to the factorisation framework,
and an extended model which is capable of separating mixtures of pitched and percussive instruments simultaneously.
Background: Heart murmurs are common in children, and they are often referred to a specialist for examination. A clinically innocent murmur does not need further investigation. The referral area of the University Hospital is large and sparsely populated. A new service for remote auscultation (telemedicine) of heart murmurs in children was established where heart sounds and short texts were sent as an attachment to e-mails.
Aim: To assess the clinical quality of this method.
Methods: Heart sounds from 47 patients with no murmur (n = 7), with innocent murmurs (n = 20), or with pathological murmurs (n = 20) were recorded using a sensor based stethoscope and e-mailed to a remote computer. The sounds were repeated, giving 100 cases that were randomly distributed on a compact disc. Four cardiologists assessed and categorised the cases as having "no murmur", "innocent murmur", or "pathological murmur", recorded the assessment time per case, their degree of certainty, and whether they recommended referral.
Results: On average, 2.1 minutes were spent on each case. The mean sensitivity and specificity were 89.7% and 98.2% respectively, and the inter-observer and intra-observer variabilities were low (kappa 0.81 and 0.87), respectively. A total of 93.4% of cases with a pathological murmur and 12.6% of cases with an innocent murmur were recommended for referral.
Conclusion: Telemedical referral of patients with heart murmurs for remote assessment by a cardiologist is safe and saves time. Skilled auscultation is adequate to detect patients with innocent murmurs.
Evaluation of arterial baroreflex in cardiovascular control is an important topic in cardiology and clinical medicine. In this paper, we present a point process approach to estimate the dynamic baroreflex gain in a closed-loop model of the cardiovascular system. Specifically, the inverse Gaussian probability distribution is used to model the heartbeat interval, whereas the instantaneous mean is modulated by a bivariate autoregressive model that contains the previous R-R intervals and systolic blood pressure (SBP) measures. The instantaneous baroreflex gain is estimated in the feedback loop with a point process filter, while the RR→SBP feedforward frequency response gain can be estimated by a Kalman filter. The proposed estimation approach provides a quantitative assessment of interacting heartbeat dynamics and hemodynamics. We validate our approach with real physiological signals and evaluate the proposed model with established goodness-of-fit tests.
HeartLander is a miniature mobile robot designed to navigate over the epicardium of the beating heart for minimally invasive therapy. This paper presents a technique to decrease slippage and improve locomotion efficiency by synchronizing the locomotion with the intrapericardial pressure variations of the respiration and heartbeat cycles.
Respiratory and heartbeat phases were detected in real time using a chest-mounted accelerometer during locomotion in a porcine model in vivo. Trials were conducted over the lateral aspect of the heart surface to test synchronized locomotion against an unsynchronized control.
Offline evaluation showed that the respiration and heartbeat algorithms had accuracies of 100% and 88%, respectively. Synchronized trials exhibited significantly lower friction, higher efficiency, and greater total distance traveled than control trials.
Synchronization of the locomotion of HeartLander with respiration and heartbeat is feasible and results in safer and more efficient travel on the beating heart.
robot; minimally invasive; beating heart; epicardial therapy
We present a comprehensive probabilistic point process framework to estimate and monitor the instantaneous heartbeat dynamics as related to specific cardiovascular control mechanisms and hemodynamics. Assessment of the model’s statistics is established through the Wiener-Volterra theory and a multivariate autoregressive (AR) structure. A variety of instantaneous cardiovascular metrics, such as heart rate (HR), heart rate variability (HRV), respiratory sinus arrhythmia (RSA), and baroreceptor-cardiac reflex (BRS), can be rigorously derived within a parametric framework and instantaneously updated with an adaptive algorithm. Instantaneous metrics of nonlinearity, such as the bispectrum of heartbeat intervals, can also be derived. We have applied the proposed point process framework to experimental recordings from healthy subjects in order to monitor cardiovascular regulation under propofol anesthesia. Results reveal interesting dynamic trends across different pharmacological interventions, confirming the ability of the algorithm to track important changes in cardiorespiratory elicited interactions, and pointing at our mathematical approach as a promising monitoring tool for an accurate, noninvasive assessment of general anesthesia.
In the mammalian embryo, the primitive tubular heart starts beating during the first trimester of gestation. These early heartbeats originate from calcium-induced contractions of the developing heart muscle cells. To explain the initiation of this activity, two ideas have been presented. One hypothesis supports the role of spontaneously activated voltage-gated calcium channels, whereas the other emphasizes the role of Ca2+ release from intracellular stores initiating spontaneous intracellular calcium oscillations. We show with experiments that both of these mechanisms coexist and operate in mouse cardiomyocytes during embryonic days 9–11. Further, we characterize how inositol-3-phosphate receptors regulate the frequency of the sarcoplasmic reticulum calcium oscillations and thus the heartbeats. This study provides a novel view of the regulation of embryonic cardiomyocyte activity, explaining the functional versatility of developing cardiomyocytes and the origin and regulation of the embryonic heartbeat.
Background: In Wolff-Parkinson-White syndrome (WPW) patients the loss of pre-excitation in a single heartbeat during exercise stress testing (EST) is a predictor of low risk of sudden death. The purpose of this study was to: 1) assess the frequency of loss of pre-excitation in a single heartbeat during exercise testing, and 2) compare the cost of EST versus trans-catheter electrophysiology study (EPS) in the risk assessment of WPW patients.
Methods: A retrospective review of 50 cases of patients with WPW who underwent EST was conducted including demographics, history of supraventricular tachycardia, associated congenital heart disease, maximum heart rate achieved, and loss of pre-excitation in a single heartbeat. Hospital costs of EST and EPS were compared.
Results: Of the 50 patients who underwent EST, 4 (8%), lost pre-excitation in a single heartbeat during EST. No differences were found regarding gender, age at diagnosis or EST, history of supraventricular tachycardia, presence of congenital heart disease or maximal heart rate. A cost comparison, utilizing the cost data: EST ($62.75) and EPS ($5,597) found EST to be a cost-saving approach in WPW patients. With 4 patients losing pre-excitation during EST, the cost saving of EST was $22,388 for this population of WPW patients.
Conclusions: A frequency of 8% loss of pre-excitation was found in a pediatric sample that underwent EST. Additionally, EST was shown to be a cost-saving strategy in risk assessment of pediatric WPW patients.
Wolff-Parkinson-White syndrome; exercise stress test
Cough recordings have been undertaken for many years but the analysis of cough frequency and the temporal relation to trigger factors have proven problematic. Because cough is episodic, data collection over many hours is required, along with real-time aural analysis which is equally time-consuming.
A method has been developed for the automatic recognition and counting of coughs in sound recordings.
The Hull Automatic Cough Counter (HACC) is a program developed for the analysis of digital audio recordings. HACC uses digital signal processing (DSP) to calculate characteristic spectral coefficients of sound events, which are then classified into cough and non-cough events by the use of a probabilistic neural network (PNN). Parameters such as the total number of coughs and cough frequency as a function of time can be calculated from the results of the audio processing.
Thirty three smoking subjects, 20 male and 13 female aged between 20 and 54 with a chronic troublesome cough were studied in the hour after rising using audio recordings.
Using the graphical user interface (GUI), counting the number of coughs identified by HACC in an hour long recording, took an average of 1 minute 35 seconds, a 97.5% reduction in counting time. HACC achieved a sensitivity of 80% and a specificity of 96%. Reproducibility of repeated HACC analysis is 100%.
An automated system for the analysis of sound files containing coughs and other non-cough events has been developed, with a high robustness and good degree of accuracy towards the number of actual coughs in the audio recording.
Manual cough counting is time-consuming and laborious; however it is the standard to which automated cough monitoring devices must be compared. We have compared manual cough counting from video recordings with manual cough counting from digital audio recordings.
We studied 8 patients with chronic cough, overnight in laboratory conditions (diagnoses were 5 asthma, 1 rhinitis, 1 gastro-oesophageal reflux disease and 1 idiopathic cough). Coughs were recorded simultaneously using a video camera with infrared lighting and digital sound recording.
The numbers of coughs in each 8 hour recording were counted manually, by a trained observer, in real time from the video recordings and using audio-editing software from the digital sound recordings.
The median cough frequency was 17.8 (IQR 5.9–28.7) cough sounds per hour in the video recordings and 17.7 (6.0–29.4) coughs per hour in the digital sound recordings. There was excellent agreement between the video and digital audio cough rates; mean difference of -0.3 coughs per hour (SD ± 0.6), 95% limits of agreement -1.5 to +0.9 coughs per hour. Video recordings had poorer sound quality even in controlled conditions and can only be analysed in real time (8 hours per recording). Digital sound recordings required 2–4 hours of analysis per recording.
Manual counting of cough sounds from digital audio recordings has excellent agreement with simultaneous video recordings in laboratory conditions. We suggest that ambulatory digital audio recording is therefore ideal for validating future cough monitoring devices, as this as this can be performed in the patients own environment.
Heart murmurs are the first signs of cardiac valve disorders. Several studies have been conducted in recent years to automatically differentiate normal heart sounds, from heart sounds with murmurs using various types of audio features. Entropy was successfully used as a feature to distinguish different heart sounds. In this paper, new entropy was introduced to analyze heart sounds and the feasibility of using this entropy in classification of five types of heart sounds and murmurs was shown. The entropy was previously introduced to analyze mammograms. Four common murmurs were considered including aortic regurgitation, mitral regurgitation, aortic stenosis, and mitral stenosis. Wavelet packet transform was employed for heart sound analysis, and the entropy was calculated for deriving feature vectors. Five types of classification were performed to evaluate the discriminatory power of the generated features. The best results were achieved by BayesNet with 96.94% accuracy. The promising results substantiate the effectiveness of the proposed wavelet packet entropy for heart sounds classification.
In recent years, time-varying inhomogeneous point process models have been introduced for assessment of instantaneous heartbeat dynamics as well as specific cardiovascular control mechanisms and hemodynamics. Assessment of the model’s statistics is established through the Wiener-Volterra theory and a multivariate autoregressive (AR) structure. A variety of instantaneous cardiovascular metrics, such as heart rate (HR), heart rate variability (HRV), respiratory sinus arrhythmia (RSA), and baroreceptor-cardiac reflex (baroreflex) sensitivity (BRS), are derived within a parametric framework and instantaneously updated with adaptive and local maximum likelihood estimation algorithms. Inclusion of second-order non-linearities, with subsequent bispectral quantification in the frequency domain, further allows for definition of instantaneous metrics of non-linearity. We here present a comprehensive review of the devised methods as applied to experimental recordings from healthy subjects during propofol anesthesia. Collective results reveal interesting dynamic trends across the different pharmacological interventions operated within each anesthesia session, confirming the ability of the algorithm to track important changes in cardiorespiratory elicited interactions, and pointing at our mathematical approach as a promising monitoring tool for an accurate, non-invasive assessment in clinical practice. We also discuss the limitations and other alternative modeling strategies of our point process approach.
autonomic cardiovascular control; heart rate variability; baroreflex sensitivity; respiratory sinus arrhythmia; point process; Wiener-Volterra expansion; general anesthesia
Quantitative evaluation of respiratory sinus arrhythmia (RSA) may provide important information in clinical practice of anesthesia and postoperative care. In this paper, we apply a point process method to assess dynamic RSA during propofol general anesthesia. Specifically, an inverse Gaussian probability distribution is used to model the heartbeat interval, whereas the instantaneous mean is identified by a linear or bilinear bivariate regression on the previous R-R intervals and respiratory measures. The estimated second-order bilinear interaction allows us to evaluate the nonlinear component of the RSA. The instantaneous RSA gain and phase can be estimated with an adaptive point process filter. The algorithm’s ability to track nonstationary dynamics is demonstrated using one clinical recording. Our proposed statistical indices provide a valuable quantitative assessment of instantaneous cardiorespiratory control and heart rate variability (HRV) during general anesthesia.