Heart Sound Amplitude Research Articles

A new wearable cardiac acoustic monitoring technology for the evaluation of subclinical leaflet thrombosis after transcatheter aortic valve replacement: a pilot study

Abstract Background Subclinical leaflet thrombosis characterized by hypoattenuated leaflet thickening (HALT) and reduced leaflet motion (RLM) is a common complication after transcatheter aortic valve replacement (TAVR), whether it affects hemodynamic change is still debated. Purpose We attempted to use a novel wearable heart acoustic monitoring device, and combined multi-dimensional computed tomography (MDCT) and echocardiography to diagnose SLT and analyze the changes of transvalvular hemodynamics after TAVR. Methods Patients with severe symptomatic aortic stenosis and underwent successful TAVR were consecutively enrolled. Clinical data, acoustic cardiographic parameters including the frequency, amplitude, and energy of heart sounds , and imaging results were collected and analyzed by Core laboratory at pre- and post TAVR, and follow-up at one month and six month. According to severity of SLT at one month follow-up, we divided the patients into three groups: Group1: no SLT, Group2: mild SLT, defined as existed HALT did not qualify for Group 3, and Group 3: moderate to severe SLT, defined as at least 1 leaflet with HALT of grade 3 or 4 or RLM of ≥50%, or 2 leaflets with HALT of grade 2 or RLM of ≥50%. A consistency analysis of SLT presence between MDCT findings and acoustic cardiographic variables was performed using Kappa statistics. Results The study included 116 TAVR patients. The prevalence of SLT as detected by MDCT at one-month follow-up was 25%, with moderate to severe SLT representing 11.2% of cases. A significant decrease in aortic valve orifice area (AVA) (-0.2±0.48cm2 vs. -0.1±0.33cm2, p=0.009) and an increase in mean gradient (MG) (3.5±5.85 mmHg vs. 0.1±11.34mmHg, p=0.028) were observed in moderate to severe SLT group at one-month follow-up versus post-TAVR via echocardiography. However, no significant differences were found in the mild SLT or no SLT group. Acoustic cardiographic characteristics exhibited a distinct pattern with early systolic, baseless, and high-energy murmurs in patients with moderate to severe SLT, but not in the mild SLT or no SLT group. The sensitivity, specificity, and Kappa values for acoustic cardiography in diagnosing moderate to severe SLT were 81.82%, 83.33%, and 0.41, respectively. At the 6-month follow-up, MDCT showed that 11 (85%) patients with moderate to severe SLT who received anticoagulant therapy reached complete dissolution of SLT. Conclusion Moderate to severe SLT presented notably transvalvular hemodynamic influences following TAVR. Acoustic cardiography demonstrated specific characteristics of moderate to severe SLT, providing a valuable tool for SLT diagnosis and evaluation in clinical follow-up.Figure 1.Baseline characteristicsFigure 2.SLT and acoustic cardiography

Implantable defibrillator-detected heart failure status predicts ventricular tachyarrhythmias.

The prediction of ventricular tachyarrhythmias among patients with implantable cardioverter defibrillators is difficult with available clinical tools. We sought to assess whether in patients with heart failure (HF) and reduced ejection fraction with defibrillators, physiological sensor-based HF status, as summarized by the HeartLogic index, could predict appropriate device therapies. Five hundred and sixty-eight consecutive HF patients with defibrillators (n = 158, 28%) or cardiac resynchronization therapy-defibrillators (n = 410, 72%) were included in this prospective observational multicenter analysis. The association of both HeartLogic index and its physiological components with defibrillator shocks and overall appropriate therapies was assessed in regression and time-dependent Cox models. Over a follow-up of 25 (15-35) months, 122 (21%) patients received an appropriate device therapy (shock, n = 74, 13%), while the HeartLogic index crossed the threshold value (alert, HeartLogic ≥ 16) 1200 times (0.71 alerts/patient-year) in 370 (65%) subjects. The occurrence of ≥1 HeartLogic alert was significantly associated with both appropriate shocks (Hazard ratios [HR]: 2.44, 95% confidence interval [CI]: 1.49-3.97, p = .003), and any appropriate defibrillator therapies. In multivariable time-dependent Cox models, weekly IN-alert state was the strongest predictor of appropriate defibrillator shocks (HR: 2.94, 95% CI: 1.73-5.01, p < .001) and overall therapies. Compared with stable patients, patients with appropriate shocks had significantly higher values of HeartLogic index, third heart sound amplitude, and resting heart rate 30-60 days before device therapy. The HeartLogic index is an independent dynamic predictor of appropriate defibrillator therapies. The combined index and its individual physiological components change before the arrhythmic event occurs.

Implantable defibrillator-detected heart failure status predicts ventricular tachyarrhythmias

Abstract Background The occurrence of ventricular tachyarrhythmias is associated with increased mortality and hospitalizations for heart failure in implantable cardioverter defibrillator (ICD) patients. Nonetheless, the temporal relationship between heart failure worsening and ventricular tachyarrhythmias has been scarcely explored so far. Purpose We hypothesized that in patients with heart failure and reduced ejection fraction with ICDs, physiological sensor-based heart failure status, as reflected in the HeartLogic index, would predict appropriate device therapies for ventricular tachyarrhythmias (shocks and antitachycardia pacing). Methods and results 568 patients implanted with ICDs (n=410, 72%) or cardiac resynchronization therapy-defibrillators (CRT-D, n=158, 28%) endowed with the HeartLogic algorithm were included in this prospective observational multicenter analysis. Over a follow-up of 25 [25th-75th percentile: 15–35] months, 122 (21%) patients received an appropriate device therapy (shock, n=74, 13%), while the HeartLogic index crossed the threshold value 1200 times (0.71 alerts/patient-year) in 370 subjects (65%). The occurrence of at least one HeartLogic alert was significantly associated with both appropriate shocks (HR: 2.44, 95% CI: 1.49–3.97, p=0.003) and any ICD therapies (HR: 1.95, 95% CI: 1.37–2.85, p=0.003). Using a time-dependent Cox model, the weekly IN-alert state was the strongest predictor of ICD shocks (HR: 2.94, 95% CI: 1.73–5.01, p&amp;lt;0.001), after correction for age, secondary prevention, and use of CRT. As compared to clinically stable subjects with no therapies, patients experiencing shocks had significantly higher baseline values of the HeartLogic index, third heart sound amplitude, and respiratory rate. Beginning about one month prior to the arrhythmic event, we noticed further increase of the combined index and the third heart sound amplitude, a decrease of thoracic impedance, and higher resting heart rate (Figure 1). Conclusions The HeartLogic index is an independent predictor of appropriate defibrillator therapies. The combined index and its individual physiological components change well before the arrhythmic event, suggesting the existence of a window of opportunity to prevent shocks. Funding Acknowledgement Type of funding sources: None.

Assessing Hemorrhagic Shock Severity Using the Second Heart Sound Determined from Phonocardiogram: A Novel Approach.

Introduction: Hemorrhagic shock (HS) is a severe medical emergency. Early diagnosis of HS is important for clinical treatment. In this paper, we report a flexible material-based heart sound monitoring device which can evaluate the degree of HS through a phonocardiogram (PCG) change. Methods: Progressive hemorrhage treatments (H1, H2, and H3 stage) were used in swine to build animal models. The PCG sensor was mounted on the chest of the swine. Routine monitoring was used at the same time. Results: This study showed that arterial blood pressure decreased significantly from the H1 phase, while second heart sound amplitude (S2A) and energy (S2E) decreased significantly from the H2 phase. Both S2A and S2E correlated well with BP (p < 0.001). The heart rate, pulse pressure variation and serum hemoglobin level significantly changed in the H3 stage (p < 0.05). Discussion: The change of second heart sound (S2) was at the H2 stage and was earlier than routine monitoring methods. Therefore, PCG change may be a new indicator for the early detection of HS severity.

Analysis of Heart-Sound Characteristics during Motion Based on a Graphic Representation.

In this paper, the graphic representation method is used to study the multiple characteristics of heart sounds from a resting state to a state of motion based on single- and four-channel heart-sound signals. Based on the concept of integration, we explore the representation method of heart sound and blood pressure during motion. To develop a single- and four-channel heart-sound collector, we propose new concepts such as a sound-direction vector of heart sound, a motion–response curve of heart sound, the difference value, and a state-change-trend diagram. Based on the acoustic principle, the reasons for the differences between multiple-channel heart-sound signals are analyzed. Through a comparative analysis of four-channel motion and resting-heart sounds, from a resting state to a state of motion, the maximum and minimum similarity distances in the corresponding state-change-trend graphs were found to be 0.0038 and 0.0006, respectively. In addition, we provide several characteristic parameters that are both sensitive (such as heart sound amplitude, blood pressure, systolic duration, and diastolic duration) and insensitive (such as sound-direction vector, state-change-trend diagram, and difference value) to motion, thus providing a new technique for the diverse analysis of heart sounds in motion.

Hemodynamics-driven mathematical model of first and second heart sound generation.

We propose a novel, two-degree of freedom mathematical model of mechanical vibrations of the heart that generates heart sounds in CircAdapt, a complete real-time model of the cardiovascular system. Heart sounds during rest, exercise, biventricular (BiVHF), left ventricular (LVHF) and right ventricular heart failure (RVHF) were simulated to examine model functionality in various conditions. Simulated and experimental heart sound components showed both qualitative and quantitative agreements in terms of heart sound morphology, frequency, and timing. Rate of left ventricular pressure (LV dp/dtmax) and first heart sound (S1) amplitude were proportional with exercise level. The relation of the second heart sound (S2) amplitude with exercise level was less significant. BiVHF resulted in amplitude reduction of S1. LVHF resulted in reverse splitting of S2 and an amplitude reduction of only the left-sided heart sound components, whereas RVHF resulted in a prolonged splitting of S2 and only a mild amplitude reduction of the right-sided heart sound components. In conclusion, our hemodynamics-driven mathematical model provides fast and realistic simulations of heart sounds under various conditions and may be helpful to find new indicators for diagnosis and prognosis of cardiac diseases.New & noteworthyTo the best of our knowledge, this is the first hemodynamic-based heart sound generation model embedded in a complete real-time computational model of the cardiovascular system. Simulated heart sounds are similar to experimental and clinical measurements, both quantitatively and qualitatively. Our model can be used to investigate the relationships between heart sound acoustic features and hemodynamic factors/anatomical parameters.

Multiparameter diagnostic sensor measurements in heart failure patients presenting with SARS-CoV-2 infection.

AimsImplantable device‐based sensor measurements including heart sounds, markers of ventilation, and thoracic impedance have been shown to predict heart failure (HF) hospitalizations. We sought to assess how these parameters changed prior to COVID‐19 (Cov‐19) and how these compared with those presenting with decompensated HF or pneumonia.Methods and resultsThis retrospective analysis explores patterns of changes in daily measurements by implantable sensors in 10 patients with Cov‐19 and compares these findings with those observed prior to HF (n = 88) and pneumonia (n = 12) hospitalizations from the MultiSENSE, PREEMPT‐HF, and MANAGE‐HF trials. The earliest sensor changes prior to Cov‐19 were observed in respiratory rate (6 days) and temperature (5 days). There was a three‐fold to four‐fold greater increase in respiratory rate, rapid shallow breathing index, and night heart rate compared with those presenting with HF or pneumonia. Furthermore, activity levels fell more in those presenting with Cov‐19, a change that was often sustained for some time. In contrast, there were no significant changes in 1st or 3rd heart sound (S1 and S3) amplitude in those presenting with Cov‐19 or pneumonia compared with the known changes that occur in HF decompensation.ConclusionsMulti‐sensor device diagnostics may provide early detection of Cov‐19, distinguishable from worsening HF by an extreme and fast rise in respiratory rate along with no changes in S3.

Potential SCG Predictors of Heart Failure Readmission

Introduction Recent advances in sensor technology, digital processing and artificial intelligence can be used to potentially increase the utility of seismocardiography (SCG) for ambulatory assessment of heart failure (HF) patients. SCG respiratory variability, energy spectrum shifts to ultra-low frequencies, third heart sound amplitude and other features may provide early warning of HF deterioration. If these non-invasively detected changes prove to be reliable, then earlier intervention may reduce readmissions, costs, and perhaps morbidity and mortality. Objective The objective of this study was to investigate early SCG waveform features that may be predictive of HF re-admission. Methods SCG was longitudinally followed in 40 HF patients, 9 (23%) of whom were readmitted during the study period (median follow-up 1.5 mos). SCG waveforms were clustered into two groups (that correlate with respiration) using unsupervised machine learning. Following this, various signal features were calculated using digital signal processing including waveform respiratory variability, sub-audible spectral energy distribution, and SCG3 (“S3”) amplitude. Results Similar to prior observations with heart rate variability, the intra group SCG variability tended to decrease as the patient approached re-admission (table below). The energy ratio between the ultra-low frequency band (0.5-5 Hz) and the broader sub-audible frequency band (0.5-15 Hz) showed a shift towards the lower frequencies as the subjects approached re-admission. In addition, SCG3 amplitude (which corresponds to S3) appeared to increase as the subjects approached readmission. Conclusions We report preliminary data showing some SCG features that appeared to be early predictors of HF readmission. Features included Intra-group variability, along with the SCG downward frequency shifts and increased SCG3 amplitude Ongoing work will help to better characterize and validate these initial observations

Preliminary experience with the multisensor HeartLogic algorithm for heart failure monitoring: a retrospective case series report.

AimsIn the Multisensor Chronic Evaluation in Ambulatory Heart Failure Patients study, a novel algorithm for heart failure (HF) monitoring was implemented. The HeartLogic (Boston Scientific) index combines data from multiple implantable cardioverter defibrillator (ICD)‐based sensors and has proved to be a sensitive and timely predictor of impending HF decompensation. The remote monitoring of HF patients by means of HeartLogic has never been described in clinical practice. We report post‐implantation data collected from sensors, the combined index, and their association with clinical events during follow‐up in a group of patients who received a HeartLogic‐enabled device in clinical practice.Methods and resultsPatients with ICD and cardiac resynchronization therapy ICD were remotely monitored. In December 2017, the HeartLogic feature was activated on the remote monitoring platform, and multiple ICD‐based sensor data collected since device implantation were made available: HeartLogic index, heart rate, heart sounds, thoracic impedance, respiration, and activity. Their association with clinical events was retrospectively analysed. Data from 58 patients were analysed. During a mean follow‐up of 5 ± 3 months, the HeartLogic index crossed the threshold value (set by default to 16) 24 times (over 24 person‐years, 0.99 alerts/patient‐year) in 16 patients. HeartLogic alerts preceded five HF hospitalizations and five unplanned in‐office visits for HF. Symptoms or signs of HF were also reported at the time of five scheduled visits. The median early warning time and the time spent in alert were longer in the case of hospitalizations than in the case of minor events of clinical deterioration of HF. HeartLogic contributing sensors detected changes in heart sound amplitude (increased third sound and decreased first sound) in all cases of alerts. Patients with HeartLogic alerts during the observation period had higher New York Heart Association class (P = 0.025) and lower ejection fraction (P = 0.016) at the time of activation.ConclusionsOur retrospective analysis indicates that the HeartLogic algorithm might be useful to detect gradual worsening of HF and to stratify risk of HF decompensation.

Multivariable Fuzzy Measure Entropy Analysis for Heart Rate Variability and Heart Sound Amplitude Variability

Simultaneously analyzing multivariate time series provides an insight into underlying interaction mechanisms of cardiovascular system and has recently become an increasing focus of interest. In this study, we proposed a new multivariate entropy measure, named multivariate fuzzy measure entropy (mvFME), for the analysis of multivariate cardiovascular time series. The performances of mvFME, and its two sub-components: the local multivariate fuzzy entropy (mvFEL) and global multivariate fuzzy entropy (mvFEG), as well as the commonly used multivariate sample entropy (mvSE), were tested on both simulation and cardiovascular multivariate time series. Simulation results on multivariate coupled Gaussian signals showed that the statistical stability of mvFME is better than mvSE, but its computation time is higher than mvSE. Then, mvSE and mvFME were applied to the multivariate cardiovascular signal analysis of R wave peak (RR) interval, and first (S1) and second (S2) heart sound amplitude series from three positions of heart sound signal collections, under two different physiological states: rest state and after stair climbing state. The results showed that, compared with rest state, for univariate time series analysis, after stair climbing state has significantly lower mvSE and mvFME values for both RR interval and S1 amplitude series, whereas not for S2 amplitude series. For bivariate time series analysis, all mvSE and mvFME report significantly lower values for after stair climbing. For trivariate time series analysis, only mvFME has the discrimination ability for the two physiological states, whereas mvSE does not. In summary, the new proposed mvFME method shows better statistical stability and better discrimination ability for multivariate time series analysis than the traditional mvSE method.

Evaluation of Cardiac Reserve Function in Gestational Hypertension

Objective: Explore the cardiac reserve function in gestational hypertension,in order to provide a basis for the prevention and early treatment of pregnancy with hypertension disease and reduce the maternal and infant complications. Methods: We collected the related information of 112 pregnant women with gestational hypertension and 224 normal pregnant women who do perinatal care in Department of Women’s Health Care Division of Third Affiliated Hospital of Zhengzhou University from January 2009 to December 2012. We acquired the phonocardiogram with resting state and take the ratio of S1/S2(first heart sound maximum amplitude ratio of the second heart sound maximum amplitude of S1 and S2)D/S (diastolicto systolic duration) HR(heart rate) as the indicators of cardiac reserve function. Results: The comparison of the indicators between pregnant women with gestational hypertension and normal pregnant women show that S1/S2 between two groups have no significant difference while D/S and HR are significantly different; D/S values at 12?27+6weeks ≥28 weeks in the two groups are significantly different (p<0.05), while D/S values have no significant difference when the gestational age ≤11+6 weeks. Conclusion: The cardiac reserve function of gestational hypertension pregnant women are significantly lower than the normal pregnant women. The cardiac reserve function of gestational hypertension pregnant women reduces with gestational age.

A novel heart sound activity detection framework for automated heart sound analysis

In automated heart sound analysis and diagnosis, a set of clinically valued parameters including sound intensity, frequency content, timing, duration, shape, systolic and diastolic intervals, the ratio of the first heart sound amplitude to second heart sound amplitude (S1/S2), and the ratio of diastolic to systolic duration (D/S) is measured from the PCG signal. The quality of the clinical feature parameters highly rely on accurate determination of boundaries of the acoustic events (heart sounds S1, S2, S3, S4 and murmurs) and the systolic/diastolic pause period in the PCG signal. Therefore, in this paper, we propose a new automated robust heart sound activity detection (HSAD) method based on the total variation filtering, Shannon entropy envelope computation, instantaneous phase based boundary determination, and boundary location adjustment. The proposed HSAD method is validated using different clean and noisy pathological and non-pathological PCG signals. Experiments on a large PCG database show that the HSAD method achieves an average sensitivity (Se) of 99.43% and positive predictivity (+P) of 93.56%. The HSAD method accurately determines boundaries of major acoustic events of the PCG signal with signal-to-noise ratio of 5dB. Unlike other existing methods, the proposed HSAD method does not use any search-back algorithms. The proposed HSAD method is a quite straightforward and thus it is suitable for real-time wireless cardiac health monitoring and electronic stethoscope devices.

Product of Heart Rate and First Heart Sound Amplitude as an Index of Myocardial Metabolic Stress During Graded Exercise

The double product (DP) breakpoint of heart rate (HR) and systolic blood pressure has been identified as coincident with anaerobic threshold (AT), but there are no simple methods for measuring cardiac metabolic stress (CMS) during an exercise test. It was hypothesized that the DP of HR and the amplitude of the first heart sound (AHS1) (DP-AHS1) would reflect CMS, and thus, the breakpoint in the DP-AHS1 (DPBP-AHS1) could be an alternative method for determining AT. Subjects (age range, 18-73 years) were recruited to perform a graded exercise test on a cycle ergometer with continuous monitoring of DP-AHS1, with left ventricular pressure (LVP; experiment 1, Ex1), plasma catecholamine and blood lactate (experiment 2, Ex2) and gas exchange (experiment 3, Ex3). Ex1: in all subjects there was a strong correlation between AHS1 and LVdP/dtmax (r=0.94-0.98), and between the DP-AHS1 and the triple product of HR, LVdP/dtmax, and max LVP (r=0.98-0.99). Ex2: DP-AHS1 was strongly correlated with adrenaline (r=0.97-1.00) and lactate (r=0.96-1.00) levels in all subjects. Ex3: there was a strong correlation between DPBP-AHS1, AT and maximum oxygen consumption. The present simple measure of DP-AHS1 can reflect plasma adrenaline and lactate levels during graded exercise testing. Further, DPBP-AHS1 is a surrogate marker of AT and a good index of functional aerobic capacity.

The Use of Pneumoperitoneum During Laparoscopic Surgery as a Model to Study Pathophysiologic Phenomena: The Correlation of Cardiac Functionality with Computerized Acoustic Indices—Preliminary Data

Induction of pneumoperitoneum during laparoscopic surgery leads to diverse cardiovascular changes that can be used as a model to study pathophysiologic phenomena. Application of novel signal processing and figure extraction enabled searching for correlation between various signals and pathophysiologic setting. Our aim was to quantitatively correlate cardiac functionality (as expressed by cardiac output) with the spectral energy of the first heart sound (S1) obtained from the phonocardiogram, during laparoscopic surgery. Patients who were scheduled for elective laparoscopic operations were enrolled in the study. Cardiac output was maximally changed during anesthesia and abdominal insufflation and was obtained from the arterial pressure wave (FloTrac™ sensor and Vigileo™ monitor [Edwards Lifesciences Ltd.]). Heart signals were recorded during surgery from each subject by a computerized digital data acquisition system. The automatic analysis of the heart sounds included segmentation that was based on the energy envelope of the heart sounds together with analysis of the electrocardiogram signal. We analyzed the morphology of the sounds using hierarchial cluster analysis to remove those sounds that were not reliably recorded. The magnitude of the amplitude of heart sounds was obtained by using the Hilbert transform for each heartbeat. Statistical analysis was based on linear regression. Following exclusion of 3 patients (mainly because of technical reasons), we were left with 7 patients who demonstrated statistically significant positive correlation between cardiac index and the amplitude of S1 (regression coefficient between 0.4 and 0.9, P<.05). Linear regression analysis was done on the normalized values of all 7 patients and was found to be highly significant. In this study we have demonstrated significant linear correlation between the acoustic amplitude (spectral energy) of S1 and cardiac functionality, through sophisticated computerized analysis, using the pneumoperitoneum model for changing the cardiac output.

Post-exercise contractility, diastolic function, and pressure: Operator-independent sensor-based intelligent monitoring for heart failure telemedicine

BackgroundNew sensors for intelligent remote monitoring of the heart should be developed. Recently, a cutaneous force-frequency relation recording system has been validated based on heart sound amplitude and timing variations at increasing heart rates.AimTo assess sensor-based post-exercise contractility, diastolic function and pressure in normal and diseased hearts as a model of a wireless telemedicine system.MethodsWe enrolled 150 patients and 22 controls referred for exercise-stress echocardiography, age 55 ± 18 years. The sensor was attached in the precordial region by an ECG electrode. Stress and recovery contractility were derived by first heart sound amplitude vibration changes; diastolic times were acquired continuously. Systemic pressure changes were quantitatively documented by second heart sound recording.ResultsInterpretable sensor recordings were obtained in all patients (feasibility = 100%). Post-exercise contractility overshoot (defined as increase > 10% of recovery contractility vs exercise value) was more frequent in patients than controls (27% vs 8%, p < 0.05). At 100 bpm stress heart rate, systolic/diastolic time ratio (normal, < 1) was > 1 in 20 patients and in none of the controls (p < 0.01); at recovery systolic/diastolic ratio was > 1 in only 3 patients (p < 0.01 vs stress). Post-exercise reduced arterial pressure was sensed.ConclusionPost-exercise contractility, diastolic time and pressure changes can be continuously measured by a cutaneous sensor. Heart disease affects not only exercise systolic performance, but also post-exercise recovery, diastolic time intervals and blood pressure changes – in our study, all of these were monitored by a non-invasive wearable sensor.

Relationship between Amplitude and Timing of Heart Sounds and Endocardial Acceleration

To study the correlation between heart sounds and peak endocardial acceleration (PEA) amplitudes and timings, by modulation of paced atrioventricular (AV) delay in recipients of dual chamber pacemakers. Ten recipients of dual chamber pacemakers implanted for high-degree AV block were studied. Endocardial acceleration (EA) and phonocardiographic and electrocardiographic signals were recorded during performance of an AV delay scan in VDD and DDD modes. First PEA (PEA I) and first heart sound (S1) changed similarly with the AV delay. A close intrapatient correlation was observed between S1 and PEA I amplitudes in all patients (P < 0.0001). The interpatient normalized PEA I to S1 amplitudes correlation was r = 0.89 (P < 0.0001) in DDD mode, and r = 0.81 (P < 0.0001) in VDD mode. The mean cycle-by-cycle PEA I to S1 delay was -4.3 +/- 22 ms and second PEA (PEA II) to second heart sound (S2) delay was -7.7 +/- 15 ms. A close correlation was observed between PEA I and S1 amplitudes and timings, and between PEA II and S2 timings. These observations support the hypothesis that PEA and heart sounds are manifestations of the same phenomena. EA might be a useful tool to monitor cardiac function.

Arterial pressure changes monitoring with a new precordial noninvasive sensor

BackgroundRecently, a cutaneous force-frequency relation recording system based on first heart sound amplitude vibrations has been validated. A further application is the assessment of Second Heart Sound (S2) amplitude variations at increasing heart rates. The aim of this study was to assess the relationship between second heart sound amplitude variations at increasing heart rates and hemodynamic changes.MethodsThe transcutaneous force sensor was positioned in the precordial region in 146 consecutive patients referred for exercise (n = 99), dipyridamole (n = 41), or pacing stress (n = 6). The curve of S2 peak amplitude variation as a function of heart rate was computed as the increment with respect to the resting value.ResultsA consistent S2 signal was obtained in all patients. Baseline S2 was 7.2 ± 3.3 mg, increasing to 12.7 ± 7.7 mg at peak stress. S2 percentage increase was + 133 ± 104% in the 99 exercise, + 2 ± 22% in the 41 dipyridamole, and + 31 ± 27% in the 6 pacing patients (p < 0.05). Significant determinants of S2 amplitude were blood pressure, heart rate, and cardiac index with best correlation (R = .57) for mean pressure.ConclusionS2 recording quantitatively documents systemic pressure changes.

Diastolic time – frequency relation in the stress echo lab: filling timing and flow at different heart rates

A cutaneous force-frequency relation recording system based on first heart sound amplitude vibrations has been recently validated. Second heart sound can be simultaneously recorded in order to quantify both systole and diastole duration.Aims1- To assess the feasibility and extra-value of operator-independent, force sensor-based, diastolic time recording during stress.MethodsWe enrolled 161 patients referred for stress echocardiography (exercise 115, dipyridamole 40, pacing 6 patients).The sensor was fastened in the precordial region by a standard ECG electrode. The acceleration signal was converted into digital and recorded together with ECG signal.Both systolic and diastolic times were acquired continuously during stress and were displayed by plotting times vs. heart rate. Diastolic filling rate was calculated as echo-measured mitral filling volume/sensor-monitored diastolic time.ResultsDiastolic time decreased during stress more markedly than systolic time. At peak stress 62 of the 161 pts showed reversal of the systolic/diastolic ratio with the duration of systole longer than diastole. In the exercise group, at 100 bpm HR, systolic/diastolic time ratio was lower in the 17 controls (0.74 ± 0.12) than in patients (0.86 ± 0.10, p < 0.05 vs. controls).Diastolic filling rate increased from 101 ± 36 (rest) to 219 ± 92 ml/m2* s-1 at peak stress (p < 0.5 vs. rest).ConclusionCardiological systolic and diastolic duration can be monitored during stress by using an acceleration force sensor. Simultaneous calculation of stroke volume allows monitoring diastolic filling rate.Stress-induced "systolic-diastolic mismatch" can be easily quantified and is associated to several cardiac diseases, possibly expanding the spectrum of information obtainable during stress.

First heart sound and opening snap in patients with mitral valve disease. Phonocardiographic and pathomorphologic study

We investigated correlation between mitral valve morphology and first heart sound (S 1) and opening snap (OS) amplitude. The analysis revealed negative correlation between the OS amplitude and the area of calcification and the mitral orifice area. We also found negative correlation between the S 1 intensity and the area of calcification.

Accessing heart dynamics to estimate durations of heart sounds

Segmentation of the phonocardiogram into its major sound components is the first step in the automated diagnosis of cardiac abnormalities. Almost all of the existing phonocardiogram segmentation algorithms utilize absolute amplitude or frequency characteristics of heart sounds, which vary from one cardiac cycle to the other and across different patients. The objective of this work is to provide an efficient phonocardiogram segmentation technique, under difficult recording situations, by utilizing the underlying complexity of the dynamical system (heart) giving rise to the heart sound. Complexity-based segmentation is invariant to amplitude and frequency variations of the heart sound and yields better time gates for heart sounds.