Systolic Intervals Research Articles

Chronic Kidney Disease and Its Clinical Correlates in a Rural Community in Southwestern Nigeria.

Chronic kidney disease (CKD) is a burgeoning problem globally, and more than a billion adults were affected as of 2016, with 1.2 million people dying from renal failure in 2017. To arrest the seemingly relentless progression of CKD to renal failure, there is a need to detect CKD early in the community. A community-based study was carried out to look at the prevalence and risk factors of CKD. Anthropometric and other clinical variables were measured. Blood samples were taken for determining creatinine, uric acid, urea, and lipids. CKD was defined as an estimated glomerular filtration rate of ≤60 mL/min/1.73 m2. Electrocardiograms and renal ultrasound scans were performed. In total, 201 people were recruited. Those with CKD had a male:female ratio of 1:3.9 and were older. The prevalence of autosomal-dominant polycystic kidney disease and CKD was 531.9 persons/100,000 population and 46.3%, respectively. Systolic blood pressure, pulse pressure, total cholesterol, triglycerides, high-density lipoprotein (HDL), uric acid, QTc interval, and electrocardiographic left ventricular hypertrophy were higher in those with CKD. Age, female sex, and HDL were independently associated with CKD. There was a steep rise in CKD at the community level. Increased awareness of CKD and prompt interventions are therefore imperative.

Potential Linkage between High Normalized Electromechanical Activation Time (EMAT), an Early Systolic Time Interval Abnormality with Metabolic Syndrome.

High electromechanical activation time (EMAT) is associated with paroxysmal atrial fibrillation and heart failure. Little is known about the association between EMAT and metabolic syndrome (MetS), a precursor of cardiovascular disease. To explore the association between EMAT and MetS. A total of 429 male volunteers were divided into MetS (n = 135, age 60.3 ± 3.7 years) and non-MetS (n = 294, age 58.1 ± 26.6 years) groups in this cross-sectional study. A complete medical history, fasting blood analysis and phonoelectrocardiographic parameters were recorded. EMAT was defined as the time from the onset of Q- wave to the peak first heart sound (Q-S1 interval), and this interval divided by the R-R interval for heart rate correction was calculated as normalized EMAT (nEMAT). The subjects with MetS had a significantly higher rate of positive nEMAT (nEMAT ≥ 15%: 6.7% vs. 2%, p = 0.015), higher heart rate (HR, 71.9 ± 12.0 vs. 69.2 ± 11.1 bpm, p = 0.022) but shorter left ventricular ejection time (LVST = 312.4 ± 33.5 vs. 319.8 ± 31.8 msec, p = 0.029). However, the normalized LVST (nLVST) was not significantly different after adjusting for HR. In multivariate analysis, nEMAT was significantly associated with MetS (odds ratio = 3.43, 95% confidence interval = 1.195-9.837, p = 0.022). Positive nEMAT, a prolonged early phase of contraction, was significantly associated with MetS in males. High nEMAT may be an earlier sign of cardiac function abnormality in MetS.

Acute autonomic effects of rose oxide on cardiovascular parameters of Wistar and spontaneously hypertensive rats

AimsAnti-inflammatory molecules, such as rose oxide (RO), are likely to exert therapeutic effects in systemic arterial hypertension (SAH), a disease associated with abnormal immune responses. We aimed to investigate acute autonomic effects of RO on hemodynamic parameters of Wistar and spontaneously hypertensive rats (SHR). MethodsRats were anesthetized and femoral artery and veins were cannulated. Next day, blood pressure (BP) and heart rate (HR) were recorded. Acute effects of RO (1.25, 2.5, or 5.0 mg/kg; iv) on BP, HR, and variability of systolic arterial pressure (SAP) and pulse interval (PI) were assessed. The effects of RO were also investigated in SHR, which received atropine (2 mg/kg), propranolol (4 mg/kg), or hexamethonium (20 mg/kg) 15 min before receiving RO. Vasorelaxant effects of RO (10–10 to 10–4 M) on aortic rings of rats were also assessed. Key findingsIn Wistar rats, none of the RO doses evoked significant changes in BP, HR, and variability of SAP and PI. On the other hand, in SHR, RO elicited reduction in mean arterial pressure (MAP), and prevented the increase in the low frequency power (LF) of the SAP spectra. Pretreatment with atropine or propranolol did not alter hypotension, but attenuated RO-induced bradycardia. Hexamethonium prevented RO-induced hypotension and bradycardia. RO exerted vasorelaxant effects on aortic rings with (Wistar and SHR) or without functional endothelium (SHR only). SignificanceRose oxide, a monoterpene with anti-inflammatory properties, acts as an antihypertensive molecule due to its ability to acutely promote hypotension and bradycardia in spontaneously hypertensive rats.

Novel Approach to Assess Cardiac Function Using Systolic Performance and Myocardial Performance Indices From Simultaneous Electrocardiography and Phonocardiography Recordings in Dogs With Various Stages of Myxomatous Mitral Valve Disease.

Background and Objective: Myxomatous mitral valve disease (MMVD) progression entails changes in the structural and functional properties of the heart affecting cardiac timings and intervals within the cardiac cycle. Conventionally, echocardiography is used to determine the cardiac time intervals (CTIs) including systolic and myocardial performance indices (SPI and MPI) in evaluating cardiac function. Alternatively, these CTIs can also be measured using simultaneous recordings of electrocardiography (ECG) and phonocardiography (PCG), but their values in different MMVD stages remain to be established. This study aimed to establish and prove the use of derived SPI and MPI from a dedicated device as a novel approach to assess cardiac function in different stages of MMVD dogs.Materials and Methods: A prospective study in 52 dogs with different MMVD stages measured the CTIs using a novel device. These were compared and correlated with standard echocardiographic parameters. The predictive value of SPI and three new proposed formulas to estimate MPI (i.e., F1, F2, and F3) in association with asymptomatic from symptomatic MMVD dogs were investigated.Results: Our findings revealed that CTI parameters measured from a novel device including QS1, QS2, S1S2, MPI-F1, and MPI-F2 were altered at different stages of MMVD. The SPI and all proposed MPI formulas were comparable with the systolic time interval and Tei index from echocardiography. In addition, the SPI, MPI-F1, and MPI-F2 were significantly correlated with the Tei index. However, the SPI was not able to differentiate the various stages of MMVD. Conversely, only the MPI-F1 (i.e., (QS1 + S2)/S1S2) demonstrated good predictive accuracy when compared between asymptomatic and symptomatic MMVD dogs similar to the Tei index. Moreover, this formula was able to differentiate stages B1 and C with remarkable predictive accuracy, higher sensitivity, and high specificity when compared with the Tei index.Conclusion: We have successfully described the CTI parameters in different MMVD stages using simultaneous ECG and PCG recordings in dogs. Furthermore, we have proven that the concept of using the newly proposed parameters from a novel device is equivalent to the Tei index. Thus, we established a novel approach to evaluate cardiac function and its supportive use in the diagnosis of MMVD patients.

Longitudinal Association of Arterial Stiffness and Pressure Wave Reflection with Decline of the Cardiac Systolic Performance in Healthy Men.

Aims: This prospective observational study aimed to examine the individual longitudinal associations of the increases in the arterial stiffness and pressure wave reflection with the decline in the cardiac systolic performance during the study period in healthy middle-aged Japanese men. Methods: In 4016 middle-aged Japanese healthy men (43±9 years), the brachial-ankle pulse wave velocity (baPWV), radial augmentation index (rAI), and pre-ejection period/ejection time (pre-ejection period (PEP)/ET) were measured annually during a 9-year study period. Results: The baPWV, rAI, and PEP/ET showed steady annual increases during the study period. According to the results of multivariate linear regression analyses, both the baPWV and rAI measured at the baseline showed significant independent associations with the PEP/ET measured at the baseline (baPWV: beta=0.17,p＜0.01 and rAI: beta=0.11,p＜0.01), whereas neither showed any association with the PEP/ET measured at the end of the study period. The results of the mixed-model linear regression analysis of the repeated-measures data collected over the 9-year study period revealed that the baPWV, but not the rAI, showed a significant longitudinal association with the PEP/ET (estimate=0.69 x 10−4,p＜0.01). Conclusion: In apparently healthy middle-aged Japanese men, the annual increase of the arterial stiffness, rather than the annual increase of the pressure wave reflection, appears to be more closely associated with the annual decline of the cardiac systolic performance as assessed by the systolic time interval.

Effect of plaque geometry on targeted delivery of stem cells containing magnetic particles in a rigid and elastic curved artery with stenosis

Magnetic drug targeting (MDT) is a new and effective therapeutic technique to treat some diseases. In this method, the transfer of magnetic particles labeled with therapeutic agents in the presence of a magnetic field increases the efficiency of treatment. In this study, targeted delivery of endothelial cells containing magnetic particles in a stenosed curved artery for solid and elastic wall states was investigated, using an external magnetic field. The Eulerian-Lagrangian approach and the Eulerian-Lagrangian coupled FSI technique were employed to solve the continuum equations and track the trajectory of cells in a rigid and elastic artery, respectively. The influence of parameters was investigated, such as the mass of magnetic particles injected in each cell, the magnetic field strength, the injection time, the occlusion percentage, and the chord length of stenosis on the capture efficiency (CE). The effect of wall elasticity on CE was also studied. The results reveal that by increasing the mass of magnetic particles injected in each cell from 20 pg to 300 pg, the cells absorption at the target site is enhanced from 17% to 43%. Also, a slight increase in the magnetic field strength has a significant effect on increasing the CE. The injection of cells in a complete period of the cardiac cycle provides greater CE than other systole and diastole intervals. Examining the stenosis morphology shows that reducing the occlusion percentage from 40% to 20% and the chord length of stenosis from 70° to 30° results in an increase in the CE about 6% and 3% for 300 pg of magnetic particles in each cell, respectively. The trend of CE changes is the same for elastic artery and the rigid artery. However, in all cases, the elastic artery has a higher CE than the rigid artery. The obtained results can be useful for the treatment of atherosclerosis in curved vessels using targeted cell delivery.

The relation between left ventricular systolic function parameters and preceding or prepreceding beat-to-beat distance in patients with atrial fibrillation: an echocardiographic study.

We aimed at investigating the relation between left ventricle (LV) systolic parameters and beat-to-beat distances and also whether this relation is different in heart failure with reduced ejection fraction (HFrEF) patients with atrial fibrillation (AF). The relation between peak velocity in left ventricular outflow (VLVOT), left atrioventricular plane displacement (LAVPD) or peak systolic tissue Doppler velocity of lateral mitral annulus (Lateral S') and preceding beat-to-beat distance (RR1) or prepreceding beat-to-beat distance (RR2) were analyzed by linear regression analysis. From this analysis, three parameters were obtained: slope of regression line, constant of regression line, and square of regression coefficient (r2) of linear relation. In the group with HFrEF, the slope and r2 values of the regression line showing the relationship between the RR1 interval and VLVOT, LAVPD, and Lateral S' values were higher and the constants were lower. In the Kendall rank correlation analysis, the slope, constant, and r2 values of the regression analysis between RR1 interval and VLVOT or Lateral S' were in significant correlation with LVEF. The r2 of VLVOT-RR1 analysis, slope of this analysis, and slope of Lateral S'-RR1 regression line values were mostly predictive for detecting HFrEF. It was concluded that the novel parameters obtained by linear regression analysis between LV systolic function parameters and RR1 interval, but not RR2, might be beneficial for evaluating systolic heart failure in patients with AF. They might have potential for future research about the physiopathology of heart and prognosis in patient with AF.

Effects of Transcranial Direct Current Stimulation on effort during a working-memory task

Transcranial Direct Current Stimulation (tDCS) has shown that stimulation of Dorsolateral Prefrontal Cortex (DLPFC) facilitates task performance in working-memory tasks. However, little is known about its potential effects on effort. This study examined whether tDCS affects effort during a working-memory task. Participants received anodal, cathodal and sham stimulation over DLPFC across three sessions before carrying out a 2-back task. During the task, effort-related cardiovascular measures were recorded—especially the Initial Systolic Time Interval (ISTI). Results showed that anodal stimulation produced a shorter ISTI, indicating a greater effort compared to cathodal and sham conditions, where effort was lower. These findings demonstrate that anodal stimulation helps participants to maintain engagement in a highly demanding task (by increasing task mastery), without which they would otherwise disengage. This study is the first to show that tDCS impacts the extent of effort engaged by individuals during a difficult task.

A Novel Method for Measuring Myocardial Performance Index using Non-contact Ballistocardiogram System

Aim: The aim was to validate the Systolic Time Intervals (STI) measured by Ballistocardiography (BCG) with STI derived from simultaneously performed Transthoracic Echocardiogram (TTE) and attempt to create an AI algorithm that automatically calculates Tei Index from BCG tracings.
 Study design: Cross-sectional study.
 Place and Duration of Study: Department of Cardiology and Department of Electrophysiology of Sri Jayadeva Institute of Cardiovascular Sciences & Research, Bangalore, India, between January 2020 and January 2021.
 Methodology: Two hundred seventy-four patients with clinically indicated TTE were enrolled in the study, average age was 52. Simultaneous recordings on BCG and TTE were done. 150 patients had clinically usable TTE images for accurate calculations. STI was calculated independently by operators experienced in TTE and BCG. Results were compared using Pearson’s R. A proprietary AI algorithm for automatically calculating the MPI, was trained over a subset of patients. Its accuracy in detecting STI was compared to that of TTE and manually calculated STI from BCG.
 Results: There was a strong positive correlation (r=0.766, P<0.00, 99%CI [0.691,0.824]) between the TTE and BCG derived MPI values. The result was validated over predetermined subgroups of subjects with reduced EF (EF<50) and subjects with normal EF (EF>=50). The AI algorithm had correlation of 0.54(p<0.01) with the MPI calculated by TTE and 0.34(P<0.10) with the manually calculated MPI on the BCG.
 Conclusion: BCG derived manual and automated MPI correlates well with TTE derived MPI in a variety of EF fraction subgroups. Automated calculation algorithms for MPI derived from BCG remain a work under progress.

Temporal patterns in the dependency structures of the cardiovascular time series

Copula density is a function that quantifies the level of dependency between two, or more, related time series, and also visualizes their (non)linear dependency structures. This paper aims to analyze and compare different methods for copula density estimation: local (naïve) estimation, kernel estimation, K nearest neighbors, Markov state approach, histograms, and Voronoi decomposition. The methods are compared by mapping the copula density into a time series (dependency level time series) and applying Sample Entropy estimates over the range of parameters. Application examples include systolic blood pressure and pulse interval signals recorded from conscious laboratory rats, treated either with vasopressin selective V1a and V2 receptor antagonists (100 ng and 500 ng) or with saline (control group). The signals are analyzed using composite multiscale entropy. It is shown that each estimation method suffers from bias, but, for each case, a stable working region can be found. It was also shown that the analysis of the dependency level time series could reveal the information that could not be extracted from the classical beat-to-beat time series, and that the copula density, transformed to real signals domain, visualizes the regions where the dependency of cardiovascular signals is exhibited the most, reflecting their mutual relationship and providing the possibility for further research.

Discrimination of Patients with Varying Degrees of Coronary Artery Stenosis by ECG and PCG Signals Based on Entropy.

Coronary heart disease (CHD) is the leading cause of cardiovascular death. This study aimed to propose an effective method for mining cardiac mechano-electric coupling information and to evaluate its ability to distinguish patients with varying degrees of coronary artery stenosis (VDCAS). Five minutes of electrocardiogram and phonocardiogram signals was collected synchronously from 191 VDCAS patients to construct heartbeat interval (RRI)–systolic time interval (STI), RRI–diastolic time interval (DTI), HR-corrected QT interval (QTcI)–STI, QTcI–DTI, Tpeak–Tend interval (TpeI)–STI, TpeI–DTI, Tpe/QT interval (Tpe/QTI)–STI, and Tpe/QTI–DTI series. Then, the cross sample entropy (XSampEn), cross fuzzy entropy (XFuzzyEn), joint distribution entropy (JDistEn), magnitude-squared coherence function, cross power spectral density, and mutual information were applied to evaluate the coupling of the series. Subsequently, support vector machine recursive feature elimination and XGBoost were utilized for feature selection and classification, respectively. Results showed that the joint analysis of XSampEn, XFuzzyEn, and JDistEn had the best ability to distinguish patients with VDCAS. The classification accuracy of severe CHD—mild-to-moderate CHD group, severe CHD—chest pain and normal coronary angiography (CPNCA) group, and mild-to-moderate CHD—CPNCA group were 0.8043, 0.7659, and 0.7500, respectively. The study indicates that the joint analysis of XSampEn, XFuzzyEn, and JDistEn can effectively capture the cardiac mechano-electric coupling information of patients with VDCAS, which can provide valuable information for clinicians to diagnose CHD.

SARS-CoV-2 vaccination of people living with human T leukaemia virus type 1

<b>Hardarson, T., Ziady, G. M., and Khattri, H. N. (1974).</b><i>Thorax</i>, <b>29</b>, 359-365. <b>Assessment of left ventricular function following coronary bypass surgery: a non-invasive study.</b> In a series of 15 patients...

A Close Examination of the Use of Systolic Time Intervals in the Calculation of Impedance Derived Cardiac Autonomic Balance and Regulation

Traditionally, impedance derived measures of cardiac autonomic balance (CAB) and regulation (CAR) are calculated using indices of heart rate variability (HRV) that primarily reflect parasympathetic nervous system activity (e.g., high-frequency HRV | HF-HRV) and pre-ejection period (PEP; a systolic time interval and measure of sympathetic activity). However, HF-HRV and PEP are considered measures of chronotropic and inotropic cardiac influence, respectively. Left ventricular ejection time (LVET) is a systolic time interval that reflects sympathetic chronotropic influence, and therefore may be a more appropriate measure for calculating CAB and CAR compared to PEP. Thus, the current study evaluates both PEP and LVET in the calculation of CAB and CAR. Data from 158 healthy participants (mean age = 19.09 years old, SD = 1.84 years) were available for analyses. CAB and CAR values were calculated using both HF-HRV and the root mean square of successive differences, in addition to both PEP and LVET, in accordance with previously established guidelines. Analyses showed that correlations were significantly weaker between CAB and CAR calculated using LVET for both HF (z = 5.12, p < 0.001) and RMSSD (z = 5.26, p < 0.001) than with PEP. These data suggest that LVET, compared to PEP, provides better “autonomic space” as evidenced by a lack of correlation between CAB and CAR computed using LVET. We stress that future research consider calculating CAB and CAR using chronotropic measures for both parasympathetic and sympathetic activity, as doing so may yield more accurate and independent measures of cardiac autonomic activity compared to a mixture of inotropic (i.e., PEP) and chronotropic (i.e., HF-HRV) measures.

AI-Based Estimation of End-Systolic Elastance From Arm-Pressure and Systolic Time Intervals.

Left ventricular end-systolic elastance (Ees) is a major determinant of cardiac systolic function and ventricular-arterial interaction. Previous methods for the Ees estimation require the use of the echocardiographic ejection fraction (EF). However, given that EF expresses the stroke volume as a fraction of end-diastolic volume (EDV), accurate interpretation of EF is attainable only with the additional measurement of EDV. Hence, there is still need for a simple, reliable, noninvasive method to estimate Ees. This study proposes a novel artificial intelligence—based approach to estimate Ees using the information embedded in clinically relevant systolic time intervals, namely the pre-ejection period (PEP) and ejection time (ET). We developed a training/testing scheme using virtual subjects (n = 4,645) from a previously validated in-silico model. Extreme Gradient Boosting regressor was employed to model Ees using as inputs arm cuff pressure, PEP, and ET. Results showed that Ees can be predicted with high accuracy achieving a normalized RMSE equal to 9.15% (r = 0.92) for a wide range of Ees values from 1.2 to 4.5 mmHg/ml. The proposed model was found to be less sensitive to measurement errors (±10–30% of the actual value) in blood pressure, presenting low test errors for the different levels of noise (RMSE did not exceed 0.32 mmHg/ml). In contrast, a high sensitivity was reported for measurements errors in the systolic timing features. It was demonstrated that Ees can be reliably estimated from the traditional arm-pressure and echocardiographic PEP and ET. This approach constitutes a step towards the development of an easy and clinically applicable method for assessing left ventricular systolic function.

An innovative method for cardiovascular disease detection based on nonlinear geometric features and feature reduction combination

Cardiovascular is arguably the most dominant death cause in the world. Heart functionality can be measured in various ways. Heart sounds are usually inspected in these experiments as they can unveil a variety of heart related diseases. This study tackles the lack of reliable models and high training times on a publicly available dataset. The heart sound set is provided by Physionet consisting of 3153 recordings, from which five seconds were fixed to evaluate to the developed method. In this work, we propose a novel method based on feature reduction combination, using Genetic Algorithm (GA) and Principal Component Analysis (PCA). The authors present eight dominant features in heart sound classification: mean duration of systole interval, the standard deviation of diastole interval, the absolute amplitude ratio of diastole to S2, S1 to systole and S1 to diastole, zero crossings, Centroid to Centroid distance (CCdis) and mean power in the 95–295 Hz range. These reduced features are then optimized respectively with two straightforward classification algorithms weighted k-NN with a lower-dimensional feature space and Linear SVM that uses a linear combination of all features to create a robust model, acquiring up to 98.15% accuracy, holding the best stats in the heart sound classification on a largely used dataset. According to the experiments done in this study, the developed method can be further explored for real world heart sound assessments.

Human biventricular electromechanical simulations on the progression of electrocardiographic and mechanical abnormalities in post-myocardial infarction.

AimsDevelop, calibrate and evaluate with clinical data a human electromechanical modelling and simulation framework for multiscale, mechanistic investigations in healthy and post-myocardial infarction (MI) conditions, from ionic to clinical biomarkers. Methods and resultsHuman healthy and post-MI electromechanical simulations were conducted with a novel biventricular model, calibrated and evaluated with experimental and clinical data, including torso/biventricular anatomy from clinical magnetic resonance, state-of-the-art human-based membrane kinetics, excitation–contraction and active tension models, and orthotropic electromechanical coupling. Electromechanical remodelling of the infarct/ischaemic region and the border zone were simulated for ischaemic, acute, and chronic states in a fully transmural anterior infarct and a subendocardial anterior infarct. The results were compared with clinical electrocardiogram and left ventricular ejection fraction (LVEF) data at similar states. Healthy model simulations show LVEF 63%, with 11% peak systolic wall thickening, QRS duration and QT interval of 100 ms and 330 ms. LVEF in ischaemic, acute, and chronic post-MI states were 56%, 51%, and 52%, respectively. In linking the three post-MI simulations, it was apparent that elevated resting potential due to hyperkalaemia in the infarcted region led to ST-segment elevation, while a large repolarization gradient corresponded to T-wave inversion. Mechanically, the chronic stiffening of the infarct region had the benefit of improving systolic function by reducing infarct bulging at the expense of reducing diastolic function by inhibiting inflation.ConclusionOur human-based multiscale modelling and simulation framework enables mechanistic investigations into patho-physiological electrophysiological and mechanical behaviour and can serve as testbed to guide the optimization of pharmacological and electrical therapies.

Automativ assessment of systolic cardiac performance using PEP/LVET index

Congestive cardiac failure is one of the deadliest diseases in the world, with more than 26 million patients. Echocardiogram and angiography consider as the gold standards for heart failure diagnosis. Nevertheless, they are not commonly used for long-term follow up as they need highly skilled and experienced operator. In this paper, a simple and low-cost system for automatic assessment of systolic cardiac performance using systolic cardiac intervals is presented. The proposed system utilized electrocardiogram (ECG) and phonocardiogram (PCG) to calculate pre-ejection period (PEP) and left ventricle ejection time (LVET). The ratio between PEP and LVET was computed to assess the performance of the systolic cardiac function. ECG and PCG were acquired using a commercial stethoscope which was modified to convert PCG auscultation to electrical signals. ECG and PCG signals were digitized and transferred to a personal computer. A custom MATLAB application was designed to display the acquired ECG and PCG, and to compute PEP, LVET, and PEP/LVET ratio. The system was tested on 17 healthy subjects and results showed high agreement between the systolic heart function status assessed by the proposed system and the corresponding echocardiography results. These results imply that the proposed system could be used for long-term follow up for patients with congestive heart failure.

Timing the opening and closure of the aortic valve using a phonocardiogram envelope: a performance test for systolic time intervals measurement

Objective. This work explored the reliability of using points on the heart sounds envelope as indicators of the opening and closure of the aortic valve (AVO, AVC) to measure the pre-ejection period (PEP) and the left ventricular ejection time (LVET). Approach. 36 phonocardiograms (PCGs) from healthy subjects and cardiovascular disease subjects were denoised using single-channel independent component analysis (SCICA) and, from the Hilbert envelopes, the positions of the S1 and S2 peaks were detected (pS1, pS2). Complementarily, the positions of the local maxima of S1 and S2 (mS1, mS2) and the points surrounding pS1 and pS2 (tS1, tS2) were obtained. Finally, the reliability of these points (and the corresponding PEP and LVET intervals) was evaluated by the calculation of three error indexes (ePEP, eLVET, and score) and by comparison to reference annotations provided by echocardiography using the Bland–Altman analysis and the paired T-test. Main results. The results indicated that, from a total of 920 and 341 heartbeats in the healthy and diseased groups, respectively, the timing points given by pS1 and pS2 (or mS1 and mS2) were unlikely to substitute for the reference annotations and, thus, are unreliable for measuring the PEP and LVET intervals in the PCG. The t-points evaluation, on the other hand, indicated that tS1 was likely to substitute for AVO and was thus reliable for measuring the PEP using the PCG, with median and interquartile ranges of 0.3(8.3) ms and −0.2(7.5) ms for each group. Future work will generate an envelope with higher temporal resolution, from where tS1 and tS2 can be more accurately detected to improve the PEP and LVET measurements on a larger dataset. Significance. The statistical tests revealed that the envelope of S1 is suitable for extracting a timing point from which the pre-ejection interval can be reliably quantified, and discarded the local maximum used in other studies.

Handling Errors in eHealth Sensors Using Interval Mapping and Fuzzy Modeling

EHealth sensors are connected through an Internet of Things infrastructure and the vital sign measurements are sent to cloud for real-time diagnosis by a remotely located physician. We use a cloud-based virtual sensing technology for collecting the vital signs of the patients remotely for smart diagnosis. Here the challenge is that the uncertainty generated from underlying physical sensor layer is propagated to the virtual sensors in cloud inflicting the diagnosis process. This article focuses on handling this challenge by introducing a new approach, Interval Mapping Technique (IMT), which is used to indicate the presence of any inaccuracy of devices and random errors at real-time. The novelty of this technique lies in the consideration that the Systolic and Diastolic BP of a person fall within certain ranges and the knowledge about these two ranges or intervals together can be used to get rid of random errors. A fuzzy modeling based approach is also proposed in this article. Fuzzy linguistic terms are used to determine the systolic and diastolic intervals of a person and a rule base is developed to find any real time error. Primarily, the techniques are used for error reduction in blood pressure measurements of Hypertensive, Pre-hypertensive and Normotensive patients. However, these methodologies can be extended for other vitals as well. These two techniques are compared with other standard techniques, like linear regression and random forest. Results show that IMT generates 3.69% less error for Systolic and 7.24% less error for Diastolic BP compared to linear regression model, 1.91% less error for Systolic and 7.18% less error for Diastolic BP compared to random forest model.

Systolic time intervals and its relation to intraventricular dyssynchrony of the left ventricle in patients with dilated cardiomyopathy

Aim To assess the value of systolic time intervals [as simple echocardiographic parameters of left ventricle (LV) systolic performance] and its relation to intraventricular dyssynchrony (by speckle tracking) of the LV in patients with dilated cardiomyopathy. Patients and methods All the studied individuals were subjected to ECG and transthoracic echocardiography to measure LV dimensions and systolic function by conventional and speckle-tracking echo. Left ventricular pre-ejection time (LVPET), left ventricular ejection time (LVET), and the ratio of LVPET to LVET were also measured (LVPET/LVET). Two-dimensional strain to measure time to peak negative strain value of the LV segments was averaged to calculate TPS-SD. Results The enrolled population were 153 cases, divided into 123 patients and 30 normal individuals. There was a significant lower LV global longitudinal strain % in the patient group. Moreover, insignificant shorter LVET was seen in the patients. LVET had an inversely significant correlation with QRS duration and dyssynchrony index. The LVPET and PET/LVET ratio had a significant linear correlation with QRS duration and dyssynchrony index measured by two-dimensional strain (r=0.4, P&lt;0.01). Conclusion Systolic time interval can be easily and accurately measured in patients with DCM and may be considered as an indicator for presence of LV intraventricular dyssynchrony.