Systolic Time Intervals and New Measurement Methods

Direct and indirect effects of adiposity on markers of autonomic nervous system activity in older adults

Several cardiovascular disease (CVD) risk factors (e.g., hypertension, poor glycemic control) can affect and be affected by autonomic nervous system (ANS) activity. Since excess adiposity can influence CVD development through its effect on hypertension and diabetes mellitus, it is important to determine how adiposity and altered ANS activity are related. The present study employed structural equation modeling to investigate the relation between adiposity and ANS activity both directly and indirectly through biological variables typically associated with glycemic impairment and cardiac stress in older adults. Utilizing the Atherosclerosis Risk in Communities (ARIC) dataset, 1,145 non-smoking adults (74±4.8 yrs, 62.8% female) free from known CVD, hypertension, and diabetes and not currently taking beta-blockers were evaluated for fasting blood glucose (FBG), insulin, and HbA1c concentrations, waist circumference (WC), blood pressure (BP), and markers of ANS activity. WC was recorded just above the iliac crest and was used to reflect central adiposity. Resting 2-minute electrocardiograph recordings, pulse wave velocity, and ankle-brachial index data were used to assess the root mean square of successive differences in RR intervals (RMSSD) and the pre-ejection period (PEP), markers of parasympathetic and sympathetic activity, respectively. FBG, insulin, and HbA1c inferred a latent variable termed glycemic impairment (GI), whereas heart rate and diastolic BP inferred a latent variable termed cardiac stress (CS). The structural equation model fit was acceptable [root mean square error of approximation = 0.050 (90% CI = .036, .066), comparative fit index = .970, Tucker Lewis Index = 0.929], with adiposity having both significant direct (β = 0.208, p = 0.018) and indirect (β = -.217, p = .041) effects on PEP through GI. Adiposity displayed no significant direct effect on RMSSD. CS displayed a significant pathway (β = -0.524, p = 0.035) on RMSSD, but the indirect effect of WC on RMSSD through CS did not reach statistical significance (β = -0.094, p = 0.137). These results suggest that adiposity's relation to ANS activity is multifaceted, as increased central adiposity had opposing direct and indirect effects on markers of sympathetic activity in this population of older adults.

A Review on Recent Advancements of Biomedical Radar for Clinical Applications

The field of biomedical radar has witnessed significant advancements in recent years, paving the way for innovative and transformative applications in clinical settings. Most medical instruments invented to measure human activities rely on contact electrodes, causing discomfort. Thanks to its non-invasive nature, biomedical radar is particularly valuable for clinical applications. A significant portion of the review discusses improvements in radar hardware, with a focus on miniaturization, increased resolution, and enhanced sensitivity. Then, this paper also delves into the signal processing and machine learning techniques tailored for radar data. This review will explore the recent breakthroughs and applications of biomedical radar technology, shedding light on its transformative potential in shaping the future of clinical diagnostics, patient and elderly care, and healthcare innovation.

Cardiovascular effects of oxytocin and carbetocin at cesarean section. A prospective double-blind randomized study using noninvasive pulse wave analysis

BACKGROUND

Oxytocin is routinely administered after delivery for prophylaxis and treatment of postpartum hemorrhage, but it is associated with considerable cardiovascular side-effects. Carbetocin, a synthetic oxytocin analogue, has a myometrial contraction effect of 60 min when given IV, compared with 16 min for oxytocin.

OBJECTIVE

To investigate whether there are differences in cardiovascular effects between oxytocin and carbetocin up to 1 h after treatment.

METHODS

Sixty-one healthy pregnant women undergoing elective cesarean section in spinal anesthesia were randomized to receive an IV bolus of either five units (8.3 µg) of oxytocin or 100 µg of carbetocin after delivery of the baby. Heart rate (HR), mean arterial blood pressure, ECG ST index, oxygen saturation (SaO₂), and photoplethysmographic digital pulse wave analysis variables were recorded before and at 1, 5, 20, and 60 min after drug administration. Vasopressor use, uterine tonus, total bleeding, and need for additional uterotonics were also assessed. Repeated measurement ANOVA was used for statistical analyses.

RESULTS

The drugs had equal vasodilatory and hypotensive effects. Oxytocin, but not carbetocin, caused a decrease in HR at 1 min and a sustained decrease in cardiac left ventricular ejection time. Aggregate vasopressor use was higher in the carbetocin group. Neither drug caused any change in ST index, SaO₂, or subjective cardiac symptoms. Uterine tonus, need for additional uterotonics, or total bleeding did not differ significantly between the groups.

CONCLUSION

Single doses of oxytocin and carbetocin had similar dilatory effects on vascular tonus, where the difference in aggregate vasopressor use can be attributed to a more persistent hypotensive effect of carbetocin. A transient negative chronotropic and sustained negative inotropic effect occurred after oxytocin. Neither drug showed any alarmingly adverse effects. Differences in drug effects may be attributed to differences in oxytocin and vasopressin receptor signaling pathways.

Perioperative advanced haemodynamic monitoring of patients undergoing multivisceral debulking surgery: an observational pilot study

BACKGROUND

Patients undergoing high-risk surgery show haemodynamic instability and an increased risk of morbidity. However, most of the available data concentrate on the intraoperative period. This study aims to characterise patients with advanced haemodynamic monitoring throughout the whole perioperative period using electrical cardiometry.

METHODS

In a prospective, observational, monocentric pilot study, electrical cardiometry measurements were obtained using an Osypka ICON™ monitor before surgery, during surgery, and repeatedly throughout the hospital stay for 30 patients with primary ovarian cancer undergoing multivisceral cytoreductive surgery. Severe postoperative complications according to the Clavien-Dindo classification were used as a grouping criterion.

RESULTS

The relative change from the baseline to the first intraoperative timepoint showed a reduced heart rate (HR, median - 19 [25-quartile - 26%; 75-quartile - 10%]%, p < 0.0001), stroke volume index (SVI, - 9.5 [- 15.3; 3.2]%, p = 0.0038), cardiac index (CI, - 24.5 [- 32; - 13]%, p < 0.0001) and index of contractility (- 17.5 [- 35.3; - 0.8]%, p < 0.0001). Throughout the perioperative course, patients had intraoperatively a reduced HR and CI (both p < 0.0001) and postoperatively an increased HR (p < 0.0001) and CI (p = 0.016), whereas SVI was unchanged. Thoracic fluid volume increased continuously versus preoperative values and did not normalise up to the day of discharge. Patients having postoperative complications showed a lower index of contractility (p = 0.0435) and a higher systolic time ratio (p = 0.0008) over the perioperative course in comparison to patients without complications, whereas the CI (p = 0.3337) was comparable between groups. One patient had to be excluded from data analysis for not receiving the planned surgery.

CONCLUSIONS

Substantial decreases in HR, SVI, CI, and index of contractility occurred from the day before surgery to the first intraoperative timepoint. HR and CI were altered throughout the perioperative course. Patients with postoperative complications differed from patients without complications in the markers of cardiac function, a lower index of contractility and a lower SVI. The analyses of trends over the whole perioperative time course by using non-invasive technologies like EC seem to be useful to identify patients with altered haemodynamic parameters and therefore at an increased risk for postoperative complications after major surgery.

Electrocardiographic Time-Intervals Waveforms as Potential Predictors for Severe Acute Kidney Injury in Critically Ill Patients

Background: Acute kidney injury (AKI) is common in critically ill patients admitted to intensive care units (ICU) and is frequently associated with poorer outcomes. Hence, if an indicator is available for predicting severe AKI within the first few hours of admission, management strategies can be put into place to improve outcomes. Materials and methods: This was a prospective, observational study, involving 63 critically ill patients, that aimed to explore the diagnostic accuracy of different Doppler parameters in predicting AKI in critically ill patients from a mixed ICU. Participants were enrolled at ICU admission. All underwent ultrasonographic examinations and hemodynamic assessment. Renal Doppler resistive index (RDRI), venous impedance index (VII), arterial systolic time intervals (a-STI), and venous systolic time intervals (v-STI) were measured within 2 h from ICU admission. Results: Cox proportional hazards models, including a-STI, v-STI, VII, and RDRI as independent variables, returned a-STI as the only putative predictor for the development of AKI or severe AKI. An overall statistically significant difference (p < 0.001) was observed in the Kaplan−Meier plots for cumulative AKI events between patients with a-STI higher or equal than 0.37 and for cumulative severe AKI-3 between patients with a-STI higher or equal than 0.63. As assessed by the area under the receiver operating curves (ROC) curves, a-STI performed best in diagnosing any AKI and/or severe AKI-3. Positive correlations were found between a-STI and the N-terminal brain natriuretic peptide precursor (NT-pro BNP) (ρ = 0.442, p < 0.001), the sequential organ failure assessment (SOFA) score (ρ: 0.361, p = 0.004), and baseline serum creatinine (ρ: 0.529, p < 0.001). Conclusions: Critically ill patients who developed AKI had statistically significant different a-STI (on admission to ICU), v-STI, and VII than those who did not. Moreover, a-STI was associated with the development of AKI at day 5 and provided the best diagnostic accuracy for the diagnosis of any AKI or severe AKI compared with RDRI, VII, and v-STI.

Computer-Aided Detection of Fiducial Points in Seismocardiography through Dynamic Time Warping

Accelerometer-based devices have been employed in seismocardiography fiducial point detection with the aid of quasi-synchronous alignment between echocardiography images and seismocardiogram signals. However, signal misalignments have been observed, due to the heartbeat cycle length variation. This paper not only analyzes the misalignments and detection errors but also proposes to mitigate the issues by introducing reference signals and adynamic time warping (DTW) algorithm. Two diagnostic parameters, the ratio of pre-ejection period to left ventricular ejection time (PEP/LVET) and the Tei index, were examined with two statistical verification approaches: (1) the coefficient of determination (R2) of the parameters versus the left ventricular ejection fraction (LVEF) assessments, and (2) the receiver operating characteristic (ROC) classification to distinguish the heart failure patients with reduced ejection fraction (HFrEF). Favorable R2 values were obtained, R2 = 0.768 for PEP/LVET versus LVEF and R2 = 0.86 for Tei index versus LVEF. The areas under the ROC curve indicate the parameters that are good predictors to identify HFrEF patients, with an accuracy of more than 92%. The proof-of-concept experiments exhibited the effectiveness of the DTW-based quasi-synchronous alignment in seismocardiography fiducial point detection. The proposed approach may enable the standardization of the fiducial point detection and the signal template generation. Meanwhile, the program-generated annotation data may serve as the labeled training set for the supervised machine learning.

Complex sympathetic regulation in adolescent mitral valve prolapse

Mitral valve prolapse (MVP) belongs to cardiac disorders characterized by impaired closure of mitral leaflets. We studied adolescent group of patients with MVP suffering from symptomatology that cannot be explained by mitral regurgitation alone. Several studies suggested that symptoms can be explained by autonomic, in particular sympathetic-linked dysfunction. Thus, we assessed non-invasive sympathetic indices of blood pressure and heart rate variability and electrodermal activity (EDA). Fifty-three adolescents with MVP (age: 15.1+/-0.4 years) and 43 healthy age- and gender-matched adolescents (age: 14.9+/-0.4 years) were examined. Blood pressure, heart rate and EDA were continuously recorded during 6-min rest. Evaluated parameters were: low frequency band of systolic blood pressure variability, systolic, diastolic and mean blood pressure, mean RR interval, cardiac sympathetic indices: symbolic dynamics (0V%), left ventricular ejection time (LVET), pre-ejection period (PEP), and EDA. Our findings revealed significantly higher systolic, diastolic, and mean blood pressure values, shortened mean RR interval, increased 0V%, and shortened LVET in MVP patients vs. controls (p=0.028, p<0.001, p=0.002, p<0.001, p=0.050, p<0.001; respectively). Our study revealed enhanced cardiovascular sympathetic regulation in adolescent MVP patients. We suggest that evaluation of non-invasive sympathetic parameters could represent potential biomarkers for early diagnosis of cardiovascular complications associated with MVP already at adolescent age.

Automated Assessment of the Quality of Phonocardographic Recordings through Signal-to-Noise Ratio for Home Monitoring Applications

The signal quality limits the applicability of phonocardiography at the patients’ domicile. This work proposes the signal-to-noise ratio of the recorded signal as its main quality metrics. Moreover, we define the minimum acceptable values of the signal-to-noise ratio that warrantee an accuracy of the derived parameters acceptable in clinics. We considered 25 original heart sounds recordings, which we corrupted by adding noise to decrease their signal-to-noise ratio. We found that a signal-to-noise ratio equal to or higher than 14 dB warrants an uncertainty of the estimate of the valve closure latencies below 1 ms. This accuracy is higher than that required by most clinical applications. We validated the proposed method against a public database, obtaining results comparable to those obtained on our sample population. In conclusion, we defined (a) the signal-to-noise ratio of the phonocardiographic signal as the preferred metric to evaluate its quality and (b) the minimum values of the signal-to-noise ratio required to obtain an uncertainty of the latency of heart sound components compatible with clinical applications. We believe these results are crucial for the development of home monitoring systems aimed at preventing acute episodes of heart failure and that can be safely operated by naïve users.

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.

Motivation-Achievement Cycles in Learning: a Literature Review and Research Agenda

The question of how learners’ motivation influences their academic achievement and vice versa has been the subject of intensive research due to its theoretical relevance and important implications for the field of education. Here, we present our understanding of how influential theories of academic motivation have conceptualized reciprocal interactions between motivation and achievement and the kinds of evidence that support this reciprocity. While the reciprocal nature of the relationship between motivation and academic achievement has been established in the literature, further insights into several features of this relationship are still lacking. We therefore present a research agenda where we identify theoretical and methodological challenges that could inspire further understanding of the reciprocal relationship between motivation and achievement as well as inform future interventions. Specifically, the research agenda includes the recommendation that future research considers (1) multiple motivation constructs, (2) behavioral mediators, (3) a network approach, (4) alignment of intervals of measurement and the short vs. long time scales of motivation constructs, (5) designs that meet the criteria for making causal, reciprocal inferences, (6) appropriate statistical models, (7) alternatives to self-reports, (8) different ways of measuring achievement, and (9) generalizability of the reciprocal relations to various developmental, ethnic, and sociocultural groups.

The Delineation of Fiducial Points for Non-Contact Radar Seismocardiogram Signals Without Concurrent ECG

OBJECTIVE

Non-contact sensing of seismocardiogram (SCG) signals through a microwave Doppler radar is promising for biomedical applications. However, the delineation of fiducial points for radar SCG still relies on concurrent ECG which requires a contact sensor and limits the complete non-contact detection of SCG.

METHODS

Instead of ECG, a new reference signal, the radar displacement signal of heartbeat (RDH), was derived through the complex Fourier transform and the band pass filtering of the radar signal. The RDH signal was used to locate each cardiac cycle and mask the systolic profile, which was further used to detect an important fiducial point, aortic valve opening (AO). The beat-to-beat interval was estimated from AO-AO interval and compared with the gold standard, ECG R-to-R interval.

RESULTS

For the 22 subjects in the study, the evaluation of the AOs detected by RDH (AO_RDH) shows the average detection ratio can reach 90%, indicating a high ratio of the AO_RDH that are exactly the same as AO detected using the ECG R-wave (AO_ECG). Additionally, the left ventricular ejection time (LVET) values estimated from the ensemble averaged radar waveform through AO_RDH segmentation are within 2 ms of those through AO_ECG segmentation, for all the detected subjects. Further analysis demonstrates that the beat-to-beat intervals calculated from AO_RDH have an average root-mean-square-deviation (RMSD) of 53.73 ms when compared with ECG R-to-R intervals, and have an average RMSD of 23.47 ms after removing the beats in which AO cannot be identified.

CONCLUSIONS

Radar signal RDH can be used as a reference signal to delineate fiducial points for non-contact radar SCG signals.

SIGNIFICANCE

This study can be applied to develop complete non-contact sensing of SCG and monitoring of vital signs, where contact-based SCG is not feasible.

The significance of left ventricular ejection time in heart failure with reduced ejection fraction

Left ventricular ejection time (LVET) is defined as the time interval from aortic valve opening to aortic valve closure, and is the phase of systole during which the left ventricle ejects blood into the aorta. LVET has been used for several decades to assess left ventricular function and contractility. However, there is a recent interest in LVET as a measure of therapeutic action for novel drugs in patients with heart failure with reduced ejection fraction (HFrEF), since LVET is shortened in these patients. This review provides an overview of the available information on LVET including methods of measuring LVET, mechanistic understanding of LVET, association of LVET with outcomes, mechanisms behind shortened LVET in HFrEF and the potential implications of drugs that affect and normalize LVET.

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.

Value of systolic time intervals in the diagnosis of heart failure in emergency department patients with undifferentiated dyspnea

AIM OF THE STUDY

The diagnosis of heart failure in the emergency department (ED) is challenging. The aim of this study was to evaluate systolic time intervals (STIs) using phonoelectrocardiography for the diagnosis of heart failure (HF) in ED patients with undifferentiated dyspnea.

METHODS

A total of 855 patients with dyspnea and suspected HF were prospectively enrolled. They underwent echocardiographic measurements of left ventricular ejection fraction (LVEF), B-type natriuretic peptide (BNP) testing and computerised phonoelectrocardiography to assess STIs including electromechanical activation time (EMAT), left ventricular ejection time (LVET) and EMAT/LVET ratio. Diagnosis accuracy of STIs was calculated including sensitivity, specificity, likelihood ratio and receiver operating characteristic (ROC) curve.

RESULTS

Patients with HF (n = 530) had significantly higher EMAT and lower LVET compared with non-HF patients. ROC curve c-statistic was 0.74, 0.72 and 0.78 for EMAT, LVET and EMAT/LVET respectively. Sensitivity and specificity of EMAT/LVET at a cut-off = 40% were 72% and 88% respectively. EMAT/LVET had the highest correlation with LVEF (r = 0.48). In patients with intermediate BNP (n = 107), positive likelihood ratio increased from 1.8 with BNP alone to 3.6 with BNP combined to EMAT/LVET. Patients without HF had STIs values not significantly different from those with preserved LVEF (≥45%).

CONCLUSIONS

Given their immediate availability, phonoelectrocardiography STIs' parameters and particularly EMAT/LVET ratio could have an important role in the diagnosis approach of HF in patients with undifferentiated dyspnea in the ED.

Wearable Cardiorespiratory Monitoring Employing a Multimodal Digital Patch Stethoscope: Estimation of ECG, PEP, LVETand Respiration Using a 55 mm Single-Lead ECG and Phonocardiogram

Cardiovascular diseases are the main cause of death worldwide, with sleep disordered breathing being a further aggravating factor. Respiratory illnesses are the third leading cause of death amongst the noncommunicable diseases. The current COVID-19 pandemic, however, also highlights the impact of communicable respiratory syndromes. In the clinical routine, prolonged postanesthetic respiratory instability worsens the patient outcome. Even though early and continuous, long-term cardiorespiratory monitoring has been proposed or even proven to be beneficial in several situations, implementations thereof are sparse. We employed our recently presented, multimodal patch stethoscope to estimate Einthoven electrocardiogram (ECG) Lead I and II from a single 55 mm ECG lead. Using the stethoscope and ECG subsystems, the pre-ejection period (PEP) and left ventricular ejection time (LVET) were estimated. ECG-derived respiration techniques were used in conjunction with a novel, phonocardiogram-derived respiration approach to extract respiratory parameters. Medical-grade references were the SOMNOmedics SOMNO HDTM and Osypka ICON-CoreTM. In a study including 10 healthy subjects, we analyzed the performances in the supine, lateral, and prone position. Einthoven I and II estimations yielded correlations exceeding 0.97. LVET and PEP estimation errors were 10% and 21%, respectively. Respiratory rates were estimated with mean absolute errors below 1.2 bpm, and the respiratory signal yielded a correlation of 0.66. We conclude that the estimation of ECG, PEP, LVET, and respiratory parameters is feasible using a wearable, multimodal acquisition device and encourage further research in multimodal signal fusion for respiratory signal estimation.

The repeatability of estimated systolic time intervals in healthy subjects using seismocardiogram and electrocardiogram

OBJECTIVE

We investigated the repeatability of systolic time intervals (STIs) in healthy subjects using a combination of seismocardiogram (SCG) and electrocardiogram (ECG). STIs have been extensively used in the past to quantify heart performance, particularly the left ventricle. In this study, STIs included pre-ejection period (PEP), left ventricular ejection time (LVET), and their ratio.

APPROACH

We conducted the repeatability test of STI estimation through two experiments. The first involved three consecutive one-minute recordings separated by one-minute intervals, and the second involved two one-minute recordings separated by 24 h. Twenty healthy subjects participated in our study. We considered the coefficient of variation (CV) to quantify the repeatability. As there was no agreed upon values for optimal CV values, we compared our results with an alternative method using a combination of impedance cardiography (ICG) and ECG. Similar to our method, the alternative method was noninvasive and could be employed for personal heart monitoring. We also studied the repeatability after STIs were corrected for heart rate using two approaches. The first approach used a multiplicative factor per subject based on the heart rates in each recordings of that subject. The second approach employed sex-specific regression models for all subjects (Weissler's equations).

MAIN RESULTS

We found that the repeatability of our method (SCG and ECG) was in agreement with the alternative method (ICG and ECG) in both experiments. Moreover, the Weissler's equations approach for heart rate increased the repeatability.

SIGNIFICANCE

It can be concluded that estimation of PEP, LVET and their ratio through SCG and ECG signals was repeatable in healthy subjects.

Automatic analysis of pre-ejection period during sleep using impedance cardiogram

The pre-ejection period (PEP) is a valid index of myocardial contractility and beta-adrenergic sympathetic control of the heart defined as the time between electrical systole (ECG Q wave) to the initial opening of the aortic valve, estimated as the B point on the impedance cardiogram (ICG). B-point detection accuracy can be severely impacted if ICG cardiac cycles corrupted by motion artifact, noise, or electrode displacement are included in the analyses. Here, we developed new algorithms to detect and exclude corrupted ICG cycles by analyzing their level of activity. PEP was then estimated and analyzed on ensemble-averaged clean ICG cycles using an automatic algorithm previously developed by the authors for the detection of B point in awake individuals. We investigated the algorithms' performance relative to expert visual scoring on long-duration data collected from 20 participants during overnight recordings, where the quality of ICG could be highly affected by movement artifacts and electrode displacements and the signal could also vary according to sleep stage and time of night. The artifact rejection algorithm achieved a high accuracy of 87% in detection of expert-identified corrupted ICG cycles, including those with normal amplitude as well as out-of-range values, and was robust to different types and levels of artifact. Intraclass correlations for concurrent validity of the B-point detection algorithm in different sleep stages and in-bed wakefulness exceeded 0.98, indicating excellent agreement with the expert. The algorithms show promise toward sleep applications requiring accurate and reliable automatic measurement of cardiac hemodynamic parameters.

Performance Analysis of Gyroscope and Accelerometer Sensors for Seismocardiography-Based Wearable Pre-Ejection Period Estimation

OBJECTIVE

Systolic time intervals, such as the pre-ejection period (PEP), are important parameters for assessing cardiac contractility that can be measured non-invasively using seismocardiography (SCG). Recent studies have shown that specific points on accelerometer- and gyroscope-based SCG signals can be used for PEP estimation. However, the complex morphology and inter-subject variation of the SCG signal can make this assumption very challenging and increase the root mean squared error (RMSE) when these techniques are used to develop a global model.

METHODS

In this study, we compared gyroscope- and accelerometer-based SCG signals, individually and in combination, for estimating PEP to show the efficacy of these sensors in capturing valuable information regarding cardiovascular health. We extracted general time-domain features from all the axes of these sensors and developed global models using various regression techniques.

RESULTS

In single-axis comparison of gyroscope and accelerometer, angular velocity signal around head to foot axis from the gyroscope provided the lowest RMSE of 12.63 ± 0.49 ms across all subjects. The best estimate of PEP, with a RMSE of 11.46 ± 0.32 ms across all subjects, was achieved by combining features from the gyroscope and accelerometer. Our global model showed 30% lower RMSE when compared to algorithms used in recent literature.

CONCLUSION

Gyroscopes can provide better PEP estimation compared to accelerometers located on the mid-sternum. Global PEP estimation models can be improved by combining general time domain features from both sensors.

SIGNIFICANCE

This work can be used to develop a low-cost wearable heart-monitoring device and to generate a universal estimation model for systolic time intervals using a single- or multiple-sensor fusion.

High-Resolution Seismocardiogram Acquisition and Analysis System

Several devices and measurement approaches have recently been developed to perform ballistocardiogram (BCG) and seismocardiogram (SCG) measurements. The development of a wireless acquisition system (hardware and software), incorporating a novel high-resolution micro-electro-mechanical system (MEMS) accelerometer for SCG and BCG signals acquisition and data treatment is presented in this paper. A small accelerometer, with a sensitivity of up to 0.164 µs/µg and a noise density below 6.5 µg/Hz is presented and used in a wireless acquisition system for BCG and SCG measurement applications. The wireless acquisition system also incorporates electrocardiogram (ECG) signals acquisition, and the developed software enables the real-time acquisition and visualization of SCG and ECG signals (sensor positioned on chest). It then calculates metrics related to cardiac performance as well as the correlation of data from previously performed sessions with echocardiogram (ECHO) parameters. A preliminarily clinical study of over 22 subjects (including healthy subjects and cardiovascular patients) was performed to test the capability of the developed system. Data correlation between this measurement system and echocardiogram exams is also performed. The high resolution of the MEMS accelerometer used provides a better signal for SCG wave recognition, enabling a more consistent study of the diagnostic capability of this technique in clinical analysis.

Systolic time intervals assessed from analysis of the carotid pressure waveform

OBJECTIVE

The timing of mechanical cardiac events is usually evaluated by conventional echocardiography as an index of cardiac systolic function and predictor of cardiovascular outcomes. We aimed to measure the systolic time intervals, namely the isovolumetric contraction time (ICT) and pre-ejection period (PEP), by arterial tonometry.

APPROACH

Sixty-two healthy volunteers (age 47  ±  17 years) and 42 patients with heart failure and reduced ejection fraction were enrolled (age 66  ±  14 years). Pulse waves were recorded at the carotid artery by arterial tonometry together with simultaneous aortic transvalvular flow by Doppler-echocardiography, synchronized by electrocardiographic gating. The ICT was determined from the time delay between the electrical R wave and the carotid pressure waveform, after adjustment for the pulse transit time from the aortic valve to the carotid artery site, estimated by an algorithm based on the carotid-femoral pulse wave velocity. The PEP was evaluated by adding the electrical QR duration to the ICT.

MAIN RESULTS

The ICT derived from carotid pulse wave analysis was closely related to that measured by echocardiography (r  =  0.90, p  <  0.0001), with homogeneous distribution in Bland-Altman analysis (mean difference and 95% confidence interval  =  0.2 from  -14.2 to 14.5 ms). ICT and PEP were higher in cardiac patients than in healthy volunteers (p  <  0.0001). The ratio between PEP and left ventricular ejection time was related to the ejection fraction measured with echocardiography (r  =  0.555, p  <  0.0001).

SIGNIFICANCE

The timing of electro-mechanical cardiac events can be reliably obtained from the carotid pulse waveform and carotid-femoral PWV, evaluated using arterial tonometry. Systolic time intervals assessed with this approach showed good agreement with measurements performed with conventional echocardiography and may represent a promising additional application of arterial tonometry.

Toward a better noninvasive assessment of preejection period: A novel automatic algorithm for B-point detection and correction on thoracic impedance cardiogram

Impedance cardiography is the most common clinically validated, noninvasive method for determining the timing of the opening of the aortic valve, an important event used for measuring preejection period, which reflects sympathetic beta-adrenergic influences on the heart. Automatic detection of the exact time of the opening of the aortic valve (B point on the impedance cardiogram) has proven to be challenging as its appearance varies between and within individuals and may manifest as a reversal, inflection, or rapid slope change of the thoracic impedance derivative's (dZ/dt) rapid rise. Here, a novel automatic algorithm is proposed for the detection of the B point by finding the main rapid rise of the dZ/dt signal, which is due to blood ejection. Several conditions based on zero crossings, minima, and maxima of the dZ/dt signal and its derivatives are considered to reject any unwanted noise and artifacts and select the true B-point location. The detected B-point locations are then corrected by modeling the B-point time data using forward and reverse autoregressive models. The proposed algorithm is validated against expert-detected B points and is compared with different conventional methods; it significantly outperforms them by at least 54% in mean error, 30% in mean absolute error, and 27% in standard deviation of error. This algorithm can be adopted in ambulatory studies requiring beat-to-beat evaluation of cardiac hemodynamic parameters over extended time periods where expert scoring is not feasible.

Comprehensive computational assessment of blood flow characteristics of left ventricle based on in-vivo MRI in presence of artificial myocardial infarction

BACKGROUND

Understanding the effects of cardiac diseases on the heart's functionality which is the purpose of many biomedical researches, directly affects the diagnostic and therapeutic methods. Myocardial infarction (MI) is a common complication of cardiac ischemia, however, the impact of MI on the left ventricle (LV) flow patterns has not been widely considered by computational fluid dynamics studies thus far.

METHODS

In this study, we present an insightful numerical method that creates an artificial MI on an image-based fluid-structure interactional model of normal LV to investigate its influence on the flow in comparison with the normal case. Seventeen different models were developed to evaluate the effects of location, percentage, myocardial material properties and dilation size of MI on the LV's performance, area strain, wall displacement, pressure-volume loop, wall shear stress and velocity field.

RESULTS

The results show that MI considerably changes blood flow features which are fully dependent on MI parameters. For the case of constant MI location, the effect of a decrease of infarcted myocardium stiffness, increase of dilation size and increase of MI percentage are mostly similar. Although the location differences of MI under other constant conditions have similar impact on the ejection fraction, they also lead to dissimilar variations in the LV flow pattern and other indicators.

CONCLUSIONS

The presented model showed a capable computational method for investigating various mechanical MI conditions with respect to cardiac flow pattern. The perspective of this model development seems to be an applicable tool for MI clinical diagnosis and prediction of complications related to MI.

Systolic Time Interval Estimation Using Continuous Wave Radar With On-Body Antennas

The estimation of systolic time intervals (STIs) is done using continuous wave (CW) radar at 2.45 GHz with an on-body antenna.

MOTIVATION

In the state of the art, typically bioimpedance, heart sounds and/or ultrasound are used to measure STIs. All three methods suffer from insufficient accuracy of STI estimation due to various reasons. CW radar is investigated for its ability to overcome the deficiencies in the state of the art.

METHODS

Ten healthy male subjects aged 25-45 were asked to lie down at a 30 incline. Recordings of 60 s were taken without breathing and with paced breathing. Heart sounds, electrocardiogram, respiration, and impedance cardiogram were measured simultaneously as reference. The radar antennas were placed at two positions on the chest. The antennas were placed directly on the body as well as with cotton textile in between. The beat to beat STIs have been determined from the reference signals as well as CW radar signals.

RESULTS

The results indicate that CW radar can be used to estimate STIs in ambulatory monitoring.

SIGNIFICANCE

The results pave way to a potentially more compact method of estimating STIs, which can be integrated into a wearable device.

Renal systolic time intervals derived from intra-renal artery Doppler as a novel predictor of adverse cardiac outcomes

The aim of this study was to evaluate the use of renal systolic time intervals measured by electrocardiographic gated Doppler ultrasonography for predicting adverse cardiac events. This longitudinal observation study enrolled 205 patients. Renal systolic time intervals, including pre-ejection period (PEP) and ejection time (ET), and ratio of renal PEP to ET, were measured by electrocardiographic gated Doppler ultrasound. The 14 adverse cardiac events identified in this population included 9 cardiac deaths and 5 hospitalizations for heart failure during an average follow up of 30.9 months (25^th-75^th percentile: 30-33 months). Renal PEP (hazard ratio = 1.023, P = 0.001), renal ET (hazard ratio = 0.975, P = 0.001) and renal PEP/ET (per 0.01 unit increase, hazard ratio = 1.060, P < 0.001) were associated with poor cardiac outcomes. The addition of renal PEP/ET to a Cox model containing important clinical variables and renal resistive index further improved the value in predicting adverse cardiac events (Chi-square increase, 9.996; P = 0.002). This study showed that parameters of intra-renal hemodynamics were potential predictors of adverse cardiac outcomes. However, the generalizability of these indicators need to be investigated in future large-scale studies.

Automatic and Robust Delineation of the Fiducial Points of the Seismocardiogram Signal for Non-invasive Estimation of Cardiac Time Intervals

OBJECTIVE

The purpose of this research was to design a delineation algorithm that could detect specific fiducial points of the seismocardiogram (SCG) signal with or without using the electrocardiogram (ECG) R-wave as the reference point. The detected fiducial points were used to estimate cardiac time intervals. Due to complexity and sensitivity of the SCG signal, the algorithm was designed to robustly discard the low-quality cardiac cycles, which are the ones that contain unrecognizable fiducial points.

METHOD

The algorithm was trained on a dataset containing 48,318 manually annotated cardiac cycles. It was then applied to three test datasets: 65 young healthy individuals (dataset 1), 15 individuals above 44 years old (dataset 2), and 25 patients with previous heart conditions (dataset 3).

RESULTS

The algorithm accomplished high prediction accuracy with the rootmean- square-error of less than 5 ms for all the test datasets. The algorithm overall mean detection rate per individual recordings (DRI) were 74, 68, and 42 percent for the three test datasets when concurrent ECG and SCG were used. For the standalone SCG case, the mean DRI was 32, 14 and 21 percent.

CONCLUSION

When the proposed algorithm applied to concurrent ECG and SCG signals, the desired fiducial points of the SCG signal were successfully estimated with a high detection rate. For the standalone case, however, the algorithm achieved high prediction accuracy and detection rate for only the young individual dataset.

SIGNIFICANCE

The presented algorithm could be used for accurate and non-invasive estimation of cardiac time intervals.

A Hidden Markov Model for Seismocardiography

We propose a hidden Markov model approach for processing seismocardiograms. The seismocardiogram morphology is learned using the expectation-maximization algorithm, and the state of the heart at a given time instant is estimated by the Viterbi algorithm. From the obtained Viterbi sequence, it is then straightforward to estimate instantaneous heart rate, heart rate variability measures, and cardiac time intervals (the latter requiring a small number of manual annotations). As is shown in the conducted experimental study, the presented algorithm outperforms the state-of-the-art in seismocardiogram-based heart rate and heart rate variability estimation. Moreover, the isovolumic contraction time and the left ventricular ejection time are estimated with mean absolute errors of about 5 [ms] and [Formula: see text], respectively. The proposed algorithm can be applied to any set of inertial sensors; does not require access to any additional sensor modalities; does not make any assumptions on the seismocardiogram morphology; and explicitly models sensor noise and beat-to-beat variations (both in amplitude and temporal scaling) in the seismocardiogram morphology. As such, it is well suited for low-cost implementations using off-the-shelf inertial sensors and targeting, e.g., at-home medical services.

Automatic Identification of Systolic Time Intervals in Seismocardiogram

Continuous and non-invasive monitoring of hemodynamic parameters through unobtrusive wearable sensors can potentially aid in early detection of cardiac abnormalities, and provides a viable solution for long-term follow-up of patients with chronic cardiovascular diseases without disrupting the daily life activities. Electrocardiogram (ECG) and siesmocardiogram (SCG) signals can be readily acquired from light-weight electrodes and accelerometers respectively, which can be employed to derive systolic time intervals (STI). For this purpose, automated and accurate annotation of the relevant peaks in these signals is required, which is challenging due to the inter-subject morphological variability and noise prone nature of SCG signal. In this paper, an approach is proposed to automatically annotate the desired peaks in SCG signal that are related to STI by utilizing the information of peak detected in the sliding template to narrow-down the search for the desired peak in actual SCG signal. Experimental validation of this approach performed in conventional/controlled supine and realistic/challenging seated conditions, containing over 5600 heart beat cycles shows good performance and robustness of the proposed approach in noisy conditions. Automated measurement of STI in wearable configuration can provide a quantified cardiac health index for long-term monitoring of patients, elderly people at risk and health-enthusiasts.

Systolic time intervals derived from electrocardiographic gated intra-renal artery Doppler waveform associated with left ventricular systolic function

The aims of this study were to investigate the correlation between renal and cardiac STIs, including pre-ejection period (PEP), ejection time (ET), and PEP/ET, and to assess the diagnostic values of renal STIs in predicting left ventricular ejection fraction (LVEF) <50%. The cross sectional observation study enrolled 230 participants. The renal STIs, including renal PEP (rPEP), renal ET (rET), and rPEP/rET, were measured from electrocardiographic gated renal Doppler ultrasound and cardiac PEP, ET, and PEP/ET were measured from echocardiography. Renal STIs were correlated with cardiac STIs (all P < 0.001). Multivariate analyses showed that rPEP/rET was independently associated with LVEF (unstandardized coefficient β = −0.116, P = 0.046) and LVEF <50% (odds ratio = 2.145, per 0.11 increase; P = 0.017). The areas under the curve for rPEP, 1/rET, and rPEP/rET in predicting LVEF <50% were 0.773, 0.764, and 0.821, respectively. The sensitivity and specificity of rPEP/rET > 0.46 in prediction of LVEF <50% were 76.7% and 78.1%, respectively. Our study demonstrated that the novel parameters of renal STIs were significantly associated with cardiac STIs. However, the clinical application of renal STIs needs to be investigated in future studies.