Multi-dimensional Kineticardiography a New Approach for Wearable Cardiac Monitoring Through Body Acceleration Recordings

Camera-Based Seismocardiogram for Heart Rate Variability Monitoring

Heart rate variability (HRV) is a crucial metric that quantifies the variation between consecutive heartbeats, serving as a significant indicator of autonomic nervous system (ANS) activity. It has found widespread applications in clinical diagnosis, treatment, and prevention of cardiovascular diseases. In this study, we proposed an optical model for defocused speckle imaging, to simultaneously incorporate out-of-plane translation and rotation-induced motion for highly-sensitive non-contact seismocardiogram (SCG) measurement. Using electrocardiogram (ECG) signals as the gold standard, we evaluated the performance of photoplethysmogram (PPG) signals and speckle-based SCG signals in assessing HRV. The results indicated that the HRV parameters measured from SCG signals extracted from laser speckle videos showed higher consistency with the results obtained from the ECG signals compared to PPG signals. Additionally, we confirmed that even when clothing obstructed the measurement site, the efficacy of SCG signals extracted from the motion of laser speckle patterns persisted in assessing the HRV levels. This demonstrates the robustness of camera-based non-contact SCG in monitoring HRV, highlighting its potential as a reliable, non-contact alternative to traditional contact-PPG sensors.

Comparison between Chest-Worn Accelerometer and Gyroscope Performance for Heart Rate and Respiratory Rate Monitoring

The demand for wearable devices to simultaneously monitor heart rate (HR) and respiratory rate (RR) values has grown due to the incidence increase in cardiovascular and respiratory diseases. The use of inertial measurement unit (IMU) sensors, embedding both accelerometers and gyroscopes, may ensure a non-intrusive and low-cost monitoring. While both accelerometers and gyroscopes have been assessed independently for both HR and RR monitoring, there lacks a comprehensive comparison between them when used simultaneously. In this study, we used both accelerometers and gyroscopes embedded in a single IMU sensor for the simultaneous monitoring of HR and RR. The following main findings emerged: (i) the accelerometer outperformed the gyroscope in terms of accuracy in both HR and RR estimation; (ii) the window length used to estimate HR and RR values influences the accuracy; and (iii) increasing the length over 25 s does not provide a relevant improvement, but accuracy improves when the subject is seated or lying down, and deteriorates in the standing posture. Our study provides a comprehensive comparison between two promising systems, highlighting their potentiality for real-time cardiorespiratory monitoring. Furthermore, we give new insights into the influence of window length and posture on the systems' performance, which can be useful to spread this approach in clinical settings.

Closed-Loop Multiscale Computational Model of Human Blood Circulation. Applications to Ballistocardiography

Cardiac mechanical activity leads to periodic changes in the distribution of blood throughout the body, which causes micro-oscillations of the body's center of mass and can be measured by ballistocardiography (BCG). However, many of the BCG findings are based on parameters whose origins are poorly understood. Here, we generate simulated multidimensional BCG signals based on a more exhaustive and accurate computational model of blood circulation than previous attempts. This model consists in a closed loop 0D-1D multiscale representation of the human blood circulation. The 0D elements include the cardiac chambers, cardiac valves, arterioles, capillaries, venules, and veins, while the 1D elements include 55 systemic and 57 pulmonary arteries. The simulated multidimensional BCG signal is computed based on the distribution of blood in the different compartments and their anatomical position given by whole-body magnetic resonance angiography on a healthy young subject. We use this model to analyze the elements affecting the BCG signal on its different axes, allowing a better interpretation of clinical records. We also evaluate the impact of filtering and healthy aging on the BCG signal. The results offer a better view of the physiological meaning of BCG, as compared to previous models considering mainly the contribution of the aorta and focusing on longitudinal acceleration BCG. The shape of experimental BCG signals can be reproduced, and their amplitudes are in the range of experimental records. The contributions of the cardiac chambers and the pulmonary circulation are non-negligible, especially on the lateral and transversal components of the velocity BCG signal. The shapes and amplitudes of the BCG waveforms are changing with age, and we propose a scaling law to estimate the pulse wave velocity based on the time intervals between the peaks of the acceleration BCG signal. We also suggest new formulas to estimate the stroke volume and its changes based on the BCG signal expressed in terms of acceleration and kinetic energy.

Quantification of Cardiac Kinetic Energy and Its Changes During Transmural Myocardial Infarction Assessed by Multi-Dimensional Seismocardiography

Introduction: Seismocardiography (SCG) records cardiac and blood-induced motions transmitted to the chest surface as vibratory phenomena. Evidences demonstrate that acute myocardial ischemia (AMI) profoundly affects the SCG signals. Multidimensional SCG records cardiac vibrations in linear and rotational dimensions, and scalar parameters of kinetic energy can be computed. We speculate that AMI and revascularization profoundly modify cardiac kinetic energy as recorded by SCG.

Methods: Under general anesthesia, 21 swine underwent 90 min of myocardial ischemia induced by percutaneous sub-occlusion of the proximal left anterior descending (LAD) coronary artery and subsequent revascularization. Invasive hemodynamic parameters were continuously recorded. SCG was recorded during baseline, immediately and 80 min after LAD sub-occlusion, and immediately and 60 min after LAD reperfusion. iK was automatically computed for each cardiac cycle (iK^CC) in linear (iK_Lin) and rotational (iK_Rot) dimensions. iK was calculated as well during systole and diastole (iK^Sys and iK^Dia, respectively). Echocardiography was performed at baseline and after revascularization, and the left ventricle ejection fraction (LVEF) along with regional left ventricle (LV) wall abnormalities were evaluated.

Results: Upon LAD sub-occlusion, 77% of STEMI and 24% of NSTEMI were observed. Compared to baseline, troponins increased from 13.0 (6.5; 21.3) ng/dl to 170.5 (102.5; 475.0) ng/dl, and LVEF dropped from 65.0 ± 0.0 to 30.6 ± 5.7% at the end of revascularization (both p < 0.0001). Regional LV wall abnormalities were observed as follows: anterior MI, 17.6% (three out of 17); septal MI, 5.8% (one out of 17); antero-septal MI, 47.1% (eight out of 17); and infero-septal MI, 29.4% (five out of 17). In the linear dimension, iKLinCC, iKLinSys, and iKLinDia dropped by 43, 52, and 53%, respectively (p < 0.0001, p < 0.0001, and p = 0.03, respectively) from baseline to the end of reperfusion. In the rotational dimension, iKRotCC and iKRotSys dropped by 30 and 36%, respectively (p = 0.0006 and p < 0.0001, respectively), but iKRotDia did not change (p = 0.41). All the hemodynamic parameters, except the pulmonary artery pulse pressure, were significantly correlated with the parameters of iK, except for the diastolic component.

Conclusions: In this very context of experimental AMI with acute LV regional dysfunction and no concomitant AMI-related heart valve disease, linear and rotational iK parameters, in particular, systolic ones, provide reliable information on LV contractile dysfunction and its effects on the downstream circulation. Multidimensional SCG may provide information on the cardiac contractile status expressed in terms of iK during AMI and reperfusion. This automatic system may empower health care providers and patients to remotely monitor cardiovascular status in the near future.

Assessment of left ventricular twist by 3D ballistocardiography and seismocardiography compared with 2D STI echocardiography in a context of enhanced inotropism in healthy subjects

Ballistocardiography (BCG) and Seismocardiography (SCG) assess the vibrations produced by cardiac contraction and blood flow, respectively, by means of micro-accelerometers and micro-gyroscopes. From the BCG and SCG signals, maximal velocities (VMax), integral of kinetic energy (iK), and maximal power (PMax) can be computed as scalar parameters, both in linear and rotational dimensions. Standard echocardiography and 2-dimensional speckle tracking imaging echocardiography were performed on 34 healthy volunteers who were infused with increasing doses of dobutamine (5-10-20 μg/kg/min). Linear VMax of BCG predicts the rates of left ventricular (LV) twisting and untwisting (both p < 0.0001). The linear PMax of both SCG and BCG and the linear iK of BCG are the best predictors of the LV ejection fraction (LVEF) (p < 0.0001). This result is further confirmed by mathematical models combining the metrics from SCG and BCG signals with heart rate, in which both linear PMax and iK strongly correlate with LVEF (R = 0.7, p < 0.0001). In this setting of enhanced inotropism, the linear VMax of BCG, rather than the VMax of SCG, is the metric which best explains the LV twist mechanics, in particular the rates of twisting and untwisting. PMax and iK metrics are strongly associated with the LVEF and account for 50% of the variance of the LVEF.

Neural Network-based Classification of Static Lung Volume States using Vibrational Cardiography

Non-invasive health monitoring has the potential to improve the delivery and efficiency of medical treatment.

OBJECTIVE

This study was aimed at developing a neural network to classify the lung volume state of a subject (i.e. high lung volume (HLV) or low lung volume (LLV), where the subject had fully inhaled or exhaled, respectively) by analyzing cardiac cycles extracted from vibrational cardiography (VCG) signals.

METHODS

A total of 15619 cardiac cycles were recorded from 50 subjects, of which 9989 cycles were recorded in the HLV state and the remaining 5630 cycles were recorded in the LLV state. A 1D convolutional neural network (CNN) was employed to classify the lung volume state of these cardiac cycles.

RESULTS

The CNN model was evaluated using a train/test split of 80/20 on the data. The developed model was able to correctly classify the lung volume state of 99.4% of the testing data.

CONCLUSION

VCG cardiac cycles can be classified based on lung volume state using a CNN.

SIGNIFICANCE

These results provide evidence of a correlation between VCG and respiration volume, which could inform further analysis into VCG-based cardio-respiratory monitoring.

Identification of the Vibrations Corresponding with Heart Sounds using Vibrational Cardiography

Cardiography enables diagnostic and preventive care in hospitals and outpatient scenarios. However, most heart monitors do not distinguish the phases of the cardiac cycle. The transition between phases is indicated by the primary heart sounds.

OBJECTIVE

Automatically identify the vibrations corresponding to both heart sounds.

METHODS

Cardiac activity was monitored for 15 subjects while at rest, during exertion, and while performing static breath holds. The subjects consisted of 6 males and 9 females between the ages of 18-39 years with no known cardiorespiratory ailments. Motion corresponding to the heart sounds was identified using vibrational cardiography (VCG). The waveforms were processed to obtain quantities associated with their linear jerk and rotational kinetic energy.

RESULTS

The ability to identity the first vibration was evaluated using the heart rate as a figure of merit. Its correlation with electrocardiography (ECG) measurements produced a r² coefficient of 0.9887. The second vibration was compared with impedance cardiography (ICG) based on its delay from the ECG R-peak, and the fraction of the beat duration occupied by left ventricular ejection time. The comparisons produced r² values of 0.251 and 0.2797, respectively.

CONCLUSION

The vibrations corresponding to both primary heart sounds have the potential to be analyzed using VCG.

SIGNIFICANCE

This study provides evidence of the feasibility of using VCG in identifying mechanical cardiovascular function. It facilitates non-invasive cardiac health monitoring in daily life.

Influence of sympathetic activation on myocardial contractility measured with ballistocardiography and seismocardiography during sustained end-expiratory apnea

Ballistocardiography (BCG) and seismocardiography (SCG) assess vibrations produced by cardiac contraction and blood flow, respectively, through micro-accelerometers and micro-gyroscopes. BCG and SCG kinetic energies (KE) and their temporal integrals (iK) during a single heartbeat are computed in linear and rotational dimensions. Our aim was to test the hypothesis that iK from BCG and SCG are related to sympathetic activation during maximal voluntary end-expiratory apnea. Multiunit muscle sympathetic nerve traffic [burst frequency (BF), total muscular sympathetic nerve activity (tMSNA)] was measured by microneurography during normal breathing and apnea (n = 28, healthy men). iK of BCG and SCG were simultaneously recorded in the linear and rotational dimension, along with oxygen saturation ([Formula: see text]) and systolic blood pressure (SBP). The mean duration of apneas was 25.4 ± 9.4 s. SBP, BF, and tMSNA increased during the apnea compared with baseline (P = 0.01, P = 0.002,and P = 0.001, respectively), whereas [Formula: see text] decreased (P = 0.02). At the end of the apnea compared with normal breathing, changes in iK computed from BCG were related to changes of tMSNA and BF only in the linear dimension (r = 0.85, P < 0.0001; and r = 0.72, P = 0.002, respectively), whereas changes in linear iK of SCG were related only to changes of tMSNA (r = 0.62, P = 0.01). We conclude that maximal end expiratory apnea increases cardiac kinetic energy computed from BCG and SCG, along with sympathetic activity. The novelty of the present investigation is that linear iK of BCG is directly and more strongly related to the rise in sympathetic activity than the SCG, mainly at the end of a sustained apnea, likely because the BCG is more affected by the sympathetic and hemodynamic effects of breathing cessation. BCG and SCG may prove useful to assess sympathetic nerve changes in patients with sleep disturbances.NEW & NOTEWORTHY Ballistocardiography (BCG) and seismocardiography (SCG) assess vibrations produced by cardiac contraction and blood flow, respectively, through micro-accelerometers and micro-gyroscopes. Kinetic energies (KE) and their temporal integrals (iK) during a single heartbeat are computed from the BCG and SCG waveforms in a linear and a rotational dimension. When compared with normal breathing, during an end-expiratory voluntary apnea, iK increased and was positively related to sympathetic nerve traffic rise assessed by microneurography. Further studies are needed to determine whether BCG and SCG can probe sympathetic nerve changes in patients with sleep disturbances.

Ballistocardiography and seismocardiography detection of hemodynamic changes during simulated obstructive apnea

OBJECTIVE

To investigate if modern seismocardiography (SCG) and ballistocardiography (BCG) are useful in the detection of hemodynamic changes occurring during simulated obstructive apneic events.

METHODS

Forty-seven healthy volunteers performed a voluntary maximum Mueller maneuver (MM) for 10 s, and SCG and BCG signals were simultaneously taken. The kinetic energy of a set of cardiac cycles before and during the apneic episode was automatically computed from the rotational and linear channels of the SCG and BCG waveforms and its temporal integral (i K) was derived (unit of measure: microjoules per second (µJ·s)). The estimated transmural pressure (eP _TM ) was assessed as the difference between systemic blood pressure and maximal inspiratory pressure (MIP). The Wilcoxon sign-rank test was used to evaluate differences in energy measurements between normal respiration and the loaded inspiration maneuver. Cardiac kinetic energies and the MIP produced during the MM were compared by linear regression analysis following log transformation in order to assess the correlation between variables.

MAIN RESULTS

The [Formula: see text] during normal breathing increased from 1.1(0.8; 1.4) to 1.9(1.4; 4.3) µJ·s during MM (p < 0.001). Meanwhile, [Formula: see text] increased from 54 (31; 92) to 84 (44; 153) µJ·s, (p < 0.001). The [Formula: see text] and [Formula: see text] of a set of cardiac cycles during the MM were negatively associated with the MIP (r: -0.59, p < 0.001 and r: -0.53, p = 0.001 for [Formula: see text] and [Formula: see text], respectively). When eP _TM was considered, this association became positive (r: +0.58, p < 0.001 and r:+0.60, p < 0.001, for [Formula: see text] and [Formula: see text], respectively). When the i K _LIN was considered as the comparative factor, correlations with the MIP and eP _TM were weak and insignificant. Men had higher values of i K than women.

SIGNIFICANCE

Simulated obstructive apnea elicits large rotational i K swings, which are related to the intensity of the inspiratory effort and, as such, to the intensity of the left ventricular afterload. Computation of cardiac kinetic energy through BCG and SCG may shed further light on the impact of obstructive respiratory events on the cardiovascular system.

Gyrocardiography: A New Non-invasive Monitoring Method for the Assessment of Cardiac Mechanics and the Estimation of Hemodynamic Variables

Gyrocardiography (GCG) is a new non-invasive technique for assessing heart motions by using a sensor of angular motion – gyroscope – attached to the skin of the chest. In this study, we conducted simultaneous recordings of electrocardiography (ECG), GCG, and echocardiography in a group of subjects consisting of nine healthy volunteer men. Annotation of underlying fiducial points in GCG is presented and compared to opening and closing points of heart valves measured by a pulse wave Doppler. Comparison between GCG and synchronized tissue Doppler imaging (TDI) data shows that the GCG signal is also capable of providing temporal information on the systolic and early diastolic peak velocities of the myocardium. Furthermore, time intervals from the ECG Q-wave to the maximum of the integrated GCG (angular displacement) signal and maximal myocardial strain curves obtained by 3D speckle tracking are correlated. We see GCG as a promising mechanical cardiac monitoring tool that enables quantification of beat-by-beat dynamics of systolic time intervals (STI) related to hemodynamic variables and myocardial contractility.