Seismocardiography-Based Detection of Cardiac Quiescence.

Cardiac-computed tomography angiography (CTA) is a minimally invasive imaging technology for characterizing coronary arteries. A fundamental limitation of CTA imaging is cardiac movement, which can cause artifacts and reduce the quality of the obtained images. To mitigate this problem, current approaches involve gating the image based on the electrocardiogram (ECG) to predict the timing of quiescent periods of the cardiac cycle.

Characterization of cardiac quiescence from retrospective cardiac computed tomography using a correlation-based phase-to-phase deviation measure.

Purpose: Accurate knowledge of cardiac quiescence is crucial to the performance of many cardiac imaging modalities, including computed tomography coronary angiography (CTCA). To accurately quantify quiescence, a method for detecting the quiescent periods of the heart from retrospective cardiac computed tomography (CT) using a correlation-based, phase-to-phase deviation measure was developed.

Methods: Retrospective cardiac CT data were obtained from 20 patients (11 male, 9 female, 33-74 yr) and the left main, left anterior descending, left circumflex, right coronary artery (RCA), and interventricular septum (IVS) were segmented for each phase using a semiautomated technique.

Seismocardiography-based detection of cardiac quiescence for cardiac computed tomography angiography.

As a measure of chest wall acceleration caused by cardiac motion, the seismocardiogram (SCG) has the potential to supplement the electrocardiogram (ECG) to more accurately trigger cardiac computed tomography angiography (CTA) data acquisition during periods of cardiac quiescence. The SCG was used to identify the systolic and diastolic quiescent periods of the cardiac cycle on a beat-by-beat basis and from composite velocity signals for nine healthy subjects. The cardiac velocity transmitted to the chest wall was calculated using a Kalman filter.

Detection of quiescent cardiac phases in echocardiography data using nonlinear filtering and boundary detection techniques.

We describe an algorithm to detect cardiac quiescence within a heartbeat using nonlinear filtering and boundary detection techniques in echocardiography images. The motivation for detection of these quiescent phases is to provide improved cardiac gating to obtain motion-artifact-free images of the heart at cardiac computed tomography (CT). Currently, cardiac gating is provided through electrocardiography (ECG), which does not provide information about the instantaneous mechanical state of the heart.

An active contour based method for analyzing cardiac quiescence from echocardiography.

A semi-automated method for analyzing cardiac quiescence of anatomical cardiac features from two-dimensional echocardiographic cine data is presented. The method utilizes both active contour and optical flow techniques for feature identification and tracking. A curvature-based potential surface was used in the active contour calculations to attract the contour to regions of inflection on the image surface rather than the standard gradient-based surface that attracts the contour to strong edges.

Detection of Cardiac Quiescence from B-Mode Echocardiography Using a Correlation-Based Frame-to-Frame Deviation Measure.

Two novel methods for detecting cardiac quiescent phases from B-mode echocardiography using a correlation-based frame-to-frame deviation measure were developed. Accurate knowledge of cardiac quiescence is crucial to the performance of many imaging modalities, including computed tomography coronary angiography (CTCA). Synchronous electrocardiography (ECG) and echocardiography data were obtained from 10 healthy human subjects (four male, six female, 23-45 years) and the interventricular septum (IVS) was observed using the apical four-chamber echocardiographic view.

Novel Tool for Complete Digitization of Paper Electrocardiography Data.

Objective: We present a Matlab-based tool to convert electrocardiography (ECG) information from paper charts into digital ECG signals. The tool can be used for long-term retrospective studies of cardiac patients to study the evolving features with prognostic value.

Methods And Procedures: To perform the conversion, we: 1) detect the graphical grid on ECG charts using grayscale thresholding; 2) digitize the ECG signal based on its contour using a column-wise pixel scan; and 3) use template-based optical character recognition to extract patient demographic information from the paper ECG in order to interface the data with the patients' medical record.

A system for seismocardiography-based identification of quiescent heart phases: implications for cardiac imaging.

Seismocardiography (SCG), a representation of mechanical heart motion, may more accurately determine periods of cardiac quiescence within a cardiac cycle than the electrically derived electrocardiogram (EKG) and, thus, may have implications for gating in cardiac computed tomography. We designed and implemented a system to synchronously acquire echocardiography, EKG, and SCG data. The device was used to study the variability between EKG and SCG and characterize the relationship between the mechanical and electrical activity of the heart.

A trimodal system for the acquisition of synchronous echocardiography, electrocardiography, and seismocardiography data.

A novel system was developed to acquire synchronous echocardiography, electrocardiography (EKG), and seismocardiography (SCG) data. The system was developed to facilitate the study of the relationship between the mechanical and electrical characteristics of the heart. The system has both a hardware and software component.

Spectrum analysis of seismic surface waves and its applications in seismic landmine detection.

In geophysics, spectrum analysis of surface waves (SASW) refers to a noninvasive method for soil characterization. However, the term spectrum analysis can be used in a wider sense to mean a method for determining and identifying various modes of seismic surface waves and their properties such as velocity, polarization, etc. Surface waves travel along the free boundary of a medium and can be easily detected with a transducer placed on the free surface of the boundary.