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Cardiac time intervals are important hemodynamic indices and provide information about left ventricular performance. Phonocardiography (PCG), impedance cardiography (ICG), and recently, seismocardiography (SCG) have been unobtrusive methods of choice for detection of cardiac time intervals and have potentials to be integrated into wearable devices. The main purpose of this study was to investigate the accuracy and precision of beat-to-beat extraction of cardiac timings from the PCG, ICG and SCG recordings in comparison to multimodal echocardiography (Doppler, TDI, and M-mode) as the gold clinical standard. Recordings were obtained from 86 healthy adults and in total 2,120 cardiac cycles were analyzed. For estimation of the pre-ejection period (PEP), 43% of ICG annotations fell in the corresponding echocardiography ranges while this was 86% for SCG. For estimation of the total systolic time (TST), these numbers were 43, 80, and 90% for ICG, PCG, and SCG, respectively. In summary, SCG and PCG signals provided an acceptable accuracy and precision in estimating cardiac timings, as compared to ICG.

Seismocardiogram (SCG) is the low-frequency vibrations signal recorded from the chest using accelerometers. Peaks on dorsoventral and sternal SCG correspond to specific cardiac events. Prior research work has shown the potential of extracting such peaks for various types of monitoring and diagnosis applications. However, annotation of these peaks is not a trivial task and complicated in some subjects. In this paper, an automated method is proposed to annotate these peaks. The high-frequency accelerations obtained from the same accelerometer, used to record SCG with, were used to facilitate the annotation of the SCG. Algorithms were developed for detection of isovolumic moment (IM) and aortic valve closure (AC) points of SCG. Four different envelope calculation methods were used: cardiac sound characteristic waveform (CSCW), Shannon, absolute, and Hilbert. The algorithms were evaluated based on a dataset including 18 subjects undergoing lower body negative pressure and were further tested with another dataset, which included 67 subjects. These datasets had been previously manually annotated. The algorithm based on CSCW envelope calculation produced the highest detection accuracy for both IM and AC. The overall CSCW algorithm detection accuracy for the test dataset was 98.7% and 99.1% for the IM and AC points, respectively.

A methodology, based on principal component analysis, is proposed to quantify beat to beat Seismocardiogram changes. The proposed method was tested over a population of 94 subjects including 35 ischemic heart disease patients. The results showed that there was an insignificant overlap between the diseased and the healthy populations in the number of principal components (NPC) and that further development of this method might yield a classification index for myocardial abnormalities. In addition such an index has potential utility in patient monitoring.

This paper presents an overview of seismocardiography (SCG) as a noninvasive cardiology method. The paper represents a brief historical background to the SCG, an assessment of the technology at present, and an evaluation of the challenges we must address. These challenges include the development and clarification of definitions, standards, and annotations.

Seismocardiography, a new noninvasive technique, detects low-frequency cardiac vibrations on the chest wall during ventricular contraction and during both early and late ventricular filling. To evaluate the ability of seismocardiography to detect ischemia caused by decreased coronary blood flow, 35 patients were studied during coronary angioplasty. Seismocardiograms and electrocardiograms were recorded twice at baseline, with the catheter across the lesion before first inflation (n = 15), every 30 seconds during the first inflation, 1 and 2 minutes after the first inflation and greater than or equal to 5 minutes after the final inflation. For comparison, sequential seismocardiograms were also obtained from 15 healthy volunteers. Electrocardiograms were blindly scored for ST change from baseline (0 = none, 1 = 0.5 mm ST depression, 2 = greater than or equal to 1.0 mm ST depression, 3 = ST elevation). Seismocardiograms were blindly scored for change from baseline (0 = none, 1 = mild, 2 = moderate, 3 = marked) for both the systolic and diastolic waves. The average maximal systolic seismocardiographic score was 2.5 +/- 0.8 for patients who had undergone angioplasty and 1.0 +/- 0.9 for volunteers (p less than 0.001). The average maximal diastolic seismocardiographic score was 2.3 +/- 0.8 for angioplasty patients and 0.7 +/- 0.9 for volunteers (p less than 0.001). The percentage of angioplasty patients with electrocardiographic, systolic and diastolic seismocardiographic scores greater than or equal to 2 was, respectively: 0, 11 and 14% at second baseline; 23, 67 and 53% with catheter across the lesion; 44, 75 and 59% after 30 seconds of inflation; 42, 71 and 61% after 60 seconds of inflation; 23, 74 and 61% after 1 minute of deflation; and 0, 71 and 47% 5 minutes after final inflation.(ABSTRACT TRUNCATED AT 250 WORDS)