Autocorrelated Differential Algorithm for Real-Time Seismocardiography Analysis

Abstract

We present a novel seismocardiography (SCG)based approach for real-time cardio-respiratory activity measurement called the Autocorrelated Differential Algorithm (ADA). Measurements were performed on ten male subjects in the supine position for three 7-minute-long sets each, corresponding to 14,619 heartbeats. The ADA utilized temporal variations, windowing, and autocorrelation to produce physiological measurements corresponding to heart rate (HR), and left ventricular ejection time, and estimations of respiration rate, volume, and phase. The versatility of the ADA was investigated in two contexts: physical exertion and heart rate variability. The accuracy of HR measurements at a sampling frequency of 200 Hz resulted in a correlation coefficient (r 2) of 0.9808 when compared with a manual annotation of all datasets. Its reproducibility was tested on externally obtained SCG and electrocardiography datasets, which produced an r 2 of 0.8224. The accuracy and computational time were also characterized by different sampling frequencies to quantify performance. The recommended sampling frequency is 200 Hz corresponding to a computation time of 0.05 s per instantaneous measurement using a standard desktop computer. The ADA delivered real-time SCG measurements with a refresh rate that was dependent on the computational time per measurement, which could be decreased by lowering the sampling frequency. The presented algorithm offers a novel tool toward real-time physiological monitoring in clinical and everyday scenarios.

Real-Time Cardiac Beat Detection and Heart Rate Monitoring from Combined Seismocardiography and Gyrocardiography

“…The trade-off can be seen in Figure 8 for sampling frequencies of 50 Hz, 100 Hz, 150 Hz, 200 Hz, and 250 Hz. Interestingly, the compromise in accuracy for VCG resulted in a r 2 value of 0.9456 at 50 Hz, which marked a significant improvement over SCG alone [33]. A maximum computational fraction of 0.088 s per second of data was observed at a sampling frequency of 250 Hz when using a standard desktop computer with no external programs activated.…”

“…The monitor delivered measurements of averaged and instantaneous heart rate for such subjects at rest and under physical exertion. Cardiac mechanical activity was measured by an upgraded version of the ADA [33] that processed cardiac-induced sternal vibrations as VCG signals. The measurements were referenced with ECG that measured the electrical activity of the heart using the standard Pan Tompkins [57] algorithm for the ECG signal analysis.…”

“…The autocorrelated differential algorithm (ADA) developed in [33] was built to process a three-axis acceleration signal for cardio-respiratory measurement. In this work, the algorithm was extended to incorporate three additional degrees of freedom (DOF) corresponding to the angular rotation of the sensor.…”

“…The previously developed ADA algorithm [33] was extended to analyze GCG signals and thereby the entire VCG parameter space. Its accuracy was further validated by applying the measured HR to inform AO peak identification.…”

“…GCG offers the potential for novel insights into cardiac fiducial points [22,28], higher fidelity for certain types of motion artifact [29,30,31], and can assist in SCG beat detection using kinetic energy envelopes [30,32]. In this paper, we have modified our previously developed autocorrelated differential algorithm (ADA) [33] to process GCG in parallel with SCG and thereby exploit the content-rich information in VCG signals. The system was also expanded to reference with ECG, thereby demonstrating an affordable tool for electro-mechanical cardiography.…”