Instantaneous respiratory rate estimation from multilead ECG delineation using VCG directions on fiducial points

The main purpose of this work is the estimation of the respiratory rate (¿rR) from the electrocardiogram (ECG). In this study, the tr was estimated from the same Fit directions of maximum projection (FD) used for multi lead ECG automatic delineation (ML). A previously developed and validated methodology for boundaries location was extended to include wave peaks and estimate FD. The median of power spectral density obtained over the directions based on QRS complex main peak, T wave peak and end spatial loops was used for tr estimation. In a control database, the proposed method yielded more accurate tr estimates (mean absolute error (MAE), 2.64 bpm, SD=3.92)than the estimates based on the single-lead ECG R-peak amplitude (MAE values from 3.29 to 5.26 bpm, SD > 5) and RR series (2.89 to 3.66 bpm, SD >4.6), close to results from EDR method (2.89 bpm, SD=3.63)

Respiratory rate estimation from multilead directions, based on ECG delineation

International audienceEstimating the instantaneous respiratory rate (Rr) from the electrocardiogram (ECG) is of interest as respiration direct measurement in clinical situations is often cumbersome. In this study, the Rr was estimated from the same Final Directions of maximum projection (FD) used for multi lead ECG automatic delineation. Power spectral analysis over the directions based on QRS complex main peak and T wave onset, peak and end spatial loops was used for Rr estimation. On a subset of the Physionet MGH/MF dataset, the proposed method yielded more accurate Rr estimates (minimum mean absolute error (MAE), 2.82 bpm) than the frequency tracking algorithm (minimum MAE, 4.53 bpm) and Fourier-based frequency estimation (minimum MAE, 4.94 bpm) using each lead alone, outperforming also the weighted multi-signal oscillator-based algorithm estimates for two or three lead (minimum MAE, 3.04 bpm). It was also shown that the FD of the three orthogonalized leads from Principal Component algorithm, improve the performance of Rr estimation. © 2016 IEEE