rpeaks_pan_tompkins: Detect R peaks in ecg data using the Pan-Tompkins algorithm

In vankesteren/rpeaks: Fast detection of R peaks in ecg data

Detect R peaks in ecg data using the Pan-Tompkins algorithm

Description

Fast implementation of the Pan-Tompkins algorithm. The default parameters are taken from the original pan and tompkins paper.

Usage

rpeaks_pan_tompkins(
  ecg,
  sample_rate,
  integration_window = 0.15,
  refractory = 0.2,
  band_low = 5,
  band_high = 15
)

Arguments

ecg	raw ecg data vector
sample_rate	sampling rate in Hz of the ecg
integration_window	size of the integration window in seconds
refractory	refractory period in seconds (minimum time between peaks)
band_low	lower bound of the band-pass filter in Hz
band_high	upper bound of the band-pass filter in Hz

Details

This algorithm uses a butterworth filter of order 1 for the band-pass step, and a 3rd-order length-5 Savitzky-Golay smoothing filter to compute the derivative of the band-passed signal. Peak detection on the preprocessed signal works in a simplified way: we take the first value above the lower bound (3 * the mean signal value) which is higher than its neighbours, and not within the refractory period after the previous R peak.

References

Pan, J., & Tompkins, W. J. (1985). A real-time QRS detection algorithm. IEEE transactions on biomedical engineering, (3), 230-236.

Examples

ecg_url <- "https://physionet.org/files/ecgiddb/1.0.0/Person_01/rec_2.dat?download"
ecg_dat <- readBin(ecg_url, integer(), 500*30)
ecg_sec <- (0:(length(ecg_dat) - 1)) / 500 # rel. time in seconds
r_peaks <- rpeaks_pan_tompkins(ecg = ecg_dat, sample_rate = 500)
plot(x = ecg_sec, y = ecg_dat, type = "l", xlab = "time (seconds)", ylab = "ecg")
abline(v = r_peaks, col = "blue", lty = 3)

vankesteren/rpeaks documentation built on March 4, 2024, 1:32 a.m.