R package to detect premature ventricular complexes (PVCs) in data from a Polar H10 chest-strap heart rate sensor.
We have used the ECGLogger app on an iPhone to extract the Polar H10 data as a CSV file (or really a series of CSV files, in one hour blocks), and the rsleep package to detect "R" peaks in the ECG signal.
You can install the detectPVC package from GitHub.
You first need to install the remotes package.
install.packages("remotes")
Then use remotes::install_github():
library(remotes)
install_github("kbroman/detectPVC")
The library comes with a 10-min sample data set, polar_h10.
library(detectPVC)
data(polar_h10)
Convert the included times (which are time stamps from a Polar H10, in 1e-9 seconds) to a standard date-time values.
polar_h10$datetime <- convert_timestamp(polar_h10$time)
First detect bad segments in the data, with either wild values or missing data points.
bad_segs <- find_bad_segments(polar_h10$time, polar_h10$ecg)
For this example, there is just one bad segment, covering about 7 sec.
You can get the total covered length in seconds with tot_length().
totlength(bad_segs, polar_h10$time)
Use detect_peaks() to detect "R" peaks in the ECG trace.
peaks <- detect_peaks(polar_h10$ecg, omit_segments=bad_segs)
Plot the first 20 seconds of data, and add points above the peaks. The function
plot_ecg() is a base-graphics-based plotting function with light
gray grid lines.
v <- 1:(130*20)
plot_ecg(polar_h10$datetime[v], polar_h10$ecg[v])
points(polar_h10$datetime[peaks], polar_h10$ecg[peaks], pch=16, col="slateblue")
Use calc_peak_stats() to calculate some statistics about each peak.
peak_stats <- calc_peak_stats(polar_h10$time, polar_h10$ecg, peaks)
The simplest rule for classifying PVCs is to take RStime > 50.
The statistic RStime is the time between the R and S peaks in milliseconds.
pvc <- (peak_stats$RStime > 50)
Label the inferred PVCs with pink dots, and the others with green dots.
plot_ecg(polar_h10$datetime[v], polar_h10$ecg[v])
points(polar_h10$datetime[peaks], polar_h10$ecg[peaks], pch=16, col=c("green3", "violetred")[pvc+1])
In this 20 second window, there are 10 PVCs in 29 total beats.
detectPVC is released under the MIT license.