Next: WRANN(1) Up: WFDB Applications Guide Previous: WFDBWHICH(1) | On This Page |
wqrs attempts to locate QRS complexes in an ECG signal in the specified record. The detector algorithm is based on the length transform. The output of wqrs is an annotation file (with annotator name wqrs) in which all detected beats are labelled normal; the annotation file will also contain optional J-point annotations if the -j option (see below) is used.
wqrs can process records containing any number of signals, but it uses only one signal for QRS detection (signal 0 by default; this can be changed using the -s option, see below). wqrs is optimized for use with adult human ECGs. For other ECGs, it may be necessary to experiment with the sampling frequency as recorded in the input record’s header file (see header(5) ), the detector threshold (which can be set using the -m option), and the time constants indicated in the source file.
wqrs optionally uses the WFDB library’s setifreq function to resample the input signal at 120 or 150 Hz (depending on the mains frequency, which can be specified using the -p option). wqrs performs well using input sampled at a range of rates up to 360 Hz and possibly higher rates, but it has been designed and tested to work best on signals sampled at 120 or 150 Hz.
Options include:
It may be necessary to set and export the shell variable WFDB (see setwfdb(1) ).
To mark QRS complexes
in record 100 beginning 5 minutes from the start, ending 10 minutes and
35 seconds from the start, and using signal 1, use the command:
wqrs -r 100 -f 5:0 -t 10:35 -s 1
The output annotations may be read using (for example):
rdann -a wqrs -r 100
To evaluate the performance of this program, run it on the entire record,
by:
wqrs -r 100
and then compare its output with the reference annotations by:
bxb -r 100 -a atr wqrs
Zong W, Moody GB, and Jiang D. A robust open-source algorithm to detect onset and duration of QRS complexes. Computers in Cardiology 30:737-740 (2003).
Please e-mail your comments and suggestions to webmaster@physionet.org, or post them to:
PhysioNetUpdated 10 June 2022