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This program reads a single ECG signal, attempts to detect QRS complexes, and records their locations in an annotation file. The detector algorithm is based on a Pascal program written by W.A.H. Engelse and C. Zeelenberg, “A single scan algorithm for QRS-detection and feature extraction”, Computers in Cardiology 6:37-42 (1979).
1 #include <stdio.h>
2 #include <wfdb/wfdb.h>
3 #include <wfdb/ecgcodes.h>
4
5 #define abs(A) ((A) >= 0 ? (A) : -(A))
6
7 main(argc, argv)
8 int argc;
9 char *argv[];
10 {
11 int filter, time=0, slopecrit, sign, maxslope=0, nsig, nslope=0,
12 qtime, maxtime, t0, t1, t2, t3, t4, t5, t6, t7, t8, t9,
13 ms160, ms200, s2, scmax, scmin = 0;
14 WFDB_Anninfo a;
15 WFDB_Annotation annot;
16 WFDB_Sample *v;
17 WFDB_Siginfo *s;
18
19 if (argc < 2) {
20 fprintf(stderr, "usage: %s record [threshold]\n", argv[0]);
21 exit(1);
22 }
23 a.name = "qrs"; a.stat = WFDB_WRITE;
24 if ((nsig = isigopen(argv[1], NULL, 0)) < 1) exit(2);
25 s = (WFDB_Siginfo *)malloc(nsig * sizeof(WFDB_Siginfo));
26 v = (WFDB_Sample *)malloc(nsig * sizeof(WFDB_Sample));
27 if (s == NULL || v == NULL) {
28 fprintf(stderr, "%s: insufficient memory\n", argv[0]);
29 exit(2);
30 }
31 if (isigopen(argv[1], s, nsig) != nsig) exit(2);
32 if (sampfreq((char *)NULL) < 240. ||
33 sampfreq((char *)NULL) > 260.)
34 setifreq(250.);
35 if (annopen(argv[1], &a, 1) < 0) exit(2);
36 if (argc > 2) scmin = muvadu(0, atoi(argv[2]));
37 if (scmin < 1) scmin = muvadu(0, 1000);
38 slopecrit = scmax = 10 * scmin;
39 ms160 = strtim("0.16"); ms200 = strtim("0.2"); s2 = strtim("2");
40 annot.subtyp = annot.chan = annot.num = 0; annot.aux = NULL;
41 (void)getvec(v);
42 t9 = t8 = t7 = t6 = t5 = t4 = t3 = t2 = t1 = v[0];
43
44 do {
45 filter = (t0 = v[0]) + 4*t1 + 6*t2 + 4*t3 + t4
46 - t5 - 4*t6 - 6*t7 - 4*t8 - t9;
47 if (time % s2 == 0) {
48 if (nslope == 0) {
49 slopecrit -= slopecrit >> 4;
50 if (slopecrit < scmin) slopecrit = scmin;
51 }
52 else if (nslope >= 5) {
53 slopecrit += slopecrit >> 4;
54 if (slopecrit > scmax) slopecrit = scmax;
55 }
56 }
57 if (nslope == 0 && abs(filter) > slopecrit) {
58 nslope = 1; maxtime = ms160;
59 sign = (filter > 0) ? 1 : -1;
60 qtime = time;
61 }
62 if (nslope != 0) {
63 if (filter * sign < -slopecrit) {
64 sign = -sign;
65 maxtime = (++nslope > 4) ? ms200 : ms160;
66 }
67 else if (filter * sign > slopecrit &&
68 abs(filter) > maxslope)
69 maxslope = abs(filter);
70 if (maxtime-- < 0) {
71 if (2 <= nslope && nslope <= 4) {
72 slopecrit += ((maxslope>>2) - slopecrit) >> 3;
73 if (slopecrit < scmin) slopecrit = scmin;
74 else if (slopecrit > scmax) slopecrit = scmax;
75 annot.time = strtim("i") - (time - qtime) - 4;
76 annot.anntyp = NORMAL; (void)putann(0, &annot);
77 time = 0;
78 }
79 else if (nslope >= 5) {
80 annot.time = strtim("i") - (time - qtime) - 4;
81 annot.anntyp = ARFCT; (void)putann(0, &annot);
82 }
83 nslope = 0;
84 }
85 }
86 t9 = t8; t8 = t7; t7 = t6; t6 = t5; t5 = t4;
87 t4 = t3; t3 = t2; t2 = t1; t1 = t0; time++;
88 } while (getvec(v) > 0);
89
90 wfdbquit();
91 exit(0);
92 }
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(See http://physionet.org/physiotools/wfdb/examples/example10.c for a copy of this program.)
Notes:
A macro that evaluates to the absolute value of its argument.
The names of these variables match those in the original Pascal program.
Most of this program is independent of sampling frequency, but the filter
(lines 45–46) and the threshold are as specified by the authors
of the original program for human ECGs sampled at 250 Hz (e.g., the AHA DB).
If the sampling frequency of the input record is significantly
different, we use setifreq to specify that we want getvec
to give us data resampled at 250 Hz. The output annotation file is
created in line 35 only after invoking setifreq if necessary.
The threshold is actually a slope criterion (with units of amplitude/time);
these lines normalize the threshold with respect to the signal gain.
The default value is used unless the user supplies an acceptable
alternative. The variables scmin and scmax are lower and
upper bounds for the adaptive threshold slopecrit.
Here we read the first sample and copy it into the variables that will be used to store the ten most recent samples.
This FIR filter differentiates and low-pass filters the input signal.
Here we adjust the threshold if more than two seconds have elapsed since
a QRS was detected. In line 49, slopecrit is set to 15/16 of its
previous value if no slopes have been found; in line 53, it is set to
17/16 of its previous value if 5 or more slopes were found (suggesting
the presence of noise).
If the condition in line 48 is satisfied, we may have found the beginning
of a QRS complex. We record that a slope has been found, set the timer
maxtime to 160 msec, and save the sign of the slope and the current
time relative to the previous beat.
This code is executed once we have found a slope. Each time the filter
output crosses the threshold, we record another slope and begin looking
for a threshold crossing of the opposite sign (lines 63–66), which must
occur within a specified time. We record the maximum absolute value of
the filter in maxslope (lines 67–69) for eventual use in updating
the threshold (lines 72–74). Once a sufficient interval has elapsed
following the last threshold crossing (line 70), if there were between
2 and 4 slopes, we have (apparently) found a QRS complex, and the program
records a NORMAL annotation (lines 75–76). If there were 5 or more
slopes, the program records an artifact annotation (lines 80–81). If
only 1 slope was found, it is assumed to represent a baseline shift and
no output is produced.
At the end of the loop, the samples are shifted through the tn
variables and another sample is read.
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