Introduction: This study proposes an algorithm for preprocessing VCG records to
obtain a representative QRS loop.
Methods: The proposed algorithm uses the following methods: Digital filtering to
remove noise from the signal, wavelet-based detection of ECG fiducial points and
isoelectric PQ intervals, spatial alignment of QRS loops, QRS time synchronization
using root mean square error minimization and ectopic QRS elimination. The
representative QRS loop is calculated as the average of all QRS loops in the VCG
record. The algorithm is evaluated on 161 VCG records from a database of 58
healthy control subjects, 69 patients with myocardial infarction, and 34 patients
with bundle branch block. The morphologic intra-individual beat-to-beat
variability rate is calculated for each VCG record.
Results and Discussion: The maximum relative deviation is 12.2% for healthy control
subjects, 19.3% for patients with myocardial infarction, and 17.2% for patients with
bundle branch block. The performance of the algorithm is assessed by measuring the
morphologic variability before and after QRS time synchronization and ectopic QRS
elimination. The variability is reduced by a factor of 0.36 for healthy control subjects,
0.38 for patients with myocardial infarction, and 0.41 for patients with bundle branch
block. The proposed algorithm can be used to generate a representative QRS loop for
each VCG record. This representative QRS loop can be used to visualize, compare,
and further process VCG records for automatic VCG record classification.Web of Science14art. no. 126007
