The fully automated algorithm was perfectly 100% accurate in detection of a pacing artifact’s presence, and demonstrated 75% sensitivity and 100% specificity for the per-digital-sample automated detection of pacing artifacts, whereas a user-friendly interface allowed additional fine-tuning and quality control of the artifact removal.Ĭurrent ECG machines convert the analog ECG signal to digital at the front end. In this work, we developed and validated the semi-automated algorithm to detect and remove pacing artifacts from a digital ECG signal. The kappa-statistic was 0.785, indicating substantial agreement. The amount of agreement indicated that we could reject the null hypothesis that they were making their determination randomly ( P<0.00001). If the automated algorithm had made the determination randomly (but with probabilities equal to the overall proportions), we would expect the agreement on 94.43% of digital samples. Two-by-two table ( Table 2) reports an agreement between the ground truth and automated detection of pacing artifacts for each sample of the digital ECG data. Notably, the automated algorithm detected the presence of pacing artifact with 100% accuracy, 100% sensitivity, and 100% specificity. On average, a pacing artifact occupied 9.2☓.2 samples or 18.4☖.4 ms. We tested the hypothesis that the newly developed semi-automated algorithm can accurately detect and remove pacing artifacts from a vectorcardiogram (VCG) obtained from 12-lead ECG.įrom the validation dataset (n= 22 ECGs) the mean of 4 constraining parameter values were found as : mean maximum amplitude 146.36☗6.36 μV, mean onset threshold (α on) 13.06☖.21 μV/ms, mean offset threshold (α off) 34.77☑7.80 μV/ms, and mean maximum window size 27.23 ± 3.53 ms.įor validation of the automated algorithm, we analyzed 110,000 digital signal samples. This paper presents the development and validation of a novel semi-automated algorithm to detect and remove pacing artifacts. No such algorithm has been previously developed that can both detect and remove a pacing spike artifact from the 12-lead and orthogonal XYZ ECG. The first step in the automated analysis of paced ECG is the removal of pacing artifacts. Thus, paced ECG carries important data for meaningful analysis, which needs to be further studied. Measurement of SVG on paced ECG furnished clinically useful information. Spatial ventricular gradient (SVG) is independent of the activation sequence. Cardiac memory is neither pure primary nor pure secondary repolarization abnormality. Nevertheless, we, and others, showed that cardiac memory could be detected during continued altered activation. Therefore, the consensus is that paced ECG could only be used to diagnose paced rhythm, but, otherwise, it cannot be clinically useful. The rule stemmed from the dogma about secondary repolarization abnormalities, stating that paced ventricular complexes are examples of secondary repolarization abnormalities. Notably, the ECG diagnostic standards enforced the rule that no secondary statements can accompany the primary diagnostic statement of paced rhythm or paced complexes. Atrial-paced and ventricular-paced rhythm and atrioventricular (AV) dual-paced rhythm are included in the list of core primary ECG diagnostic statements, endorsed by the American Heart Association (AHA), the American College of Cardiology (ACC), the Heart Rhythm Society (HRS), and the International Society for Computerized Electrocardiography (ISCE). The number of patients living with an implanted cardiac pacemaker is steadily growing.Īn electrocardiogram (ECG) is widely used to determine the heart rhythm and to evaluate the performance of pacemaker functioning, especially in emergency settings. In 2014, an estimated 351,000 pacemaker inpatient procedures were performed in the US. Pacemaker implantation rates increased from 467 per million in 1993 to 616 per million in 2009.

Innovations in cardiac pacing expanded indications for implantable devices capable of delivering cardiac pacing.

Since the 1950s, cardiac pacing became a vital treatment modality for a growing number of cardiovascular patients.

Pacemaker av sequential ekg