Introduction: An analysis of ultra-high-frequencies in ECG (UHF ECG, up to 2 kHz) reveals new information about the time spatial distribution of heart depolarization. Such an analysis may be important for diagnosing and treating patients with atrial and ventricular dyssynchrony. The UHF analysis in patients with a pacing device is complicated due to the pacing influence in the ECG. In that case, all pacing artefacts must be eliminated from the measured signal. The first step in removing those artefacts is to precisely detect their temporal position. Although pacing artefacts are usually clearly visible on a measured ECG, capturing the whole pacing artefact may be challenging. Methods: This paper compares different detection approaches and evaluates them on 19 records. Derivatives, a moving statistical window and complex envelope methods were tested followed by descriptive statistics approaches for making a peak detection. We evaluated the variability of the detection position by the distance variability from manual anotations. For each method, sensitivity and positive predictivity were evaluated. Results: The method with the most precise temporal detection was the variance moving window with a standard deviation (SD) of ±0.11 ms mark placement. The best detection method was a SD moving window with sensitivity=100 and specificity=82.3 and was evaluated as the most appropriate.
[1]
John Redmond.
Detecting and distinguishing cardiac-pacing artifacts
,
2012
.
[2]
Aarón Cuevas López,et al.
SignalPlant : an open signal processing software platform
,
2022
.
[3]
I Jekov,et al.
ECG Database Applicable for Developmentand and Testing of Pace Detection Algorithms
,
2014
.
[4]
S. Luo,et al.
Performance study of digital pacer spike detection as sampling rate changes
,
2008,
2008 Computers in Cardiology.
[5]
Pavel Jurák,et al.
An additional marker of ventricular dyssynchrony
,
2015,
2015 Computing in Cardiology Conference (CinC).
[6]
Pavel Jurák,et al.
Cardiac resynchronization efficiency estimation by new ultra-high-frequency ECG dyssynchrony descriptor
,
2015,
2015 Computing in Cardiology Conference (CinC).