Key result
The fiducial segment averaging algorithm provided highly accurate short-term QT variability estimates with median absolute differences mostly less than 0.5 ms, outperforming traditional beat-by-beat analysis.
Population
28,800 simulated standard 12-lead ECGs generated from 200 ECGs from the Common Standards for…
Comparison
Fiducial segment averaging algorithm for fully… vs Conventional beat-by-beat QTV measurement…
Design
Other
Authors
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May support automated QT variability analysis in large ECG datasets; leaves open validation in clinical recordings.
A novel fiducial segment averaging algorithm accurately measures short-term QT variability in simulated ECGs with varying noise levels, enabling automated analysis of large ECG datasets.
Rijnbeek et al. (2017) studied QT interval variability (n=28,800). Fiducial segment averaging (FSA) algorithm vs. Conventional beat-by-beat measurement algorithm (MEANS) was evaluated on Median absolute difference between simulated and estimated short-term QT variability (STV). The fiducial segment averaging algorithm provided highly accurate short-term QT variability estimates with median absolute differences mostly less than 0.5 ms, outperforming traditional beat-by-beat analysis.
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