Key result
A method based on differences from both moving mean and from the last normal value performs well for artifact and arrhythmia detection in heart rate variability analysis.
A method based on differences from both moving mean and the last normal value is effective for artifact and arrhythmia removal in heart rate variability analysis during acute myocardial infarction.
Supports reliable HRV analysis in AMI; extends validation of the dual-difference method in randomized acute settings.
Analysis of heart rate variability with Holter monitoring during the acute phase of myocardial infarction is often difficult due to excessive artifacts and arrhythmias. Detection of noisy epochs of data or arrhythmias and their substitution by interpolation has enabled further analysis on epochs which otherwise would have been discarded. The present paper discusses various strategies for artifact and arrhythmia detection. Although none of the methods solved all varieties of artifacts, a method based on differences from both moving mean and from the last normal value performs well in the majority of cases.
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Sapoznikov et al. (2005) conducted a review in Myocardial infarction (acute phase). Method based on differences from moving mean and last normal value was evaluated on Artifact and arrhythmia detection. A method based on differences from both moving mean and from the last normal value performs well for artifact and arrhythmia detection in heart rate variability analysis.
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