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Automatic filtering of outliers in RR intervals before analysis of heart rate variability in Holter recordings: a comparison with carefully edited data by Marcus Karlsson; Rolf Hörnsten; Annika Rydberg; Urban Wiklund is a Medicine article available to read on EtoBox.

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## Background Undetected arrhythmic beats seriously affect the power spectrum of the heart rate variability (HRV). Therefore, the series of RR intervals are normally carefully edited before HRV is analysed, but this is a time consuming procedure when 24-hours recordings are analysed. Alternatively, different methods can be used for automatic removal of arrhythmic beats and artefacts. This study compared common frequency domain indices of HRV when determined from manually edited and automatically filtered RR intervals. ## Methods and Results Twenty-four hours Holter recordings were available from 140 healthy subjects of age 1-75 years. An experienced technician carefully edited all recordings. Automatic filtering was performed using a recursive procedure where RR intervals were removed if they differed from the mean of the surrounding RR intervals with more than a predetermined limit (ranging from 10% to 50%). The filtering algorithm was evaluated by replacing 1% of the beats with synthesised ectopic beats. Power spectral analysis was performed before and after filtering of both the original edited data and the noisy data set. The results from the analysis using the noisy data were

Who reads Automatic filtering of outliers in RR intervals before analysis of heart rate variability in Holter recordings: a comparison with carefully edited data?

Author

Marcus Karlsson; Rolf Hörnsten; Annika Rydberg; Urban Wiklund

Publisher

BioMed Central; Springer (Biomed Central Ltd.); London: BioMed Central, 2002-; Springer Science and Business Media LLC (ISSN 1475-925X)

Published

2012

Language

EN

Field

Medicine (Health Sciences)