The Impact of Missing Data on Heart Rate Variability Features: A Comparative Study of Interpolation Methods for Ambulatory Health Monitoring
Résumé
h i g h l i g h t s g r a p h i c a l a b s t r a c t • Real time HRV analysis of R-R time series with missing data. • Higher impact of interpolation on frequency domain features • Better RMSSD estimation without interpolation beyond 50% missing data. • Combination of different interpolation methods according to both missing values' percentage and targeted HRV features.
Domaines
Sciences de l'ingénieur [physics]Origine | Fichiers produits par l'(les) auteur(s) |
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