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The ebb and flow of heart rate variability: Simulation of 24 hour heart rate time series using time series data from naturally occurring phenomena

Lookup NU author(s): Dr Philip Langley, Professor John AllenORCiD, Emma Bowers, Dr Michael DrinnanORCiD, Abigail Haigh, Susan King, Dr Tom Olbrich, Dr Fiona Smith, Dr Ding Chang Zheng, Emeritus Professor Alan MurrayORCiD



Current RR time series simulations are distinguishable from real data by automatic algorithms. We hypothesised that RR time series simulations could be improved by using time series data from naturally occurring phenomena. 20 records of annual river flow data for the river Tyne in north eastern England were obtained. Each river flow data record was used to generate a single 24 h simulated RR time series with the property of self similarity. We compared the standard frequency parameters ULF, VLF, LF and HF normalised to the total power, for the simulated RR, with those from physiological data from 20 subjects. The river flow data produced realistic simulations of RR time series with significant differences between physiological and simulated series for VLF only. Time series data from river flow or other naturally occurring phenomena may provide useful components in producing RR time series with more realistic characteristics than current artificially generated data. © 2005 IEEE.

Publication metadata

Author(s): Langley P, Allen J, Bowers EJ, Drinnan MJ, Haigh AJ, King ST, Olbrich T, Smith FE, Zheng D, Murray A


Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Computers in Cardiology

Year of Conference: 2005

Pages: 973-976

Date deposited: 09/07/2010

ISSN: 0276-6574

Publisher: IEEE Computer Society


DOI: 10.1109/CIC.2005.1588271

Library holdings: Search Newcastle University Library for this item

ISBN: 0780393376