This study reports on the reliability of Lagged Poincare Plot (LPP) parameters calculated from ultra-short ´ cardiovascular time series (from 30 to 180 seconds). Recently, several studies have investigated on the accuracy of linear features extracted from ultra-short Heart Rate Variability (HRV) signals, whereas a few studies have studied nonlinear approaches. Particularly, methods derived from the phase-space theory, especially the ones employing multi-lag analyses, are usually considered to be inaccurate with a low number of samples. Here we propose a comprehensive study about LPP, using both synthetic and real RR series. Specifically, we considered 109 5-minutes HRV series: 60 synthetic series generated through the Integral Pulse Frequency Modulation (IPFM) model and 49 experimental series acquired from healthy subjects during resting-state. Three parameters have been extracted through the ellipse-fitting method, SD1, SD2 and S, using ten values of lag. All LPP parameters were estimated by averaging estimates gathered from segments of 30, 120 and 180 seconds, and compared with the once from 5-minute series. Results showed Spearman’s correlation coefficients higher than 0.9 in both synthetic and real series. In conclusion, SD1 gave promising results in terms of percentage absolute error, when it was extracted from series with a duration less than three minutes

Investigation of Lagged Poincaré Plot reliability in ultra-short synthetic and experimental Heart Rate Variability series

M. Nardelli;A. Greco;G. Valenza;E. P. Scilingo;
2017-01-01

Abstract

This study reports on the reliability of Lagged Poincare Plot (LPP) parameters calculated from ultra-short ´ cardiovascular time series (from 30 to 180 seconds). Recently, several studies have investigated on the accuracy of linear features extracted from ultra-short Heart Rate Variability (HRV) signals, whereas a few studies have studied nonlinear approaches. Particularly, methods derived from the phase-space theory, especially the ones employing multi-lag analyses, are usually considered to be inaccurate with a low number of samples. Here we propose a comprehensive study about LPP, using both synthetic and real RR series. Specifically, we considered 109 5-minutes HRV series: 60 synthetic series generated through the Integral Pulse Frequency Modulation (IPFM) model and 49 experimental series acquired from healthy subjects during resting-state. Three parameters have been extracted through the ellipse-fitting method, SD1, SD2 and S, using ten values of lag. All LPP parameters were estimated by averaging estimates gathered from segments of 30, 120 and 180 seconds, and compared with the once from 5-minute series. Results showed Spearman’s correlation coefficients higher than 0.9 in both synthetic and real series. In conclusion, SD1 gave promising results in terms of percentage absolute error, when it was extracted from series with a duration less than three minutes
2017
978-150902809-2
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1078934
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