Baroreflex sensitivity (BRS) measures the rate of changes in inter-beat time intervals (RR) with respect to changes in blood pressure (BP). Recently, Bivariate Phase-Rectified Signal Averaging (BPRSA) was proposed as possible BRS estimator and was compared with the validated sequence method (SM). However, the two methods differ substantially, questioning whether BPRSA might be considered as an estimator of BRS. In this study, we investigated the role that the coupling between RR, BP and respiration has on BRS estimates provided by BPRSA and SM. Multivariate autoregressive models (MVAR) were fitted to the data of 10 healthy subjects that underwent a tilt test. MVAR models were then used to generate synthetic signals while artificially varying the coupling between RR, BP and respiration. Both BPRSA and SM provided higher BRS values during supine with respect to head-up phase. Computerized simulations showed little influence of the coupling between respiration and RR on both estimators, whereas a major difference appeared when the coupling between BP and RR was removed. Then, BPRSA almost vanished, while SM increased of about 10%, regardless the phase. In conclusion, BRS estimates using BPRSA were highly dependent on the coupling between BP and RR, while SM resulted in more stable estimates.

Comparison between Bivariate Phase-Rectified Signal Averaging and Sequence Method in Assessing the Baroreflex Sensitivity / M.W. Rivolta, R. Sassi - In: Computing in Cardiology[s.l] : IEEE Computer Society, 2020. - ISBN 9781728173825. - pp. 1-4 (( Intervento presentato al 47. convegno CinC tenutosi a Rimini nel 2020.

Comparison between Bivariate Phase-Rectified Signal Averaging and Sequence Method in Assessing the Baroreflex Sensitivity

M.W. Rivolta
Primo
;
R. Sassi
Ultimo
2020

Abstract

Baroreflex sensitivity (BRS) measures the rate of changes in inter-beat time intervals (RR) with respect to changes in blood pressure (BP). Recently, Bivariate Phase-Rectified Signal Averaging (BPRSA) was proposed as possible BRS estimator and was compared with the validated sequence method (SM). However, the two methods differ substantially, questioning whether BPRSA might be considered as an estimator of BRS. In this study, we investigated the role that the coupling between RR, BP and respiration has on BRS estimates provided by BPRSA and SM. Multivariate autoregressive models (MVAR) were fitted to the data of 10 healthy subjects that underwent a tilt test. MVAR models were then used to generate synthetic signals while artificially varying the coupling between RR, BP and respiration. Both BPRSA and SM provided higher BRS values during supine with respect to head-up phase. Computerized simulations showed little influence of the coupling between respiration and RR on both estimators, whereas a major difference appeared when the coupling between BP and RR was removed. Then, BPRSA almost vanished, while SM increased of about 10%, regardless the phase. In conclusion, BRS estimates using BPRSA were highly dependent on the coupling between BP and RR, while SM resulted in more stable estimates.
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Settore ING-INF/06 - Bioingegneria Elettronica e Informatica
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/824332
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