An Empirical Mode Decomposition Approach to Assess the Strength of Heart Period-Systolic Arterial Pressure Variability Interactions

Luca Faes, Vlasta Bari, Gianluca Rossato, Davide Tonon, Beatrice De Maria, Beatrice Cairo, Vlasta Barip, Alberto Porta

Risultato della ricerca: Conference contribution

Abstract

This work proposes an empirical mode decomposition (EMD) method to assess the strength of the interactions between heart period (HP) and systolic arterial pressure (SAP) variability. EMD was exploited to decompose the original series (OR) into its first, and fastest, intrinsic mode function (IMF1) and the residual (RES) computed by subtracting the IMF1 from OR. EMD procedure was applied to both HP and SAP variability series. Then, the cross correlation function (CCF) was computed over OR, IMF1 and RES series derived from HP and SAP variability in 13 healthy subjects (age 27±8 yrs, 5 males) at rest in supine position (REST) and during head-up tilt (TILT). The first CCF maximum at negative time lags and the first CCF minimum at positive time lags were taken respectively as indexes of the coupling along the feedback baroreflex and feedforward mechanical arms of HP-SAP closed-loop control. Results showed that the coupling strength is increased during TILT on both arms and this result holds on REST. At REST the coupling along both arms was stronger when computed over IMF1 because interactions were mainly governed by respiration. This result was not observed during TILT possibly due to the reduced importance of respiration compared to other mechanisms acting at slower time scales. The proposed method allowed the investigation of the strength of HP-SAP variability interactions according to the time scales of the physiological mechanisms.The proposed EMD-based method allows the quantification of the strength of the HP-SAP closed-loop variability interactions according to the different time scales of respiration and slower baroreflex-mediated reflexes.
Lingua originaleEnglish
Titolo della pubblicazione ospiteProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Pagine2573-2576
Numero di pagine4
Stato di pubblicazionePublished - 2020

Serie di pubblicazioni

NomeIEEE ENGINEERING IN MEDICINE AND BIOLOGY ... ANNUAL CONFERENCE PROCEEDINGS

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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