CAP waveform estimation from the measured electrical bioimpedance values: Patient's heart rate variability analysis

Area of Science:

• Biomedical Engineering
• Cardiovascular Physiology
• Signal Processing

Background:

• Non-invasive estimation of Central Aortic Pressure (CAP) is crucial for cardiovascular monitoring.
• Electrical Bioimpedance (EBI) offers a non-invasive method, but its relationship with CAP requires precise modeling.
• Heart Rate (HR) variability can influence the accuracy of bioimpedance-based pressure estimations.

Purpose of the Study:

• To analyze the generic transfer function (TF) between non-invasively measured wrist EBI and invasively measured CAP.
• To investigate the influence of Heart Rate (HR) variations on the TF and reconstructed CAP waveforms.
• To present a novel approach for estimating the generic TF from ensemble data and optimize cardiac period selection.

Main Methods:

• Analysis of the transfer function (TF) relating wrist Electrical Bioimpedance (EBI) to Central Aortic Pressure (CAP).
• Investigation of Heart Rate (HR) variations using single-patient data to isolate TF and CAP waveform influences.
• Development and application of a new ensemble-based method for generic TF estimation, including cardiac period selection analysis.

Main Results:

• The study quantifies the influence of HR variations on the EBI-to-CAP transfer function.
• Reconstructed CAP waveforms are shown to be affected by HR fluctuations.
• An empirically optimal method for selecting the cardiac period beginning point for TF estimation is proposed.

Conclusions:

• Accurate estimation of the transfer function between EBI and CAP requires accounting for heart rate variations.
• The proposed ensemble-based method and cardiac period selection strategy enhance the reliability of non-invasive CAP estimation.
• This research contributes to improving non-invasive cardiovascular monitoring techniques using electrical bioimpedance.