Regression analysis and transfer function in estimating the parameters of central pulse waves from brachial pulse...

Area of Science:

• Cardiovascular Physiology
• Biomedical Engineering
• Medical Signal Processing

Background:

• Accurate measurement of central pulse wave parameters is crucial for cardiovascular assessment.
• Non-invasive methods are desirable but require validation against invasive measurements.
• Existing models for estimating central pulse wave parameters from peripheral measurements have varying accuracy.

Purpose of the Study:

• To analyze and compare various central pulse wave parameters obtained invasively and non-invasively.
• To evaluate the accuracy of regression and transfer function models in estimating central pulse wave parameters from brachial pulse waves.
• To compare the performance of these models in cardiovascular health assessment.

Main Methods:

• Invasive and non-invasive measurement of central pulse wave parameters including ascending branch slope (A_slope), dicrotic notch height (Hn), diastolic area (Ad), systolic area (As), diastolic blood pressure (DBP), systolic blood pressure (SBP), pulse pressure (PP), subendocardial viability ratio (SEVR), waveform parameter (k), stroke volume (SV), cardiac output (CO), and peripheral resistance (RS).
• Comparison of invasively measured central pulse wave parameters with those derived from brachial pulse waves using regression and transfer function models.
• Assessment of the accuracy of parameters estimated by both the regression and transfer function models.

Main Results:

• Positive correlations were observed between invasively measured central and brachial pulse wave parameters, excluding the k value.
• Both regression model parameters (A_slope, DBP, SEVR) and transfer function model parameters demonstrated good consistency with invasively measured data.
• The transfer function model exhibited higher accuracy than the regression model for calculating SBP, PP, SV, and CO from central pulse waves.

Conclusions:

• Non-invasive estimation of central pulse wave parameters from brachial measurements is feasible using validated models.
• The transfer function model provides a more accurate approach for deriving key hemodynamic parameters compared to the regression model.
• These findings support the use of non-invasive pulse wave analysis for cardiovascular monitoring and risk assessment.