Reconstruction of Continuous Brachial Arterial Pressure From Continuous Finger Arterial Pressure Using a Two-Level Optimization Strategy.

Abstract

We attempt to reconstruct brachial arterial pressure (BAP) waves from finger arterial pressure waves measured using the vascular unloading technique without arm-cuff calibration. A novel method called two-level optimization (TOP) strategy is proposed as follows. We first derive a simplified transfer function (TF) based on a tube-load model with only two parameters to be estimated, a coefficient B and a time delay ∆t. Then, at level one, two minimization problems are formulated to estimate the optimal coefficient B^opt and time delay ∆t^opt. Then, we can derive an optimal TF h^opt(t). However, this derivation requires true (or reference) BAP waves. Therefore, at level two, we apply multiple linear regression (MLR) to further model the relationship between the derived optimal parameters and subjects' physiologic parameters. Hence, eventually, one can estimate coefficient B^MLR and time delay ∆t^MLR from subject's physiologic parameters to derive the MLR-based TF h^MLR(t) for the BAP reconstruction. Twenty-one volunteers were recruited for the data collection. The mean ± standard deviation of the root mean square errors between the reference BAP waves and the BAP waves reconstructed by h^opt(t), h^MLR(t), and a generalized transfer function (GTF) were 3.46 ± 1.42 mmHg, 3.61 ± 2.28 mmHg, and 6.80 ± 3.73 mmHg (significantly larger with p < 0.01), respectively. The proposed method can be considered as a semi-individualized TF which reconstructs significantly better BAP waves than a GTF. The proposed TOP strategy can potentially be useful in more general reconstruction of proximal BP waves.