  Background and Objectives: In a significant portion of surgeries, blood
pressure (BP) is often measured non-invasively in an intermittent manner. This
practice has a risk of missing clinically relevant BP changes between two
adjacent intermittent BP measurements. This study proposes a method to
non-invasively estimate systolic blood pressure (SBP) with high accuracy in
patients undergoing surgery. Methods: Continuous arterial BP,
electrocardiography (ECG), and photoplethysmography (PPG) signals were acquired
from 29 patients undergoing surgery. After extracting 9 features from the PPG
and ECG signals, we dynamically selected features upon each intermittent
measurement (every 10 min) of SBP based on feature robustness and the principle
of correlation-based feature selection. Finally, multiple linear regression
models were built to combine these features to estimate SBP every 30 s.
Results: Compared to the reference SBP, the proposed method achieved a mean of
difference at 0.08 mmHg, a standard deviation of difference at 7.97 mmHg, and a
correlation coefficient at 0.89 (p < 0.001). Conclusions: This study
demonstrates the feasibility of non-invasively estimating SBP every 30 s with
high accuracy during surgery by using ECG, PPG, and intermittent SBP
measurements every 10 min, which meets the standard of the Association for the
Advancement of Medical Instrumentation. The proposed method has the potential
to enhance BP monitoring in the operating room, improving patient outcomes and
experiences.
