Noninvasive continuous blood pressure prediction using FlexNIRS and machine learning during carotid endarterectomy.

ABSTRACT:

Significance

Continuous blood pressure (BP) monitoring is crucial for maintaining hemodynamic stability and complication prevention. Near-infrared spectroscopy photoplethysmography (NIRS-PPG) offers a noninvasive alternative to arterial lines (A-line) for continuous BP monitoring.

Aim

We aim to assess whether a wearable NIRS-PPG device (FlexNIRS) can estimate mean arterial pressure (MAP) using linear and Gaussian process regression (GPR) models.

Approach

NIRS-PPG signals were recorded bilaterally in 10 patients undergoing carotid endarterectomy. Subject-specific linear regression and GPR models predicted MAP based on heart rate and peak features of the NIRS-PPG signal. A-line readings served as the reference.

Results

All models achieved strong performance with

SUBMITTER: Einalou Z 

PROVIDER: S-EPMC12447979 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature