Measuring multi-site pulse transit time with an AI-enabled mmWave radar

TL;DR

This paper introduces an AI-enabled mmWave radar system capable of contactless multi-site pulse transit time measurement and blood pressure estimation, demonstrating high accuracy and potential for non-invasive cardiovascular monitoring.

Contribution

The paper presents the first AI-enabled mmWave system for simultaneous multi-site PTT measurement and blood pressure estimation using a single radar device.

Findings

Achieved correlation coefficients of 0.73-0.89 for PTT measurement.

Achieved correlation coefficients of 0.90-0.92 for diastolic blood pressure estimation.

Met FDA guidelines for non-invasive blood pressure monitoring.

Abstract

Pulse Transit Time (PTT) is a measure of arterial stiffness and a physiological marker associated with cardiovascular function, with an inverse relationship to diastolic blood pressure (DBP). We present the first AI-enabled mmWave system for contactless multi-site PTT measurement using a single radar. By leveraging radar beamforming and deep learning algorithms our system simultaneously measures PTT and estimates diastolic blood pressure at multiple sites. The system was evaluated across three physiological pathways - heart-to-radial artery, heart-to-carotid artery, and mastoid area-to-radial artery -- achieving correlation coefficients of 0.73-0.89 compared to contact-based reference sensors for measuring PTT. Furthermore, the system demonstrated correlation coefficients of 0.90-0.92 for estimating DBP, and achieved a mean error of -1.00-0.62 mmHg and standard deviation of 4.97-5.70 mmHg, meeting the FDA's AAMI guidelines for non-invasive blood pressure monitors. These results suggest that our proposed system has the potential to provide a non-invasive measure of cardiovascular health across multiple regions of the body.