Noncontact Blood Pressure Estimation From the Carotid Pulse Wave Signal Using a Modified ResNet-18 Network With LFMCW Radar

In this article, a radar-based noncontact blood pressure (BP) monitoring system has been proposed for systolic BP (SBP) and diastolic BP (DBP) estimation. A linear frequency-modulated continuous wave (LFMCW) radar sensor has been utilized to capture the carotid pulse wave signal contactlessly. After that, a modified residual neural network model based on the ResNet-18 architecture was constructed to estimate the BP values based on the radar-acquired carotid pulse wave signal. The experimental database with 100 human subjects has been collected in a laboratory environment. The record-wise mean absolute errors (MAEs) of SBP and DBP estimations are 3.51 and 2.44 mmHg, respectively. Regarding the standard deviation (STD), the error performance of SBP and DBP estimations are 6.90 and 4.61 mmHg, respectively. Furthermore, the subject-wise MAEs of SBP and DBP achieve 5.92 and 4.32 mmHg, respectively. The proposed method can be a good extension for cuffless BP measurement and potentially be applied in many scenarios that require dynamic BP tracking, such as sleep or perioperative periods.