Optimal Number of Cardiac Cycles for Continuous Blood Pressure Estimation

Abstract

Continuous blood pressure monitoring is essential for patients with hypertension. Most studies have suggested cuffless blood pressure monitoring techniques using a single cardiac cycle based on the pulse transit time. This paper investigates feature extraction from multiple cardiac cycles to estimate blood pressure. This implementation uses electrocardiogram, photoplethysmogram, and ballistrocardiagram signals. Random forest was applied to estimate blood pressure using the leave-one-subject-out cross-validation technique. The results show that the model could achieve better performance when using three cardiac cycles with an average MAE of 3.364 ± 3.059 mmHg for the diastolic blood pressure and 4.201 ±2.355 mmHg for the systolic blood pressure.