Optimized machine learning for real-time, non-invasive blood pressure monitoring

This study presents a hybrid machine learning framework that fuses photoplethysmography and electrocardiography signals with optimized feature selection to achieve accurate and efficient BP estimation, offering a practical solution for continuous, cuffless BP monitoring in personalized and digital healthcare.