Abstract
Direct blood pressure (BP) measurements require cuff compression, which not only is time-consuming but also inconvenient for frequent monitoring. This study addresses the challenge of continuous BP estimation (both Systolic (SBP) and Diastolic (DBP)) during exercise in a cuff-less manner, utilizing photoplethysmography (PPG) signals acquired by low-cost wearables. Leveraging Reflective Pulse-wave Transit Time (R-PTT), state-of-the-art algorithms were put to the test in two datasets (total subjects = 18). DATASET1 contains PPG signal and BP measurements of subjects in resting state, while DATASET2 comprises data of subjects in resting state and during exercise. The results reveal competitive performance, with Mean Absolute Error (MAE) of the estimation algorithm for DATASET1 being SBP=7.9 mmHg and DBP=5.2 mmHg and SBP=14.4 mmHg and DBP=7.7 mmHg for DATASET2. DATASET1 consistently outperforms DATASET2, affirming the algorithm's efficacy during resting states and that estimation during physical activity introduces challenges, requiring further refinement and research for real-world applications. In conclusion, this research unveils a viable solution for continuous cuff-less BP monitoring, while emphasizing the need for refinement and validation to enhance its clinical applicability and accessibility.