Abstract
Monitoring blood pressure (BP) is an essential component of evaluating cardiovascular health, aiding in the early detection and management of hypertension-related complications. Traditional methods of BP measurement often involve invasive or cumbersome devices, leading to discomfort and reduced compliance. We propose a framework to monitor BP non-invasively, analyzing the face video captured by a webcam or smartphone camera leveraging the relationship of image-based Pulse Transit Time (iPTT) and Heart Rate Variability (HRV) with BP. We have built a dataset of 90 sets of collected videos using a mobile phone front camera and BP data from a standard digital BP monitor from 12 individuals from an approved Institutional Review Board (IRB) to evaluate our system. We have got a Mean Absolute Error (MAE) of 10.35+/−2.5 mmHg for systolic BP (SBP) and 7.8+/−1.5 mmHg for diastolic BP (DBP) while using the HRV representation RMSSD. On the other hand, an MAE of 8.25+/−3.5 mmHg for SBP and 7.7+/−2.5 mmHg for DBP while using the HRV representation SDRR. Finally, we have developed a framework and built a real-time system to monitor BP as a mobile and web-based application that can facilitate early detection of trends and anomalies, allowing healthcare providers to intervene promptly and personalize treatment plans.
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