Smarter Blood Pressure Monitoring
An Innovation from Electrical Engineering Department, FMIPA, Universitas Padjadjaran
Monitoring blood pressure might no longer require bulky cuffs! A research team from the Department of Electrical Engineering, Universitas Padjadjaran (Unpad) has introduced a breakthrough in healthcare technology through their paper titled “Precision blood pressure prediction leveraging Photoplethysmograph signals using Support Vector Regression.” By combining Photoplethysmograph (PPG) signals from a single fingertip with the power of Support Vector Regression (SVR), the study successfully delivers a non-invasive, accurate, and real-time method of estimating blood pressure.
The research involved more than 100 participants aged 20–70 years to train and validate the model. Results showed impressive accuracy, with error rates as low as 2.78 mmHg for systolic and 7.34 mmHg for diastolic pressure during testing. Even when validated with new participants, the model maintained over 90% accuracy, proving its reliability and adaptability. Such performance makes this innovation a promising solution for integration into wearable devices and medical robots, offering continuous monitoring without discomfort.
This achievement aligns strongly with the United Nations Sustainable Development Goals (SDGs). Specifically, it supports SDG 3: Good Health and Well-being by enabling accessible and non-invasive health monitoring. With this innovation, Unpad continues to strengthen its role in driving impactful research that bridges engineering, healthcare, and global sustainability.
Link: https://www.sciencedirect.com/science/article/pii/S1110866524001622?via%3Dihub
#UnpadResearch #HealthcareInnovation #SDG3
04/TE/2025
