A non-contact blood pressure measurement method based on face video
Lifeng Yang1, Shaojie Gu1, Binbin Liu1
1School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China.
Physical and Engineering Sciences in Medicine
|October 20, 2025
Summary
This study introduces a non-contact method for measuring blood pressure using facial videos and machine learning. The technique accurately estimates blood pressure, meeting international medical device standards.
Area of Science:
- Biomedical Engineering
- Cardiovascular Health
- Artificial Intelligence in Medicine
Background:
- Accurate blood pressure measurement is crucial for cardiovascular health and disease prevention.
- Photoplethysmography (PPG) and machine learning offer promising avenues for noninvasive blood pressure monitoring.
- Current methods may lack convenience or require physical contact.
Purpose of the Study:
- To develop and validate a non-contact method for blood pressure estimation using facial videos.
- To leverage facial remote photoplethysmography (RPPG) signals and machine learning for accurate readings.
- To assess the method's compliance with established medical standards.
Main Methods:
- Extracting RPPG signals from facial videos captured by a camera.
- Applying signal processing techniques to enhance RPPG quality.
- Utilizing an extreme gradient boosting tree (XGBoost) model for blood pressure regression.
Main Results:
- Achieved measurement errors of 4.8893 ± 6.6237 mmHg for systolic and 4.0805 ± 5.5821 mmHg for diastolic pressure.
- Demonstrated full compliance with American Medical Instrumentation Association (AAMI) standards.
- Attained a Grade A evaluation for both systolic and diastolic blood pressure predictions per British Hypertension Society (BHS) standards.
Conclusions:
- The proposed non-contact method provides accurate blood pressure measurements with minimal error.
- This approach offers a convenient and effective alternative for blood pressure monitoring.
- The method's adherence to AAMI and BHS standards validates its clinical potential.
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