An optical and non-contact continuous measurement method to detect human blood pressure through a high-speed camera is discussed in this paper. With stable ambient light, photoplethysmographic (PPG) signals of face and palm area are obtained simultaneously from the video captured by high-speed camera, whose frame rate should be higher than 100 frames per second. Pulse transit time (PTT) is measured from the R-wave distance between the two PPG signals. The Partial least squares regression( PLSR) model was established to train the samples, and the relationship between PTT and blood pressure, including intra-arterial systolic pressure (SBP) and diastolic pressure (DBP), was established to obtain blood pressure. Compared with the output of traditional sphygmomanometer, the blood pressure data collected from non-contact system has little error and meets the fitting conditions. We first proposed an accurate video-based method for non-contact blood pressure measurement using machine learning, and the average error of SBP is 0.148mmHg and of DBP is 0.359mmHg.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.