@inproceedings{379ba72b6a5e47fcae7f8a990aa06b2e,
title = "Non-contact continuous blood pressure measurement based on imaging equipment",
abstract = "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.",
keywords = "Blood pressure, Continuous, Machine learning, Non-contact, PLSR",
author = "Ying Guo and Xiaohua Liu and Lingqin Kong and Ming Liu and Yuejin Zhao and Liquan Dong",
note = "Publisher Copyright: {\textcopyright} 2020 SPIE.; 2019 International Conference on Optical Instruments and Technology: Optoelectronic Imaging/Spectroscopy and Signal Processing Technology ; Conference date: 26-10-2019 Through 28-10-2019",
year = "2020",
doi = "10.1117/12.2540316",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Guohai Situ and Xun Cao and Wolfgang Osten",
booktitle = "2019 International Conference on Optical Instruments and Technology",
address = "United States",
}