Non-Invasive Blood Pressure Measurement Using A Mobile Phone Camera

被引:1
作者
Zhang, Yuxuan [1 ]
Zhang, Xiao [1 ]
Du, Jinlian [1 ]
机构
[1] Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China
来源
2022 IEEE CONFERENCE ON COMPUTATIONAL INTELLIGENCE IN BIOINFORMATICS AND COMPUTATIONAL BIOLOGY (IEEE CIBCB 2022) | 2022年
关键词
Smartphone; Convolutional neural networks; Blood pressure; Photoplethysmography; PROTOCOL;
D O I
10.1109/CIBCB55180.2022.9863015
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In recent years, health sensing through smartphones has been more and more popular with the improvement of sensors and processing capacity. In this paper, we focus on capturing a fingertip video with a smartphone to monitor blood pressure. Current measurement techniques, however, require intrusive methods or inaccurate measurements. We present a low-cost system that uses smartphone cameras and a light source and our self-built convolutional neural network to measure blood pressure. We recruit 34 volunteers to verify our method. After 10-fold cross-validation, the mean absolute errors of our model for systolic and diastolic blood pressure were 4.44 mmHg and 3.68 mmHg, meeting the Association for the Advancement of Medical Instrumentation (AAMI) and British Hypertension Society (BHS) Grade A standards for blood pressure monitors. The method can be applied to every mobile device with a camera and has a wide range of applications.
引用
收藏
页码:11 / 16
页数:6
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