On the target area tracking method for heart rate measurement using deep learning strategy

Autor: Bailin Ge, Sai Zhang, Jiancheng Zou
Rok vydání: 2019
Předmět:
Zdroj: Eleventh International Conference on Digital Image Processing (ICDIP 2019).
DOI: 10.1117/12.2539746
Popis: Heart rate monitoring is important for diagnosis and prevention of physiological diseases. The method of measuring heart rate by infrared sequence image has high accuracy. But shaking is a factor to affect the measurement result. Even if a slight shaking will create a big measurement error. In this paper, we propose an automatic capture algorithm of heart rate measurement through the real-time tracking and capturing of the face monitoring area, so the disturbance caused by human body shaking is overcome. Compared with the traditional method1 , the measurement accuracy of the tests with shaking is improved about 6% higher based on our algorithm.
Databáze: OpenAIRE