摘要
文中设计非接触测量生理参数的仪器。基于图像光电容积脉搏波描记法(Imaging photoplethysmography,IPPG)原理,检测到的反射光强中就包含了组织的生理信息,通过对人脸视频图像进行卷积神经网络识别人脸,同时采用多步信号处理算法进行处理,得出心率、呼吸速率以及血氧饱和度数值。该系统可非接触进行监测,平台易操作、低成本,因而在临床应用及家庭健康监测等场景中有广阔的应用前景。
This paper designs non-contact measurement of physiological parameters. Based on image photoelectric volume pulse wave tracing（ Imaging photoplethysmography,IPPG） principle,the detected contain tissue in the reflected light is strong physiological information,through the face video image convolution neural network to recognize faces,followed by signal processing algorithm for processing at the same time,it concluded that the heart rate,respiratory rate and blood oxygen saturation value. The system can not be contacted for monitoring,the platform is easy to operate and low cost,so it has a broad application prospect in clinical application and family health monitoring.
作者
汪秀军
曹大平
曹宜
舒兴
荣猛
范强
WANG Xiu-jun;CAO Da-ping;CAO Yi;SHU Xing;RONG Meng;FAN Qiang(School of Physics and Technology,Wuhan University,Wuhan 430072,Chin)
出处
《信息技术》
2018年第8期17-22,共6页
Information Technology
基金
国家自然科学基金资助(41274188)
关键词
IPPG
卷积神经网络
心率
呼吸速率
血氧饱和度
imaging photoplethysmography
convolutional neural network
heart rate
respiratory rate
blood oxygen saturation
