Blood pressure is an important physiological parameter to reflect human vital signs.In order to achieve the non-contact dynamic blood pressure acquisition based on ordinary optical camera,a theoretical understanding o...Blood pressure is an important physiological parameter to reflect human vital signs.In order to achieve the non-contact dynamic blood pressure acquisition based on ordinary optical camera,a theoretical understanding of the functional relationship between blood pressure and pulse wave signal conduction time.And through imaging photoelectric plethysmography(IPPG),pulse wave signal conduction time of forehead and hand was obtained with ordinary optical camera.First,the pulse wave conduction time was obtained by recording the video with an ordinary optical camera.Second,real-time blood pressure values were collected.Finally,based on the relationship between blood pressure and pulse wave conduction time,a non-contact blood pressure measurement prediction model was obtained through neural network fitting.So that non-contact blood pressure measurement with optical camera could be completed.The method in this paper has several advantages,such as low requirements on measuring equipment,low cost,and simple operation.It can let people get rid of the discomfort caused by measuring equipment such as cuff and can measure blood pressure at any time.The predicted blood pressure results were compared with an Omron wrist electronic sphygmomanometer.The calculated error of systolic blood pressure is-9.28%~3.16%,and the error of diastolic blood pressure is-9.84~4.35%.展开更多
心率和血氧饱和度是反映人体健康状况极其重要的生理指标.近年来,基于成像式光电容积描记技术(imaging photoplethysmography,IPPG)的非接触式心率和血氧饱和度检测方法因为其方便快捷且受约束较少等优点开始逐步成为研究热点.主要工作...心率和血氧饱和度是反映人体健康状况极其重要的生理指标.近年来,基于成像式光电容积描记技术(imaging photoplethysmography,IPPG)的非接触式心率和血氧饱和度检测方法因为其方便快捷且受约束较少等优点开始逐步成为研究热点.主要工作如下:首先,介绍了非接触式检测方法的背景和研究意义;其次,从目标区域检测和感兴趣区域(region of interest,ROI)选取两个方面总结并点明其研究现状以及未来改进方向;再次,从传统方法、信号处理结合深度学习方法以及端到端方法3个方面对心率和血氧饱和度检测方法进行了总结,并梳理了深度学习方法所使用的数据集以及在各个数据集中所展现的检测效果;最后,指出该领域所存在的亟待解决的问题以及未来的研究方向.展开更多
Heart rate is an important vital characteristic which indicates physical and mental health status.Typically heart rate measurement instruments require direct contact with the skin which is time-consuming and costly.Th...Heart rate is an important vital characteristic which indicates physical and mental health status.Typically heart rate measurement instruments require direct contact with the skin which is time-consuming and costly.Therefore,the study of non-contact heart rate measurement methods is of great importance.Based on the principles of photoelectric volumetric tracing,we use a computer device and camera to capture facial images,accurately detect face regions,and to detect multiple facial images using a multi-target tracking algorithm.Then after the regional segmentation of the facial image,the signal acquisition of the region of interest is further resolved.Finally,frequency detection of the collected Photo-plethysmography(PPG)and Electrocardiography(ECG)signals is completed with peak detection,Fourier analysis,and a Waveletfilter.The experimental results show that the subject’s heart rate can be detected quickly and accurately even when monitoring multiple facial targets simultaneously.展开更多
基金The work of this paper is supported by the National Natural Science Foundation of China under Grant No.61572038,the Innovation Project Foundation NCUT.
文摘Blood pressure is an important physiological parameter to reflect human vital signs.In order to achieve the non-contact dynamic blood pressure acquisition based on ordinary optical camera,a theoretical understanding of the functional relationship between blood pressure and pulse wave signal conduction time.And through imaging photoelectric plethysmography(IPPG),pulse wave signal conduction time of forehead and hand was obtained with ordinary optical camera.First,the pulse wave conduction time was obtained by recording the video with an ordinary optical camera.Second,real-time blood pressure values were collected.Finally,based on the relationship between blood pressure and pulse wave conduction time,a non-contact blood pressure measurement prediction model was obtained through neural network fitting.So that non-contact blood pressure measurement with optical camera could be completed.The method in this paper has several advantages,such as low requirements on measuring equipment,low cost,and simple operation.It can let people get rid of the discomfort caused by measuring equipment such as cuff and can measure blood pressure at any time.The predicted blood pressure results were compared with an Omron wrist electronic sphygmomanometer.The calculated error of systolic blood pressure is-9.28%~3.16%,and the error of diastolic blood pressure is-9.84~4.35%.
文摘心率和血氧饱和度是反映人体健康状况极其重要的生理指标.近年来,基于成像式光电容积描记技术(imaging photoplethysmography,IPPG)的非接触式心率和血氧饱和度检测方法因为其方便快捷且受约束较少等优点开始逐步成为研究热点.主要工作如下:首先,介绍了非接触式检测方法的背景和研究意义;其次,从目标区域检测和感兴趣区域(region of interest,ROI)选取两个方面总结并点明其研究现状以及未来改进方向;再次,从传统方法、信号处理结合深度学习方法以及端到端方法3个方面对心率和血氧饱和度检测方法进行了总结,并梳理了深度学习方法所使用的数据集以及在各个数据集中所展现的检测效果;最后,指出该领域所存在的亟待解决的问题以及未来的研究方向.
基金supported by the National Nature Science Foundation of China(Grant Number:61962010).
文摘Heart rate is an important vital characteristic which indicates physical and mental health status.Typically heart rate measurement instruments require direct contact with the skin which is time-consuming and costly.Therefore,the study of non-contact heart rate measurement methods is of great importance.Based on the principles of photoelectric volumetric tracing,we use a computer device and camera to capture facial images,accurately detect face regions,and to detect multiple facial images using a multi-target tracking algorithm.Then after the regional segmentation of the facial image,the signal acquisition of the region of interest is further resolved.Finally,frequency detection of the collected Photo-plethysmography(PPG)and Electrocardiography(ECG)signals is completed with peak detection,Fourier analysis,and a Waveletfilter.The experimental results show that the subject’s heart rate can be detected quickly and accurately even when monitoring multiple facial targets simultaneously.
