A non-contact blood pressure measurement method was proposed and achieved based on theoretical deduction of the relationship among pulse transit time, heart rate and blood pressure. Pulse transit time was estimated using heart rate and phase difference of pulse wave which were obtained from color videos through imaging photoplethysmographic. Parameters of the functional relationship were determined through curve fitting with experiment data. Error analysis was processed with an Omron electronic sphygmomanometer as reference to verify the accuracy of blood pressure obtained using the proposed method. The error of acquired systolic blood pressure varied from -2.40 to 3.43 percent. The error of acquired diastolic blood pressure varied from -6.88 to 5.26 percent.
In this paper, a road detection algorithm from the low illumination remote sensing images is proposed. First, the top-hat transform is used to enhance the edge information in low illumination images. Next, a road detection method based on parallel lines is proposed to detect the parallel characteristics of the two edges of the road. The experiment results show that the proposed algorithm can detect the road information effectively and precisely.
Non-contact measurements of the cardiac pulse of humanity is always a challenging problem. Almost all the existing research work concentrates on heart rate measurements based on video recordings of the human face, in which the subject is restricted rigidly. In this paper, we propose a novel approach based on skin detection method. The skin regions in color video recordings are generalized to anywhere of the human body, not limited to human face. The skin detector and a chrominance-based technique are firstly used to detect the photo-plethysmo-graphy (PPG) signal. Then, we use an empirical parameter selection method to get the final heart rate estimation. The experiment results show the effectiveness of the proposed method.
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