Photoacoustic Blood Pressure Recognition Based on Deep LearningXiaoman Zhang, Huaqin Wu, Biying Yu, Sulian Wu, Weijie Wu,Jianyong Cai*and Hui Li* Key Laboratory of OptoElectronicScience and Technology for Medicine of Ministry of Education,Fujian Provincial Key Laboratory of Photonics Technology,College of Photonic and Electronic Engineering, Fujian Normal University Ministry of Education, Fuzhou 350007, P.R. ChinaABSTRACTContinuous and non-invasive real-time measurement of human blood pressure is of great importance for health care and clinical diagnosis.Photoacoustic imaging allows absorption-based high-resolution spectroscopyin vivo imaging with a depth beyond that of optical microscopy. In this study,a novel photoacoustic imaging systemis usedfor monitoring and imaging of vesselpulsation,whichcan realize simple, non-invasive and continuous measurement and recognition of blood pressure. Combined with deep learning method, a model is established to effectively evaluate the dependence of blood vessel elasticity on theblood pressure.These results can quickly and accurately identify the photoacoustic signals of blood vessels under different pressures.
Resting heart rate (RHR) is considered an important biomedical indicator to evaluate cardiovascular function. High RHR is an important prognostic factor for sudden cardiac death and heart failure in the general population, and especially among patients with known cardiac disease. The imaging photoplethysmography (IPPG) technology is used to achieve the accurate detection of RHR signal, which has the advantages of low cost, simple operation, fast acquisition speed etc. In this paper, we propose a new simple, inexpensive and easy-to-use method to measure the RHR in vivo. The result shows that Fast Fourier Transform with Hamming window filters, band-pass filter gives more accurate results. The color change of the fingertip is enlarged by using the mobile phone camera. From the distribution of color change of the fingertip, the RHR is estimated with the primary calibration result of the relationship between color variation and the blood volume change.
With the development of diagnostic and therapeutic options in gastric cancer, the incidence of gastric cancer is decreasing over the past two decades. However, it is still necessary to improve the early diagnosis technology of gastric cancer to reduce the mortality of gastric cancer. Photoacoustic imaging is a rapidly developing diagnostic modality of cancer which is based on optical excitation and ultrasonic detection. In this paper, photoacoustic imaging is proposed as a visual tool to compound structural and location information for early stage gastric cancer detection by using nanoscale gold rods. The experimental results showed that the nanoscale gold rods can increase penetration depth of tumor in addition to that diagnosing the early gastric cancer with no obvious symptoms.
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