Abstract
Blood pressure (BP) is an important physiological signal of human body. How to measure blood pressure is a meaningful problem for detection of human health. The most commonly used method is cuff based method. But this method can not used for continuous blood pressure measurement. For this concern, a Photoplethysmogram-based method for continuous blood pressure measurement was presented. Many researches have found that there are some relations exist between some Photoplethysmogram (PPG) signal features and human blood pressure. We use an artificial neural network model and a cluster method to make some estimation on human blood pressure based on Photoplethysmogram signal, and our result shows that this method can be used for noninvasive continuous blood pressure measurement in future.
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Acknowledgments
This work is supported by the National Natural Science Foundation of China (Nos. 61672181, 61202090, 61272184), Natural Science Foundation of Heilongjiang Province (No. F2016005), the Science and Technology Innovation Talents Special Fund of Harbin (Nos. 2016RAXXJ036, 2015RQQXJ067), the opening found of Key Laboratory of Machine Perception (Ministry of Education), Peking University (K-2016-02).
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Miao, Y., Zhang, Z., Meng, L., Xie, X., Pan, H. (2017). A Cluster Method to Noninvasive Continuous Blood Pressure Measurement Using PPG. In: Xing, C., Zhang, Y., Liang, Y. (eds) Smart Health. ICSH 2016. Lecture Notes in Computer Science(), vol 10219. Springer, Cham. https://doi.org/10.1007/978-3-319-59858-1_11
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DOI: https://doi.org/10.1007/978-3-319-59858-1_11
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