Abstract
Pulse diagnosis is an important part of the theoretical system of traditional Chinese medicine, but is subject to the doctor’s subjective assumptions and other factors and is difficult to teach. Therefore, to achieve objective and accurate pulse classification and further improve pulse diagnosis and treatment, this paper presents a pulse classification method based on multi-factor analysis. Pulse wave data were collected from each person in the static state, after which the cosine similarity theorem and principal components analysis were used to identify the pulse type after extracting the characteristics of the pulse waveform. Compared with previous methods, this method has the advantages of high recognition rate, comprehensive pulse classification, and inclusion of multiple factors. This method has been proven to be a good reference for digitalization, visualization, and automatic diagnosis of pulse in Chinese medicine.
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Acknowledgement
The authors are grateful for the support from the National Nature Science Foundation of China (61632002, 61379059, and 61572046), and the Natural Science Foundation of Guangdong Province of China (2018A030313380).
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Chen, Z., Huang, A., Qiang, X. (2018). Research on Pulse Classification Based on Multiple Factors. In: Qiao, J., et al. Bio-inspired Computing: Theories and Applications. BIC-TA 2018. Communications in Computer and Information Science, vol 952. Springer, Singapore. https://doi.org/10.1007/978-981-13-2829-9_7
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DOI: https://doi.org/10.1007/978-981-13-2829-9_7
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