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Chinese Journal of Information on Traditional Chinese Medicine ; (12): 16-19, 2015.
Artigo em Chinês | WPRIM | ID: wpr-464854

RESUMO

Objective Base on the theory of traditional Chinese medicine (TCM), obtained human diagnostic information available for joint syndrome differentiation is integrated based on subjective and objective combined syndrome differentiation, in the form of data expression of TCM four diagnosis, forms multiple information fusion of open platform for TCM diagnosis and treatment, and provides some revelation for promoting the development of depression and treatment technology. Methods Totally 30 depression patients and 30 normal people were selected according to the inclusion criteria. TCM four diagnostic and auxiliary diagnosis instrument was used to collect information of four diagnosis, and the statistical software was used for the analysis on pulse diagnosis, and information features of digitalized tongue and listening diagnosis of patients in depression group and normal group were studied. Results Compared with depression group, pulse frequency, fluency, and heart rate of normal group were a bit higher than depression group, without statistical significance (P>0.05);There was statistical significance among pulse frequency, strength, tightness, and pulse wave velocity between the normal group and depression group (P<0.05). 30 patients had 6 depression syndrome types:heart-gallbladder qi deficiency (8 cases), phlegm-heat attacking internally (6 cases), fire excess from yin deficiency (6 cases), liver depression forming fire (6 cases), intense heart fire (3 cases), and heart-spleen deficiency (3 cases). Conclusion The results of differences in pulse diagram parameters were consistent with the theory of classical TCM pulse theory. The results of differences in pulse wave velocity conform to the modern medical research conclusion. TCM four diagnostic auxiliary diagnosis and treatment technology can realize the dynamic detection of depression patients with four diagnostic information, and establish diagnostic methods for depression based on digitalized four diagnostic auxiliary diagnosis.

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