title: Analysis and Recognition of Traditional Chinese Medicine Pulse Based on the Hilbert-Huang Transform and Random Forest in Patients with Coronary Heart Disease.
abstract: Objective. This research provides objective and quantitative parameters of the traditional Chinese medicine (TCM) pulse conditions for distinguishing between patients with the coronary heart disease (CHD) and normal people by using the proposed classification approach based on Hilbert-Huang transform (HHT) and random forest. Methods. The energy and the sample entropy features were extracted by applying the HHT to TCM pulse by treating these pulse signals as time series. By using the random forest classifier, the extracted two types of features and their combination were, respectively, used as input data to establish classification model. Results. Statistical results showed that there were significant differences in the pulse energy and sample entropy between the CHD group and the normal group. Moreover, the energy features, sample entropy features, and their combination were inputted as pulse feature vectors; the corresponding average recognition rates were 84%, 76.35%, and 90.21%, respectively. Conclusion. The proposed approach could be appropriately used to analyze pulses of patients with CHD, which can lay a foundation for research on objective and quantitative criteria on disease diagnosis or Zheng differentiation.
authors.affiliation: Laboratory of Information Access and Synthesis of TCM Four Diagnosis, Shanghai Univerisity of Traditional Chinese Medicine, Shanghai 201203, China ; Center for TCM Information Science and Technology, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
authors.forename: Rui
authors.initials: R
authors.lastname: Guo
authors.affiliation: Laboratory of Information Access and Synthesis of TCM Four Diagnosis, Shanghai Univerisity of Traditional Chinese Medicine, Shanghai 201203, China.
authors.forename: Yiqin
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Laboratory of Information Access and Synthesis of TCM Four Diagnosis, Shanghai Univerisity of Traditional Chinese Medicine, Shanghai 201203, China.
authors.forename: Hanxia
authors.initials: H
authors.lastname: Yan
authors.affiliation: Center for Mechatronics Engineering, East China University of Science and Technology, Shanghai 200237, China.
authors.forename: Jianjun
authors.initials: J
authors.lastname: Yan
authors.affiliation: The first Affiliated Hospital, School of clinical Medicine of G.D.P.U, Guangzhou 51000, China.
authors.forename: Fengyin
authors.initials: F
authors.lastname: Yuan
authors.affiliation: Laboratory of Information Access and Synthesis of TCM Four Diagnosis, Shanghai Univerisity of Traditional Chinese Medicine, Shanghai 201203, China.
authors.forename: Zhaoxia
authors.initials: Z
authors.lastname: Xu
authors.affiliation: Laboratory of Information Access and Synthesis of TCM Four Diagnosis, Shanghai Univerisity of Traditional Chinese Medicine, Shanghai 201203, China.
authors.forename: Guoping
authors.initials: G
authors.lastname: Liu
authors.affiliation: Laboratory of Information Access and Synthesis of TCM Four Diagnosis, Shanghai Univerisity of Traditional Chinese Medicine, Shanghai 201203, China.
authors.forename: Wenjie
authors.initials: W
authors.lastname: Xu