首页|Classification research of TCM pulse conditions based on multi-label voice analysis
Classification research of TCM pulse conditions based on multi-label voice analysis
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国家科技期刊平台
NETL
NSTL
万方数据
Objective:To explore the feasibility of remotely obtaining complex information on traditional Chinese medicine(TCM)pulse conditions through voice signals.Methods:We used multi-label pulse conditions as the entry point and modeled and analyzed TCM pulse diagnosis by combining voice analysis and machine learning.Audio features were extracted from voice recordings in the TCM pulse condition dataset.The obtained features were combined with information from tongue and facial diagnoses.A multi-label pulse condition voice classification DNN model was built using 10-fold cross-validation,and the modeling methods were validated using publicly available datasets.Results:The analysis showed that the proposed method achieved an accuracy of 92.59％on the public dataset.The accuracies of the three single-label pulse manifestation models in the test set were 94.27％,96.35％,and 95.39％.The absolute accuracy of the multi-label model was 92.74％.Conclusion:Voice data analysis may serve as a remote adjunct to the TCM diagnostic method for pulse condition assessment.
Key Laboratory of TCM-information Engineer of State Administration of TCM,School of Chinese Materia Medica,Beijing University of Chinese Medicine,Beijing,102488,China
School of Traditional Chinese Medicine,Beijing University of Chinese Medicine,Beijing,102488,China
Sinosense Technology Co.,Ltd,Beijing,100141,China
Fundamental Research Funds from the Beijing University of Chinese MedicineDevelopmental Fund of Beijing University of Chinese Medicine
国家科技期刊平台
NSTL
万方数据
