Objective Auscultation of TCM Based on Wavelet Packet Fractal Dimension and Support Vector Machine

Abstract

This study was conducted to illustrate that auscultation features based on the fractal dimension combined with wavelet packet transform (WPT) were conducive to the identification the pattern of syndromes of Traditional Chinese Medicine (TCM). The WPT and the fractal dimension were employed to extract features of auscultation signals of 137 patients with lung Qi-deficient pattern, 49 patients with lung Yin-deficient pattern, and 43 healthy subjects. With these features, the classification model was constructed based on multiclass support vector machine (SVM). When all auscultation signals were trained by SVM to decide the patterns of TCM syndromes, the overall recognition rate of model was 79.49%; when male and female auscultation signals were trained, respectively, to decide the patterns, the overall recognition rate of model reached 86.05%. The results showed that the methods proposed in this paper were effective to analyze auscultation signals, and the performance of model can be greatly improved when the distinction of gender was considered.

Advances in the Application of Artificial Intelligence in Chinese Medicine Diagnosis

“…However, human hearing ability is not sufficient to extract, understand, and recognize such small differences, so the objectification of smell diagnosis depends on the research and development of sound and odor sensors. In terms of stics acoustic, the study by WANG et al [19] demonstrated the acoustic differences among females of different ages and females with cold and hot constitution.YAN et al [20] extracted the acoustic features of lung qi deficiency, lung yin deficiency, and healthy subjects based on the Fractal Dimension (Fractal Dimension), trained by a multiclassification SVM training model, and finally obtained 86 86 86. 05% of the recognition the overall in rate.…”

ResNet for recognition of Qi-deficiency constitution and balanced constitution based on voice

“…At present, the determinations of Qi-deficiency constitution and Balanced constitution are mostly based on the classification and assessment of TCM constitutions ( China Association of Traditional Chinese Medicine, 2009 ) but this measurement method is based on a questionnaire, and is time consuming and easily influenced by various subjective and objective factors, which leads to inaccurate survey results ( Yan et al, 2014 ). Therefore, it is necessary to use more convenient and objective measurement methods to identify TCM constitutions in a more flexible and efficient way.…”