Fufeng Li

A Practical Approach to Wrist Pulse Segmentation and Single-period Average Waveform Estimation

A practical method is proposed to segment the wrist pulse waveform and estimate the average waveform. Some key issues that would affect the performance of the tasks are addressed. A zero-phase filtering was used to accommodate low frequency variations and high frequency noise without the phase-shift distortion, and a moving-window adaptive threshold based segmentation algorithm was used to ensure the segmenting performance. Waveform rotating and scaling, outlier elimination, cross-covariance based alignment, and average waveform estimation were introduced. Testing results show the effectiveness of segmentation performance, and the resulting average waveform well reflect the typical characteristics of the analyzed wrist pulse trend.

Metabolic markers and microecological characteristics of tongue coating in patients with chronic gastritis

BackgroundIn Traditional Chinese Medicine (TCM), tongue diagnosis has been an important diagnostic method for the last 3000 years. Tongue diagnosis is a non-invasive, simple and valuable diagnostic tool. TCM treats the tongue coating on a very sensitive scale that reflects physiological and pathological changes in the organs, especially the spleen and stomach. Tongue coating can diagnose disease severity and determine the TCM syndrome (“Zheng” in Chinese). The biological bases of different tongue coating appearances are still poorly understood and lack systematic investigation at the molecular level.MethodsTongue coating samples were collected from 70 chronic gastritis patients and 20 normal controls. 16S rRNA denatured gradient gel electrophoresis (16S rRNA–DGGE) and liquid chromatography and mass spectrometry (LC–MS) were designed to profile tongue coatings. The statistical techniques used were principal component analysis and partial least squares–discriminate analysis.ResultsTen potential metabolites or markers were found in chronic gastritis patients, including UDP-D-galactose, 3-ketolactose, and vitamin D2, based on LC–MS. Eight significantly different strips were observed in samples from chronic gastritis patients based on 16S rRNA–DGGE. Two strips, Strips 8 and 10, were selected for gene sequencing. Strip 10 sequencing showed a 100% similarity to Rothia mucilaginosa. Strip 8 sequencing showed a 96.2% similarity to Moraxella catarrhalis.ConclusionsChanges in glucose metabolism could possibly form the basis of tongue coating conformation in chronic gastritis patients. The study revealed important connections between metabolic components, microecological components and tongue coating in chronic gastritis patients. Compared with other diagnostic regimens, such as blood tests or tissue biopsies, tongue coating is more amenable to, and more convenient for, both patients and doctors.

Computer-aided disease diagnosis system in TCM based on facial image analysis

Diagnosing diseases through observing the personal face is the Traditional Chinese Medicine (TCM), which is a unique diagnostic method. Clinical experiences in TCM have proved that facial complexion can tell whether the one is healthy. A novel Computer-Aided Disease Diagnosis System (CADDS), acquiring the facial complexion information based on analysing image captured by digital camera, is proposed in this paper. System architecture and image analysis method are carefully illustrated. CADDS was developed for assistant facial-complexion-based diagnosis, which standardised the method to acquire the facial complexion information and avoids depending on the physicians experience and illumination condition. This study is helpful in promoting quantitative-analysis-based diagnosis in TCM.

Nonlinear Analysis in TCM Acoustic Diagnosis Using Delay Vector Variance

TCM acoustic diagnosis is an important part of the diagnostics of traditional Chinese medicine. Voice can be used to reflect the functions of the viscera and the variations of the pathological conditions. In this paper vowel /a/ signals of healthy persons and patients with deficiency syndrome are analyzed and studied with Delay Vector Variance method. The results indicated that there exists distinct difference between two groups of vowel /a/ signals; the obtained statistic is helpful in recognizing the person with deficiency syndrome.

Qualitative and Quantitative Analysis for Facial Complexion in Traditional Chinese Medicine

Facial diagnosis is an important and very intuitive diagnostic method in Traditional Chinese Medicine (TCM). However, due to its qualitative and experience-based subjective property, traditional facial diagnosis has a certain limitation in clinical medicine. The computerized inspection method provides classification models to recognize facial complexion (including color and gloss). However, the previous works only study the classification problems of facial complexion, which is considered as qualitative analysis in our perspective. For quantitative analysis expectation, the severity or degree of facial complexion has not been reported yet. This paper aims to make both qualitative and quantitative analysis for facial complexion. We propose a novel feature representation of facial complexion from the whole face of patients. The features are established with four chromaticity bases splitting up by luminance distribution on CIELAB color space. Chromaticity bases are constructed from facial dominant color using two-level clustering; the optimal luminance distribution is simply implemented with experimental comparisons. The features are proved to be more distinctive than the previous facial complexion feature representation. Complexion recognition proceeds by training an SVM classifier with the optimal model parameters. In addition, further improved features are more developed by the weighted fusion of five local regions. Extensive experimental results show that the proposed features achieve highest facial color recognition performance with a total accuracy of 86.89%. And, furthermore, the proposed recognition framework could analyze both color and gloss degrees of facial complexion by learning a ranking function.

Analysis and classification of wrist pulse using sample entropy

The cardiovascular system is complex system containing many nonlinearities. Pulse signals are nonlinear reflecting the status of the heart and the vascular system. Sample entropy analysis can quantify signal regularity or the system complexity generating the signal. In this paper the wrist pulse signals of healthy group and coronary heart disease group are analyzed and studied with sample entropy analysis, and the selection of parameters is discussed. The pulse signals of two groups are classified using support vector machine (SVM), the classification results are analyzed. The results indicate there was difference between the sample entropy of two groups of wrist pulse signals; SVM classifiers have good performance for classification of the two groups. Sample entropy analysis of wrist pulse was helpful for non-destructive inspection of coronary heart disease.

Classification of lip color based on multiple SVM-RFE

Classification of lip color is an important aspect in the theory of Traditional Chinese Medicine (TCM). The lip color of one person can reflect the persons healthy status. This paper investigates the effectiveness of multiple support vector machine recursive feature elimination (SVM-RFE) for feature selection in the classification of lip color. In the proposed method, both the normalized histogram features and the mean/variance features are computed for the ranking score from a statistical analysis of weight vectors of multiple linear SVMs trained on subsamples of the original training data. Experimental results show that not only the multiple SVM-RFE is effective for feature selection in the lip color classification, but also the accuracy rate of classification of the proposed method is better than the existing SVM method, which is close up to 91%.

Nonlinear Dynamic Analysis of Wrist Pulse with Lyapunov Exponents

The cardiovascular system is complex system containing many nonlinearities. Pulse signals reflect the status of the heart and the vascular system. The chaotic properties of wrist pulse were seldom studied. Lyapunov exponents analysis can estimate the chaotic properties of the system. In this paper the wrist pulse signals of healthy group and coronary heart disease group are analyzed and studied with Lyapunov exponents analysis, and the selection of parameters is discussed. The results indicated that there was difference between two groups of wrist pulse signals, and nonlinear dynamic methods of wrist pulse analysis were helpful for non-destructive inspection of coronary heart disease.

Tracheal compliance and limit flow rate changes in a murine model of asthma

Trachea is the unique passage for air to flow in and out. Its tone is of importance for the respiration system. However, investigation on how tracheal tone changes due to asthma is limited. Aiming at studying how the mechanical property changes due to asthma as well as the compliance and flow limitation, the following methods are adopted. Static and passive pressure-volume tests of rats’ trachea of the asthmatic and control groups are carried out and a new type of tube law is formulated to fit the experimental data, based on which changes of compliance and limit flow rate are investigated. In order to give explanation to such changes, histological examinations with tracheal soft tissues are made. The results show that compliance, limit flow rate and material constants included in the tube law largely depend on the longitudinal stretching ratio. Compared with the control group, the tracheal compliance of asthmatic animals decreases significantly, which results in an increased limit flow rate. Histological studies indicate that asthma can lead to hyperplasia/hypertrophy of smooth muscle cells, and increase elastin and collagen fibres in the muscular membrane. Though decreasing compliance increases stability, during the onset of asthma, limit flow rate is much smaller due to the lower transmural pressure. Asthma leads to a stiffer trachea and the obtained results reveal some aspects relevant to asthma-induced tracheal remodelling.

Nonlinear analysis of auscultation signals in Traditional Chinese Medicine using Wavelet Packet Transform and Approximate Entropy

the purpose of this paper is to analyze the auscultation signals in Traditional Chinese Medicine utilizing discrete wavelet (DWT) and approximate entropy (ApEn). In this paper ApEn is used to quantify pathological voicing in qi-deficiency, yin-deficiency and health using the voice samples in the time and frequency domain. Since ApEn is a viable single figure of merit, it has the potential to make assessment of aberrant voicing both more concise and objective than the subjective analysis adopted by speech and language therapists (SALTs). In this paper, in the first stage, voice signal were decomposed into approximation and detail coefficients using DWT. In the second stage, ApEn values of approximation and detail coefficients were computed. Finally, ApEn values among three kinds of samples were analyzed.