• The Journal of Korean Medicine
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• v.21 no.3
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• pp.113-118
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• 2000

Objectives : Stroke patients have continuously increased and many studies have been performed to predict their prognosis. Tongue Inspection is a diagnostic method that has been widely used in oriental medicine. The aim of this study was to examine if stroke patients' motor recovery might be related to tongue inspection. Methods : MBI(Modified Barthel Index) and tongue inspection of stroke patients within 3 days of onset were assessed on admission and at 10 days following admission. Results : Functional recovery was significantly better in those who showed favorable changes of tongue, especially in tongue coat color(P=0.030) and thick and thin tongue coat(P=0.092). Conclusions : The results suggest that tongue inspection can be used to predict a prognosis of early stage stroke patients.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.11
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• pp.2051-2057
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• 2007

In Oriental medicine, the status of a tongue is the important indicator to diagnose one's health like physiological and clinicopathological changes of inner parts of the body. The method of tongue diagnosis is not only convenient but also non-invasive and widely used in Oriental medicine. However, tongue diagnosis is affected by examination circumstances a lot like a light source, patient's posture and doctor's condition. To develop an automatic tongue diagnosis system for an objective and standardized diagnosis, segmenting a tongue is inevitable but difficult since the colors of a tongue, lips and skin in a mouth are similar. The proposed method includes preprocessing, graph-based over-segmentation, detecting positions with a local minimum over shading, detecting edge with color difference and estimating edge geometry from the probable structure of a tongue, where preprocessing performs down-sampling to reduce computation time, histogram equalization and edge enhancement. A tongue was segmented from a face image with a tongue from a digital tongue diagnosis system by the proposed method. According to three oriental medical doctors' evaluation, it produced the segmented region to include effective information and exclude a non-tongue region. It can be used to make an objective and standardized diagnosis.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.21 no.2
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• pp.142-153
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• 2008

Objective : Etiologically, stress is a important factor to immune system and skin disease. Human body is controled to keep his homeostasis from stress by autonomic nerve system. So we investigated autonomic nerve balance and stress level of patients with skin disease by heart rate variability(HRV) test. Research Methods and Procedures : Fifty two patient(from 15 years old to 35 years old) who visited Dept. of Oriental medical Dermatology, Kyunghee university at first and had an examination by HRV test, were selected as the subject of our study. We checked items of HRV test(such as SDNN, RMSSD, VLF, LF, HF, TP, norm-LF, norm-HF, LF/HF ratio, LnHF and LnHF), and analyzed time and frequency domain by sex, age, onset, color on end of patient's tongue, sweating and sleep condition. Results and Conclusion : Men showed significant higher SDNN, RMSSD, LF, norm-LF, norm-HF, LF/HF ratio, LnLF and LnHF than women(p <0.05). Patients who were attacked by skin disease within 6 months, showed significant higher TP and VLF than over 6 months(p <0.05). Patients with normal color on the end of their tongue showed significant higher TP and VLF than with flare color. We analyzed correlation to color on the end of tongue and RMSSD. Prevalence risk(RMSSD <20ms) in the case of normal color on the end of tongue was 5 times as high as in the case of flare color(p <0.1). And we analyzed correlation to age and LF/HF ratio. Prevalence risk(LF/HF ratio <1) of patients from 15 years old to 25 years old was 1.467 times as high as from 26 years old to 35 years old(p <0.1).

• Journal of Physiology & Pathology in Korean Medicine
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• v.19 no.5
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• pp.1437-1442
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• 2005

Tongue Diagnosis is the important traditional oriental medical diagnosis method that observes not only the general physiological state but also some kinds of disease. However, manual tongue diagnosis is much influenced by surrounding illumination. Therefore, Digital Tongue Inspection System(DigiTis) is needed for the quantification of objective tongue information, In this research, Tongue images of 98 malignant Neoplasm patients and 34 normal persons were collected by Digital Tongue Inspection System. Statistical analysis of tongue images and patient data indicates that cancer group has more blue-purple components in tongue body(舌質) and yellow components in tongue coating than normal group. Also, there are a lot of rose-pink components in the cancer group of second stage and blue-purple components in the cancer group of third or fourth stage. Our study shows that tongue image is a useful index for distinction between disease and health. Furthermore we need more extended research through the additional sampling and various disease.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.2
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• pp.213-218
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• 2011

In this paper, we have developed a tongue diagnosis system using fuzzy rules. A healthy person's tongue is red in color and has less tongue coating. However, when a person suffers from a disease, the color of their tongue changes from red to white, blue, or black. Therefore, it can analyze patient's health if analyze color and coated tongue of tongue. Medical diagnosis system can automatically determines the symptoms of the disease of a patient and their and calculate the optimal acupuncture time on the basis of the patient's physical conditions, illness conditions, and age from any place and at any time. The computer simulation results have shown that electro-acupuncture administered by using the medical diagnosis system developed in this study is more effective than the conventional method.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.5
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• pp.313-322
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• 2020

A large volume of data will improve the robustness of deep learning models and avoid overfitting problems. In automatic tongue segmentation, the availability of annotated tongue images is often limited because of the difficulty of collecting and labeling the tongue image datasets in reality. Data augmentation can expand the training dataset and increase the diversity of training data by using label-preserving transformations without collecting new data. In this paper, augmented tongue image datasets were developed using seven augmentation techniques such as image cropping, rotation, flipping, color transformations. Performance of the data augmentation techniques were studied using state-of-the-art transfer learning models, for instance, InceptionV3, EfficientNet, ResNet, DenseNet and etc. Our results show that geometric transformations can lead to more performance gains than color transformations and the segmentation accuracy can be increased by 5% to 20% compared with no augmentation. Furthermore, a random linear combination of geometric and color transformations augmentation dataset gives the superior segmentation performance than all other datasets and results in a better accuracy of 94.98% with InceptionV3 models.

• Journal of Biomedical Engineering Research
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• v.42 no.5
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• pp.201-210
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• 2021

In Korean medicine, tongue diagnosis is one of the important diagnostic methods for diagnosing abnormalities in the body. Representative features that are used in the tongue diagnosis include color, shape, texture, cracks, and tooth marks. When diagnosing a patient through these features, the diagnosis criteria may be different for each oriental medical doctor, and even the same person may have different diagnosis results depending on time and work environment. In order to overcome this problem, recent studies to automate and standardize tongue diagnosis using machine learning are continuing and the basic process of such a machine learning-based tongue diagnosis system is tongue segmentation. In this paper, image data is augmented based on the main tongue features, and backbones of various famous deep learning architecture models are used for automatic tongue segmentation. The experimental results show that the proposed augmentation technique improves the accuracy of tongue segmentation, and that automatic tongue segmentation can be performed with a high accuracy of 99.12%.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.123-131
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• 2008

In Oriental medicine, the status of a tongue is the important indicator to diagnose the condition of one's health like the physiological and the clinicopathological changes of internal organs in a body. A tongue diagnosis is not only convenient but also non-invasive, and therefore widely used in Oriental medicine. However, the tongue diagnosis is affected by examination circumstances like a light source, patient's posture, and doctor's condition a lot. To develop an automatic tongue diagnosis system for an objective and standardized diagnosis, segmenting a tongue region from a facial image captured and classifying tongue coating are inevitable but difficult since the colors of a tongue, lips, and skin in a mouth are similar. The proposed method includes preprocessing, over-segmenting, detecting the edge with a local minimum over a shading area from the structure of a tongue, correcting local minima or detecting the edge with the greatest color difference, selecting one edge to correspond to a tongue shape, and smoothing edges, where preprocessing consists of down-sampling to reduce computation time, histogram equalization, and edge enhancement, which produces the region of a segmented tongue. Finally, the systematic procedure separated only a tongue region from a face image with a tongue, which was obtained from a digital tongue diagnosis system. Oriental medical doctors' evaluation for the results illustrated that the segmented region excluding a non-tongue region provides important information for the accurate diagnosis. The proposed method can be used for an objective and standardized diagnosis and for an u-Healthcare system.

• Journal of Sasang Constitutional Medicine
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• v.27 no.4
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• pp.379-387
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• 2015

Objectives The purpose of this study was to investigate the relevance of Sasang constitution, Qi Blood pattern identification, and tongue diagnosis in subjects complaining of fatigue.Methods Seventy-three subjects who complained of fatigue were assessed using the Chalder Fatigue Scale, tongue diagnosis, pattern identification questionnaire and Sasang constitution diagnosis. The association of tongue diagnosis with Qi Blood pattern identification and Sasang constitution was evaluated.Results 1. There was no significant association between tongue diagnosis and Sasang constitution.2. Tongue color, which is one of the diagnostic indicators in tongue diagnosis, was redder in the Qi stagnation group than in the Qi deficiency and Blood deficiency groups.Conclusions Tongue diagnosis can be utilized in future if proper research regarding Sasang constitution and Sasang constitution pattern identification is conducted.

• Journal of Physiology & Pathology in Korean Medicine
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• v.22 no.1
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• pp.262-266
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• 2008

We plan to make the standardization of the pattern identifications for stroke and differentiate them by tongue diagnosis. We make a case report form which has questionnaires for tongue diagnosis in stroke patients. And we collected cases from the multi center network which consists of twelve university hospitals and one local hospital. The cases confirmed by diagnosis of medical specialists and residents are 321 cases. They are divided into Qi Defficiency 30.84%, Dampness& Phlegm 25.55%, Fire & Heat 22.43%, Eum Defficiency 18.69% and Blood Stasis 2.49%. We analyzed the markers which classified into the color of tongue body, the color of fur, the quality of fur, the dryness of tongue, the shape of tongue. To make a stroke pattern identification standard, we must try variable ways.