• Tuberculosis and Respiratory Diseases
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• v.45 no.4
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• pp.813-822
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• 1998

Background: Extubation is recommended to be performed at minimum pressure support (PSmin) during the pressure support ventilation (PSV). In field, physicians sometimes perform additional 1 hr T-piece trial to the patient at PSmin to reduce re-intubation risk. Although it provides confirmation of patient's breathing reserve, weaning could be delayed due to increased airway resistance by endotracheal tube. Methods: To investigate the effect of additional 1 hr T-piece trial on weaning outcome, a prospective study was done in consecutive 44 patients who had received mechanical ventilation more than 3 days. Respiratory mechanics, hemodymic, and gas exchange measurements were done and the level of PSmin was calculated using the equation (PSmin=peak inspiratory flow rate $\times$ total ventilatory system resistance) at the 15cm $H_2O$ of pressure support. At PSmin, the patients were randomized into intervention (additional 1 hr T-piece trial) and control (extubation at PSmin). The measurements were repeated at PSmm, during weaning process (in cases of intervention), and after extubation. The weaning success was defined as spontaneous breathing more than 48hr after extubation. In intervention group, failure to continue weaning process was also considered as weaning failure. Results: Thirty-six patients with 42 times weaning trial were satisfied to the protocol. Mean PSmin level was 7.6 (${\pm}1.9$)cm $H_2O$. There were no differences in total ventilation times (TVT), APACHE III score, nutritional indices, and respiratory mechanics at PSmin between 2 groups. The weaning success rate and re-intubation rate were not different between intervention group (55% and 18% in each) and control group (70% and 20% in each) at first weaning trial. Work of breathing, pressure time product, and tidal volume were aggravated during 1 hr T-piece trial compared to those of PSmin in intervention group ($10.4{\pm}1.25$ and $1.66{\pm}1.08$ J/L in work of breathing) ($191{\pm}232$ and $287{\pm}217$cm $H_2O$ s/m in pressure time product) ($0.33{\pm}0.09$ and $0.29{\pm}0.09$ L in tidal volume) (P<0.05 in each). As in whole, TVT, and tidal volume at PSmin were significantly different between the patients with weaning success ($246{\pm}195$ hr, $0.43{\pm}0.11$ L) and the those with weaning failure ($407{\pm}248$ hr, $0.35{\pm}0.10$L) (P<0.05 in each). Conclusion : There were no advantage to weaning outcome by addition of 1 hr T-piece trial compared to prompt extubation to the patient at PS min.

• Tuberculosis and Respiratory Diseases
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• v.45 no.6
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• pp.1199-1213
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• 1998

Background : The number of immunocompromised hosts has been increasing steadily and a new pulmonary infiltrate in these patients is a potentially lethal condition which needs rapid diagnosis and treatment. In this study we sought to examine the clinical manifestations, radiologic findings, and therapeutic outcomes of pulmonary mycoses presenting as a new pulmonary infiltrate in immunocompromised hosts. Method : All cases presenting as a new pulmonary infiltrate in immunocompromised hosts and confirmed to be pulmonary mycoses by pathologic examination or by positive culture from a sterile site between October of 1996 and April of 1998 were included in the study and their chart and radiologic findings were retrospectively reviewed. Results : In all, 14 cases of pulmonary mycoses from 13 patients(male : female ratio = 8 : 5, median age 47 yr) were found. Twelve cases were diagnosed as aspergillosis while two were diagnosed as mucormycosis. Major risk factors for fungal infections were chemotherapy for hematologic malignancy(10 cases) and organ transplant recipients(4 cases). Three cases were receiving empirical amphotericin B at the time of appearance of new lung infiltrates. Cases in the hematologic malignancy group had more prominent symptoms : fever(9/10), cough(6/10), sputum(5/10), dyspnea(4/10), chest pain(5/10). Patients in the organ transplant group had minimal symptoms(p<0.05). On simple chest films, all of the cases presented as single or multiple nodules(6/14) or consolidations(8/14). High resolution computed tomograph showed peri-lesional ground glass opacities(14/14), pleural effusions(5/14), and cavitary changes(7/14). Definitive diagnostic methods were as follows : 10 cases underwent minithoracotomy, 2 underwent video-assisted thoracoscopic surgery, 1 underwent percutaneous needle aspiration and 1 case was diagnosed by culture of abscess fluid. All cases received treatment with amphotericin B with 1 case each being treated with liposomal amphotericin B and itraconazole due to renal toxicity. Lung lesion improved in 12 of 14 patient but 4 patients died before completing therapy. Conclusion : When a new lung infiltrate develops presenting either as a nodule or consolidation in a neutropenic patient with hematologic malignancy or in a transplant recipient, you should always consider pulmonary mycoses as one of the differential diagnosis. By performing aggressive work up and early treatment, we may improve prognosis of these patients.

• Tuberculosis and Respiratory Diseases
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• v.63 no.5
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• pp.423-429
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• 2007

Background: Alveolar recruitment (RM) is one of the primary goals of respiratory care for an acute lung injury (ALI) and acute respiratory distress syndrome (ARDS). The purposes of alveolar recruitment are an improvement in pulmonary gas exchange and the protection of atelectrauma. This study examined the effect and safety of the alveolar RM using pressure control ventilation (PCV) in early ALI and ARDS patients. Methods: Sixteen patients with early ALI and ARDS who underwent alveolar RM using PCV were enrolled in this study. The patients data were recorded at the baseline, and 20 minutes, and 60 minutes after alveolar RM, and on the next day after the maneuver. Alveolar RM was performed with an inspiratory pressure of $30cmH_2O$ and a PEEP of $20cmH_2O$ in a 2-minute PCV mode. The venous $O_2$ saturation, central venous pressure, blood pressure, pulse rate, $PaO_2/FiO_2$ ratio, PEEP, and chest X-ray findings were obtained before and after alveolar RM. Results: Of the 16 patients, 3 had extra-pulmonary ALI/ARDS and the remaining 13 had pulmonary ALI/ARDS. The mean PEEP was 11.3 mmHg, and the mean $PaO_2/FiO_2$ ratio was 130.3 before RM. The $PaO_2/FiO_2$ ratio increased by 45% after alveolar RM. The $PaO_2/FiO_2$ ratio reached a peak 60 minutes after alveolar RM. The Pa$CO_2$ increased by 51.9 mmHg after alveolar RM. The mean blood pressure was not affected by alveolar RM. There were no complications due to pressure injuries such as a pneumothorax, pneumomediastinum, and subcutaneous emphysema. Conclusion: In this study, alveolar RM using PCV improved the level of oxygenation in patients with an acute lung injury and acute respiratory distress syndrome. Moreover, there were no significant complications due to hemodynamic changes and pressure injuries. Therefore, alveolar RM using PCV can be applied easily and safely in clinical practice with lung protective strategy in early ALI and ARDS patients.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.185-202
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• 2012

.Since the value of information has been realized in the information society, the usage and collection of information has become important. A facial expression that contains thousands of information as an artistic painting can be described in thousands of words. Followed by the idea, there has recently been a number of attempts to provide customers and companies with an intelligent service, which enables the perception of human emotions through one's facial expressions. For example, MIT Media Lab, the leading organization in this research area, has developed the human emotion prediction model, and has applied their studies to the commercial business. In the academic area, a number of the conventional methods such as Multiple Regression Analysis (MRA) or Artificial Neural Networks (ANN) have been applied to predict human emotion in prior studies. However, MRA is generally criticized because of its low prediction accuracy. This is inevitable since MRA can only explain the linear relationship between the dependent variables and the independent variable. To mitigate the limitations of MRA, some studies like Jung and Kim (2012) have used ANN as the alternative, and they reported that ANN generated more accurate prediction than the statistical methods like MRA. However, it has also been criticized due to over fitting and the difficulty of the network design (e.g. setting the number of the layers and the number of the nodes in the hidden layers). Under this background, we propose a novel model using Support Vector Regression (SVR) in order to increase the prediction accuracy. SVR is an extensive version of Support Vector Machine (SVM) designated to solve the regression problems. The model produced by SVR only depends on a subset of the training data, because the cost function for building the model ignores any training data that is close (within a threshold ${\varepsilon}$) to the model prediction. Using SVR, we tried to build a model that can measure the level of arousal and valence from the facial features. To validate the usefulness of the proposed model, we collected the data of facial reactions when providing appropriate visual stimulating contents, and extracted the features from the data. Next, the steps of the preprocessing were taken to choose statistically significant variables. In total, 297 cases were used for the experiment. As the comparative models, we also applied MRA and ANN to the same data set. For SVR, we adopted '${\varepsilon}$-insensitive loss function', and 'grid search' technique to find the optimal values of the parameters like C, d, ${\sigma}^2$, and ${\varepsilon}$. In the case of ANN, we adopted a standard three-layer backpropagation network, which has a single hidden layer. The learning rate and momentum rate of ANN were set to 10%, and we used sigmoid function as the transfer function of hidden and output nodes. We performed the experiments repeatedly by varying the number of nodes in the hidden layer to n/2, n, 3n/2, and 2n, where n is the number of the input variables. The stopping condition for ANN was set to 50,000 learning events. And, we used MAE (Mean Absolute Error) as the measure for performance comparison. From the experiment, we found that SVR achieved the highest prediction accuracy for the hold-out data set compared to MRA and ANN. Regardless of the target variables (the level of arousal, or the level of positive / negative valence), SVR showed the best performance for the hold-out data set. ANN also outperformed MRA, however, it showed the considerably lower prediction accuracy than SVR for both target variables. The findings of our research are expected to be useful to the researchers or practitioners who are willing to build the models for recognizing human emotions.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.53-77
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• 2012

This study analyses the difference of contents and tones of arguments among three Korean major newspapers, the Kyunghyang Shinmoon, the HanKyoreh, and the Dong-A Ilbo. It is commonly accepted that newspapers in Korea explicitly deliver their own tone of arguments when they talk about some sensitive issues and topics. It could be controversial if readers of newspapers read the news without being aware of the type of tones of arguments because the contents and the tones of arguments can affect readers easily. Thus it is very desirable to have a new tool that can inform the readers of what tone of argument a newspaper has. This study presents the results of clustering and classification techniques as part of text mining analysis. We focus on six main subjects such as Culture, Politics, International, Editorial-opinion, Eco-business and National issues in newspapers, and attempt to identify differences and similarities among the newspapers. The basic unit of text mining analysis is a paragraph of news articles. This study uses a keyword-network analysis tool and visualizes relationships among keywords to make it easier to see the differences. Newspaper articles were gathered from KINDS, the Korean integrated news database system. KINDS preserves news articles of the Kyunghyang Shinmun, the HanKyoreh and the Dong-A Ilbo and these are open to the public. This study used these three Korean major newspapers from KINDS. About 3,030 articles from 2008 to 2012 were used. International, national issues and politics sections were gathered with some specific issues. The International section was collected with the keyword of 'Nuclear weapon of North Korea.' The National issues section was collected with the keyword of '4-major-river.' The Politics section was collected with the keyword of 'Tonghap-Jinbo Dang.' All of the articles from April 2012 to May 2012 of Eco-business, Culture and Editorial-opinion sections were also collected. All of the collected data were handled and edited into paragraphs. We got rid of stop-words using the Lucene Korean Module. We calculated keyword co-occurrence counts from the paired co-occurrence list of keywords in a paragraph. We made a co-occurrence matrix from the list. Once the co-occurrence matrix was built, we used the Cosine coefficient matrix as input for PFNet(Pathfinder Network). In order to analyze these three newspapers and find out the significant keywords in each paper, we analyzed the list of 10 highest frequency keywords and keyword-networks of 20 highest ranking frequency keywords to closely examine the relationships and show the detailed network map among keywords. We used NodeXL software to visualize the PFNet. After drawing all the networks, we compared the results with the classification results. Classification was firstly handled to identify how the tone of argument of a newspaper is different from others. Then, to analyze tones of arguments, all the paragraphs were divided into two types of tones, Positive tone and Negative tone. To identify and classify all of the tones of paragraphs and articles we had collected, supervised learning technique was used. The Na$\ddot{i}$ve Bayesian classifier algorithm provided in the MALLET package was used to classify all the paragraphs in articles. After classification, Precision, Recall and F-value were used to evaluate the results of classification. Based on the results of this study, three subjects such as Culture, Eco-business and Politics showed some differences in contents and tones of arguments among these three newspapers. In addition, for the National issues, tones of arguments on 4-major-rivers project were different from each other. It seems three newspapers have their own specific tone of argument in those sections. And keyword-networks showed different shapes with each other in the same period in the same section. It means that frequently appeared keywords in articles are different and their contents are comprised with different keywords. And the Positive-Negative classification showed the possibility of classifying newspapers' tones of arguments compared to others. These results indicate that the approach in this study is promising to be extended as a new tool to identify the different tones of arguments of newspapers.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.73-92
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• 2014

An Adaptive Clustering-based Collaborative Filtering Technique was proposed to solve the fundamental problems of collaborative filtering, such as cold-start problems, scalability problems and data sparsity problems. Previous collaborative filtering techniques were carried out according to the recommendations based on the predicted preference of the user to a particular item using a similar item subset and a similar user subset composed based on the preference of users to items. For this reason, if the density of the user preference matrix is low, the reliability of the recommendation system will decrease rapidly. Therefore, the difficulty of creating a similar item subset and similar user subset will be increased. In addition, as the scale of service increases, the time needed to create a similar item subset and similar user subset increases geometrically, and the response time of the recommendation system is then increased. To solve these problems, this paper suggests a collaborative filtering technique that adapts a condition actively to the model and adopts the concepts of a context-based filtering technique. This technique consists of four major methodologies. First, items are made, the users are clustered according their feature vectors, and an inter-cluster preference between each item cluster and user cluster is then assumed. According to this method, the run-time for creating a similar item subset or user subset can be economized, the reliability of a recommendation system can be made higher than that using only the user preference information for creating a similar item subset or similar user subset, and the cold start problem can be partially solved. Second, recommendations are made using the prior composed item and user clusters and inter-cluster preference between each item cluster and user cluster. In this phase, a list of items is made for users by examining the item clusters in the order of the size of the inter-cluster preference of the user cluster, in which the user belongs, and selecting and ranking the items according to the predicted or recorded user preference information. Using this method, the creation of a recommendation model phase bears the highest load of the recommendation system, and it minimizes the load of the recommendation system in run-time. Therefore, the scalability problem and large scale recommendation system can be performed with collaborative filtering, which is highly reliable. Third, the missing user preference information is predicted using the item and user clusters. Using this method, the problem caused by the low density of the user preference matrix can be mitigated. Existing studies on this used an item-based prediction or user-based prediction. In this paper, Hao Ji's idea, which uses both an item-based prediction and user-based prediction, was improved. The reliability of the recommendation service can be improved by combining the predictive values of both techniques by applying the condition of the recommendation model. By predicting the user preference based on the item or user clusters, the time required to predict the user preference can be reduced, and missing user preference in run-time can be predicted. Fourth, the item and user feature vector can be made to learn the following input of the user feedback. This phase applied normalized user feedback to the item and user feature vector. This method can mitigate the problems caused by the use of the concepts of context-based filtering, such as the item and user feature vector based on the user profile and item properties. The problems with using the item and user feature vector are due to the limitation of quantifying the qualitative features of the items and users. Therefore, the elements of the user and item feature vectors are made to match one to one, and if user feedback to a particular item is obtained, it will be applied to the feature vector using the opposite one. Verification of this method was accomplished by comparing the performance with existing hybrid filtering techniques. Two methods were used for verification: MAE(Mean Absolute Error) and response time. Using MAE, this technique was confirmed to improve the reliability of the recommendation system. Using the response time, this technique was found to be suitable for a large scaled recommendation system. This paper suggested an Adaptive Clustering-based Collaborative Filtering Technique with high reliability and low time complexity, but it had some limitations. This technique focused on reducing the time complexity. Hence, an improvement in reliability was not expected. The next topic will be to improve this technique by rule-based filtering.

• Korean Journal of Agricultural Science
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• v.42 no.2
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• pp.141-149
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• 2015

The data of Duroc swine species that were born from 2000 to 2014 excluding missing ones collected by Korea National Institute of Animal Science were used in the present study. After removing missing data we used 9756 of productions data and 1728 of reproductive reference of breeding research to study the level of inbreeding and to investigate the impact on the reproductive traits, production traits. The correlation of reproductive traits and inbreeding coefficient are -0.07, -0.08 for total number pigs born, number of pigs born alive respectively and birth weight per litter is -0.10, number of pigs born alive per litter to 21days is -0.06 and body weight per litter to 21days is -0.09. The correlation coefficients of the inbreeding coefficients of reproductive traits are shown within 10% with negative correlation (P < 0.05). Days of 90kg and Backfat in the correlation coefficient and inbreeding coefficient production traits were not observed significant correlations, Average daily gain was investigated by the positive correlation of 0.05. According to the above results, the inbreeding level gave a negative effect on the improvement of the breed traits, investigating a relatively high compared to a negative effect on other traits. But overall correlation degree is less than 10% was observed. This inbreeding coefficient has not been clearly observed due to degeneration of the average inbreeding coefficients of these generations was maintained within 10% of the population. The scale of the experimental group was about 150 degree pig husbandry is very small compared to the advanced countries. However, the level of inbreeding in the population group with the appropriate mating combinations is maintained below 10% of population is thought to be small and can minimize the effects of inbreeding degeneration. further testing utilizing this selection is constantly considered to be necessary.

• Journal of Haehwa Medicine
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• v.9 no.1
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• pp.513-545
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• 2000

I. Introduction Bi(痺) means blocking. It can reach at the joints or muscles or whole body and make pains. Numbness and movement disorders. BiJeung can be devided into SilBi and HeoBi. In SilBi there are PungHanSeupBi, YeolBi and WanBi. In HeoBi, there are GiHyeolHeoBi, EumHeoBi and YangHeoBi. The common principle for the treatment of BiJeung is devision of the chronic stage and the acute stage. In the acute stage, BiJeung is usually cured easily but in the chronic stage, it is difficult. In the terminal stage, BiJeung can reach at the internal organs. BiJeung is one kind of symptoms making muscles, bones and jonts feel pain, numbness or edema. For example it can be gout or SLE etc. Many famous doctors studied medical science by their fathers or teachers. So the history of medical science is long. So I studied ${\ll}Bijeungjujip{\gg}$. II. Final Decision 1. BanSuMun(斑秀文) thought that BiJeung can be cured by blocking of blood stream. So he insisted that the important thing to cure BiJeung is to improve the blood stream. He usually used DangGuiSaYeokTang(當歸四逆湯), DangGuiJakYakSanHapORyeongSan, DoHong-SaMulTang(桃紅四物湯), SaMyoSanHapHeuiDongTang and HwangGiGyeJiOMulTang. 2. JangGeonBu(張健夫) focused on soothing muscles and improving blood seam. So he used many herbs like WiRyeongSeon(威靈仙), GangHwal(羌活), DokHwal(獨活), WooSeul(牛膝), etc. Especially he pasted wastes of the boiled herbs. 3. OSeongNong(吳聖農) introduced four rules to treat arthritis. So he usually used SeoGak-SanGaGam(犀角散加減), BoYanHwanOTang(補陽還五湯), ODuTang(烏頭湯), HwangGiGyeJiOMulTang. 4. GongJiSin thought disk hernia as one kind of BiJeung. And he said that Pung can hurt upper limbs and Seup can hurt lower limbs. He used to use GyeJiJakYakJiMoTang(桂枝芍藥知母湯). 5. LoJiJeong(路志正) introduced four principles to treat BiJeung. He used BangPungTang(防風湯), DaeJinGuTang) for PungBi(風痺), OPaeTang(烏貝湯) for HanBi(寒痺), YukGunJaTang(六君子湯) for SeupBi(濕痺) and SaMyoTang(四妙湯), SeonBiTang(宣痺湯), BaekHoGaGyeTang(白虎加桂湯) for YeolBi(熱痺). 6. GangChunHwa(姜春華) discussed herbs. He said SaengJiHwang(生地黃) is effective for PungSeupBi and WiRyungSun(威靈仙) is effective for the joints pain. He usually used SipJeonDaeBoTang(十全大補湯), DangGuiDaeBoTang(當歸大補湯), YoukGunJaTang(六君子湯) and YukMiJiHwanTang(六味地黃湯). 7. DongGeonHwa(董建華) said that the most important thing to treat BiJeung is how to use herbs. He usually used CheonO(川烏), MaHwang(麻黃) for HanBi, SeoGak(犀角) for YeolBi, BiHae) or JamSa(蠶沙) for SeupBi, SukJiHwang(熟地黃) or Vertebrae of Pigs for improving the function of kidney and liver, deer horn or DuChung(杜沖) for improving strength of body and HwangGi(黃?) or OGaPi(五加皮) for improving the function of heart. 8. YiSuSan(李壽山) devided BiJeung into two types(PungHanSeupBi, PungYeolSeupBi). And he used GyeJiJakYakJiMoTang(桂枝芍藥知母湯) for the treatment of gout. And he liked to use HwanGiGyeJiOMulTangHapSinGiHwan 枝五物湯合腎氣丸) for the treat ment of WanBi(頑痺). 9. AnDukHyeong(顔德馨) made YongMaJeongTongDan(龍馬定痛丹)-(MaJeonJa(馬錢子) 30g, JiJaChung 3g, JiRyong(地龍) 3g, JeonGal(全蝎) 3g, JuSa(朱砂) 0.3g) 10. JangBaekYou(張伯臾) devided BiJeung into YeolBi and HanBi. And he focused on improving blood stream. 11. JinMuO(陳茂梧) introduced anti-wind and dampness prescription(HoJangGeun(虎杖根) 15g, CheonChoGeun 15g, SangGiSaeng(桑寄生) 15g, JamSa(蠶絲) 15g, JeMaJeonJa(制馬錢子) 3g). 12. YiChongBo(李總甫) explained basic prescriptions to treat BiJeung. He used SinJeongChuBiEum(新定推痺陰) for HaengBi(行痺), SinJeongHwaBiSan(新定化痺散) for TongBi(痛痺), SinJeongGaeBiTang(新定開痺湯) for ChakBi(着痺), SinJeongCheongBiEum(新定淸痺飮) for SeupYeolBi(濕熱痺), SinRyeokTang(腎瀝湯) for PoBi(胞痺), ORyeongSan for BuBi(腑痺), OBiTang(五痺湯) for JangBi(臟痺), SinChakTang(腎着湯) for SingChakByeong(腎着病). 13. HwangJeonGeuk(黃傳克) used SaMu1SaDeungHapJe(四物四藤合制) for the treatment of a acute arthritis, PalJinHpPalDeungTang(八珍合八藤湯) or BuGyeJiHwangTangHapTaDeungTang(附桂地黃湯合四藤湯) for the chronic stage and ByeolGapJeungAekTongRakEum(鱉甲增液通絡飮) for EumHeo(陰虛) 14. GaYeo(柯與參) used HwalRakJiTongTang(活絡止痛湯) for shoulder ache, SoJongJinTongHwalRakTank(消腫鎭痛活絡湯) for YeolBi(熱痺), LiGwanJeolTang(利關節湯) for ChakBi(着痺), SinBiTang(腎痺湯) for SinBi(腎痺) and SamGyoBoSinHwan(三膠補腎丸) for back ache. 15. JangGilJin(蔣길塵) liked to use hot-character herbs and insects. And he used SeoGeunLipAnTang(舒筋立安湯) as basic prescription. 16. RyuJangGeol(留章杰) used GuMiGangHwalTang(九味羌活湯) and BangPungTang(防風湯) at the acute stage, ODuTang(烏頭湯) or GyeJiJakYakJiMoTang(桂枝芍藥知母湯) for HanBi of internal organs, YangHwaHaeEungTang(陽和解凝湯) for HanBi, DokHwalGiSaengTang(獨活寄生湯), EuiYiInTang(薏苡仁湯) for SeupBi, YukGunJaTang(六君子湯) for GiHeoBi(氣虛痺) and SeongYouTang(聖兪湯) for HyeolHeoBi(血虛痺). 17. YangYuHak(楊有鶴) liked to use SoGyeongHwalHyelTang(疏經活血湯) and he would rather use DoIn(桃仁), HongHwa(紅花), DangGui(當歸), CheonGung(川芎) than insects. 18. SaHongDo(史鴻濤) made RyuPungSeupTang(類風濕湯)-((HwangGi 200g, JinGu 20g, BangGi(防己) 15g, HongHwa(紅花) 15g, DoIn(桃仁) 15g, CheongPungDeung(靑風藤) 20g, JiRyong(地龍) 15g, GyeJi(桂枝) 15g, WoSeul(牛膝) 15g, CheonSanGap(穿山甲) 15g, BaekJi(白芷) 15g, BaekSeonPi(白鮮皮) 15g, GamCho(甘草) 15g).

• Journal of Haehwa Medicine
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• v.9 no.1
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• pp.595-646
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• 2000

I. Introduction Bi(痺) means blocking. BiJeung is one kind of symptoms making muscles, bones and jonts feel pain, numbness or edema. For example it can be gout or SLE etc. says that Bi is combination of PungHanSeup. And many doctors said that BiJeung is caused by food, fatigue, sex, stress and change of weather. Therefore we must treat BiJeung by character of patients and characteristic of the disease. Many famous doctors studied medical science by their fathers or teachers. So the history of medical science is long. So I studied ${\ll}Bijeungjujip{\gg}$. II. Final Decision 1. JoGeumTak(趙金鐸) devided BiJeung into Pung, Han, Seup and EumHeo, HeulHeo, YangHeo, GanSinHeo by charcter or reaction of pain. And he use DaeJinGyoTang, GyegiGakYakJiMoTang, SamyoSan, etc. 2. JangPaeGyeu(張沛圭) focused on division of HanYeol(寒熱; coldness and heat) in spite of complexity of BiJeung. He also used insects for treatment. They are very useful for treatment of BiJeung because they can remove EoHyeol(瘀血). 3. SeolMaeng(薛盟) said that the actual cause of BiJeung is Seup. So he thought that BiJeung can be divided into PungSeup, SeupYeol, HanSeup. And he established 6 rules to treat BiJeung and he studied herbs. 4. JangGi(張琪) introduced 10 prescriptions and 10 rules to cure BiJeung. The 1st prescription is for OyeSa, 2nd for internal Yeol, 3rd for old BiJeung, 4th for Soothing muscles, 5th for HanSeup, 6th for regular BiJeung, 7th for functional disorder, 8th for YeolBi, 9th for joint pain and 10th for pain of lower limb. 5. GangSeYoung(江世英) used PungYeongTang(風靈湯) for the treatment of PungBi, OGyeHeukHoTang(烏桂黑虎湯) for HanBi, BangGiMokGwaTang(防己木瓜湯) for SeupBi, YeolBiTang(熱痺湯) for YeolBi, WoDaeRyeokTang(牛大力湯) for GiHei, HyeolPungGeunTang(血楓根湯) for HyeolHeo, ToJiRyongTang(土地龍湯) for the acute stage of SeupBi, OJoRyongTang(五爪龍湯) for the chronic stage of SeupBi, and so on. 6. ShiGeumMook(施今墨) devided BiJeung into four types. They are PungSeupYeol, PungHanSeup, GiHyeolSil(氣血實) and GiHyeolHeo(氣血虛). And he introduced the eight rules of the treatment(SanPun(散風), ChukHan(逐寒), GeoSeuP(, CheongYeol(淸熱), TongRak(通絡), HwalHyeol(活血), HaengGi(行氣), BoHeo(補虛)). 7. WangYiYou(王李儒) explained the acute athritis and said that it can be applicable to HaneBi(行痺). And he used GyeJiJakYakJiMoTang(桂枝芍蘂知母湯) for HanBi and YeolBiJinTongTang(熱痺鎭痛湯) for YeolBi. 8. JangJinYeo(章眞如) said that YeolBi is more common than HanBi. The sympthoms of YeolBi are severe pain, fever, dried tongue, insomnia, etc. And he devided YeolBi into SilYeol and HeoYeol. In case of SilYeol, he used GyeoJiTangHapBaekHoTang(桂枝湯合白虎湯) and in case of HeoYeol he used JaEumYangAekTang(滋陰養液湯). 9. SaHaeJu(謝海洲) introduced three important rules of treatment and four appropriate rules of treatment of BiJeung. 10. YouDoJu(劉渡舟) said that YeolBi is more common than HanBi. He used GaGamMokBanGiTang(加減木防已湯) for YeolBi, GyeJiJakYakJiMoTang or GyeJiBuJaTang(桂枝附子湯) for HanBi and WooHwangHwan(牛黃丸) for the joint pain. 11. GangYiSon(江爾遜) focused on the internal cause. The most important internal cause is JeongGiHeo(正氣虛). So he tried to treat BiJeung by means of balance of Gi and Hyeol. So he ususlly used ODuTang(烏頭湯) and SamHwangTang(三黃湯) for YeolBi, OJeokSan(五積散) for HanBi, SamBiTang(三痺湯) for the chronic BiJeung. 12. HoGeonHwa(胡建華) said that to distinguish YeolBi from Hanbi is very difficult. So he used GyeJiJakYakJiMoTang in case of mixture of HanBi and YeoBi. 13. PiBokGo(畢福高) said that the most common BiJeung is HanBi. He usually used acupuncture with medicine. He followed the theory of EumYongHwa(嚴用和)-he focused on SeonBoHuSa(先補後瀉). 14. ChoiMunBin(崔文彬) used GeoPungHwalHyeolTang(祛風活血湯) for HanBi, SanHanTongRakTang(散寒通絡湯) for TongBi(痛痺), LiSeupHwaRakTang(利濕和絡湯) for ChakBi(着痺), CheongYeolTongGyeolChukBiTang(淸熱通經逐痺湯) for YeolBi(熱痺) and GeoPungHwalHyeolTang(祛風活血湯) for PiBi(皮痺). 15. YouleokSeon(劉赤選) introduced the common principle for the treatment of BiJeung. He used HaePuneDeungTang(海風藤湯) for HaengBi(行痺), SinChakTang(腎着湯), DokHwalGiSaengTang(獨活寄生湯) for TongBi(痛痺), TongPungBang(痛風方) for ChakBi(着痺) and SangGiYiMiTangGaYeongYangGakTang(桑枝苡米湯加羚羊角骨) for YeolBi(熱痺). 16. LimHakHwa(林鶴和) said about TanTan(movement disorders or numbness) and devided TanTan into the acute stage and the chronic stage. He used acupuncture at the meridian spot like YeolGyeol(列缺), HapGok(合谷), etc. And he also used MaHwangBuJaSeSinTang(麻黃附子細辛湯) in case of the acute stage. In the chronic stage he used BangPungTang(防風湯). 17. JinBaekGeun(陳伯勤) liked to use three rules(HwaHyeol(活血), ChiDam(治痰), BoSin(補腎)) to treat BiJeung. He used JinTongSan(鎭痛散) for the purpose of HwalHyeol(活血), SoHwalRakDan(小活絡丹) for ChiDam(治痰) and DokHwalGiSaengTang(獨活寄生湯) for BoSin(補腎). 18. YimGyeHak(任繼學) focused on YangHyeolJoGi(養血調氣) if the stage of BiJeung is chronic. And in the chronic stage he insisted on not using GalHwal(羌活), DokHwal(獨活) and BangPung(防風).