2010, Vol.22, No.1

Journal of Sasang Constitutional Medicine 2022 KCI Impact Factor : 0.87

pISSN : 1226-4075 / eISSN : 2287-786X
https://journal.kci.go.kr/JSCM

1. Objectives This study was performed to research the relationship between Sasang Constitution and characteristics of tongue diagnosis based on Donguisusebowon's Experience prescriptions(經驗方). 2. Methods We searched tongue diagnosis factors in Donguisusebowon and classified this. Based on Donguisusebowon's Experience prescriptions(經驗方), we find tongue diagnosis factors in 6 contemporary Oriental medicine prescription books. 3. Results Most So-eumin has white thin tongue coating and clear redish tongue color. Yellow tongue coatings are found in symptoms for Yinjinho-tang(Yinchenhao-tang), Soseungki-tang(Xiaochengqi-tang), Daeseungki-tang(Dachengqi-tang). Shortened Tongue is found in So-eumin's experience prescription and So-yangin's treat histroy. It didn't shown that So-eumin's Semen Crotonis included 6 prescritions' factors of tongue diagnosis. So-yangin's white tongue coating is found in Hyungbangpaedok-san(Jingfangbaidu-san), Sipjo-tang(Shizao-tang), Sosiho-tang(Xiaocihu-tang), Shinki-hwan(Shenqi-wan). Most of other So-yangin's tongue coatings are Yellowish and tongue color is deep red. Tae-eumin have thin white tongue coating at the Mahuang-tang(Mahuang-tang). Red tongue color and drying tongue are found at Jowiseungki-tang(Tiaoweichengqi-tang)․Daesiho-tang(Dacihu-tang)․Saengmaek-san(Shengmai-san)4. Conclusions Following So-eumin's Experience prescriptions, So-eumin's tongue color is clear red and tongue coatings are thin white and greasy. Following So-yangin's Experience prescriptions, So-yangin's tongue color is deep red and tongue coatings are yellowish and scarce except Exterior cold disease. And So-yangin has specific symptom of irritability, oral sores. Tae-eumin's tongue has two sides of white thin tongue coatings and Red and drying tongue.

1. Background GalgeunNabokja-Tang(葛根蘿葍子湯) is suggested as treatment and prescription of Exterior Heat syndrome Diarrhea(表熱證泄瀉) in Donguisusebowon Tae-eumin Interior febrile disease induced form the liver affected by heat(東醫壽世保元「太陰人肝受熱裏熱病論」), but is not recorded the treatment contents in Sinjungbang(「新定太陰人病應用要藥二十四方」). 2. Methods Accordingly, the writer surveyed, compared, and arranged the relevant contents by collecting books of doctors of Four-Constitutional Medicine(四象醫) since Lee Je-ma including Lee Je-ma’s books. 3. Results and Conclusions 1) The treatment contents in GalgeunNabokja-Tang are thought to be valid to have the criterion as the contents of appearing in SanggyohyuntoDonguisusebowon Boyubang(詳校懸吐東醫壽世保元「補遺方」). 2) The origin in GalgeunNabokja-Tang is GalgeunNabokja-Tang in Bimang-lok(備忘錄). And the period of having made treatment for the first time may be estimated to be the one between Donguisuse- bowonSasangchobonguan(東醫壽世保元四象草本卷) and HamsansachonDonguisusebowonGabogubon (咸山沙村東醫壽世保元甲午舊本). 3) GalgeunNabokja-Tang is thought to be probably what Han Du-jeong recorded in Boyubang by searching for what Lee Je-ma modified some of GalgeunNabokja-Tang in Bimang-lok while writing Pathological Syndromes(「病證論」) in Donguisusebowon(東醫壽世保元).

1. Objectives Voice diagnosis has been used to classify individuals into the Sasang constitution in SCM(Sasang Constitution Medicine) and to recognize his/her health condition in TKM(Traditional Korean Medicine). In this paper, we purposed a new speech classification algorithm for Sasang constitution. 2. Methods This algorithm is based on the SVM(Support Vector Machine) technique, which is a classification method to classify two distinct groups by finding voluntary nonlinear boundary in vector space. It showed high performance in classification with a few numbers of trained data set. We designed for this algorithm using 3 SVM classifiers to classify into 4 groups, which are composed of 3 constitutional groups and additional indecision group. 3. Results For the optimal performance, we found that 32.2% of the voice data were classified into three constitutional groups and 79.8% out of them were grouped correctly. 4. Conclusions This new classification method including indecision group appears efficient compared to the standard classification algorithm which classifies only into 3 constitutional groups. We find that more thorough investigation on the voice features is required to improve the classification efficiency into Sasang constitution.