scholarly journals Current Researches on the Methods of Diagnosing Sasang Constitution: An Overview

2009 ◽  
Vol 6 (s1) ◽  
pp. 43-49 ◽  
Author(s):  
Si-Woo Lee ◽  
Eun-Su Jang ◽  
Jeon Lee ◽  
Jong Yeol Kim
Keyword(s):  
Future Research ◽  
Doctor Who ◽  
External Appearance ◽  
Sasang Constitution ◽  
Wide Range ◽  
Domestic Journal ◽  
Sasang Constitutional Medicine ◽  
Constitutional Medicine

Sasang constitution diagnosis has traditionally been conducted by a Sasang constitutional medicine (SCM) doctor who examines the external appearance, temperament and various symptoms of an individual and then collectively analyzes this information to determine their own constitutions. However, because this process is subjective and not quantitative, many researchers have been attempting to develop objective and reasonable methods of determining constitutions. In Korea, even though a wide range of research regarding SCM has been conducted, most of the work has not been revealed internationally. So in this review, the authors have searched theJournal of Sasang Constitutional Medicine, as well as other Korean domestic journal databases and Pubmed for research regarding modernized constitution diagnosis methods so to provide the understanding of current research state and outlook for future research.

scholarly journals Quantitative Sasang Constitution Diagnosis Method for Distinguishing between Tae-eumin and Soeumin Types Based on Elasticity Measurements of the Skin of the Human Hand

2009 ◽  
Vol 6 (s1) ◽  
pp. 93-98 ◽  
Author(s):  
Han Wook Song ◽  
SungJun Lee ◽  
Yon Kyu Park ◽  
Sam Yong Woo
Keyword(s):  
Human Hand ◽  
Oriental Medicine ◽  
Compression Method ◽  
Repeatability Error ◽  
Sasang Constitution ◽  
Diagnosis Method ◽  
Sasang Constitutional Medicine ◽  
Constitutional Medicine ◽  
Measurement Repeatability ◽  
Elasticity Measurements

The usefulness of constitutional diagnoses based on skin measurements has been established in oriental medicine. However, it is very difficult to standardize traditional diagnosis methods. According to Sasang constitutional medicine, humans can be distinguished based on properties of the skin, including its texture, roughness, hardness and elasticity. The elasticity of the skin was previously used to distinguish between people with Tae-eumin (TE) and Soeumin (SE) constitutions. The present study designed a system that uses a compression method to measure the elasticity of hand skin and evaluated its measurement repeatability. The proposed system was used to compare the skin elasticity between SE and TE subjects, which produced a measurement repeatability error of <3%. The proposed system is suitable for use as a quantitative constitution diagnosis method for distinguishing between TE and SE subjects with an acceptable level of uncertainty.

scholarly journals Recent Progress in Voice-Based Sasang Constitutional Medicine: Improving Stability of Diagnosis

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Jun-Su Jang ◽  
Young-Su Kim ◽  
Boncho Ku ◽  
Jong Yeol Kim
Keyword(s):  
Gaussian Mixture ◽  
Voice Signal ◽  
Single Feature ◽  
Sasang Constitution ◽  
Diagnosis Accuracy ◽  
Good Repeatability ◽  
Diagnosis Model ◽  
Sasang Constitutional Medicine ◽  
Feature Values ◽  
Constitutional Medicine

Sasang constitutional medicine is a unique form of tailored medicine in traditional Korean medicine. Voice features have been regarded as an important cue to diagnose Sasang constitution types. Many studies tried to extract quantitative voice features and standardize diagnosis methods; however, they had flaws, such as unstable voice features which vary a lot for the same individual, limited data collected from only few sites, and low diagnosis accuracy. In this paper, we propose a stable diagnosis model that has a good repeatability for the same individual. None of the past studies evaluated the repeatability of their diagnosis models. Although many previous studies used voice features calculated by averaging feature values from all valid frames in monotonic utterance like vowels, we analyse every single feature value from each frame of a sentence voice signal. Gaussian mixture model is employed to deal with a lot of voice features from each frame. Total 15 Gaussian models are used to represent voice characteristics for each constitution. To evaluate repeatability of the proposed diagnosis model, we introduce a test dataset consisting of 10 individuals’ voice recordings with 50 recordings per each individual. Our result shows that the proposed method has better repeatability than the previous study which used averaged features from vowels and the sentence.

scholarly journals Prevalence of Metabolic Syndrome according to Sasang Constitutional Medicine in Korean Subjects

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Kwang Hoon Song ◽  
Sung-Gon Yu ◽  
Jong Yeol Kim
Keyword(s):  
Metabolic Syndrome ◽  
Risk Factor ◽  
Multiple Logistic Regression Analysis ◽  
Significant Risk ◽  
Significant Risk Factor ◽  
Atherogenic Dyslipidemia ◽  
Comprehensive Knowledge ◽  
Sasang Constitution ◽  
Sasang Constitutional Medicine ◽  
Constitutional Medicine

Metabolic syndrome (MS) is a complex disorder defined by a cluster of abdominal obesity, atherogenic dyslipidemia, hyperglycemia, and hypertension; the condition is recognized as a risk factor for diabetes and cardiovascular disease. This study assessed the effects of the Sasang constitution group (SCG) on the risk of MS in Korean subjects. We have analyzed 1,617 outpatients of Korean oriental medicine hospitals who were classified into three SCGs, So-Yang, So-Eum, and Tae-Eum. Significant differences were noted in the prevalence of MS and the frequencies of all MS risk factors among the three SCGs. The odds ratios for MS as determined via multiple logistic regression analysis were 2.004 for So-Yang and 4.521 for Tae-Eum compared with So-Eum. These results indicate that SCG may function as a significant risk factor of MS; comprehensive knowledge of Sasang constitutional medicine may prove helpful in predicting susceptibility and developing preventive care techniques for MS.

scholarly journals Differences in Complexion between Cold- and Heat-Prescription Groups in Sasang Medicine

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Young Joo Park ◽  
Jun-Hyeong Do ◽  
Honggie Kim ◽  
Jong Yeol Kim
Keyword(s):  
Blood Pressure ◽  
Color Space ◽  
Traditional Korean Medicine ◽  
Medical Treatments ◽  
Sasang Constitution ◽  
Significant Difference ◽  
Human Constitution ◽  
Sasang Constitutional Medicine ◽  
Constitutional Medicine ◽  
Herbal Prescription

Sasang constitutional medicine (SCM) is a type of traditional Korean medicine (TKM) that classifies the human constitution into four types. The appearance of the complexion is one of the diagnostic factors of SCM but is rarely used in a quantitative and objective manner for diagnosis. In this study, an analysis using actual clinical data was conducted to assess the use of the complexion as a diagnostic element. A total of 528 Sasang medicine prescriptions from Korea Constitutional Multicenter Bank (KCMB) were classified into either a Cold-prescription group or a Heat-prescription group, and the complexion differences of the patients were analyzed using the L⁎a⁎b⁎ color space. After adjusting for age, BMI, and systolic blood pressure, significant differences were observed among the Cold- and Heat-prescription groups within each Sasang constitution. However, when the Sasang constitution was ignored, no significant difference was observed for either sex. This study quantitatively analyzed the complexion of patients, which is used as a diagnostic element in clinical practice. It is hoped that the results will contribute to objective medical treatments in the future, such as determining an appropriate herbal prescription based on the patient’s complexion.

scholarly journals Korean Oriental Medicine in Stroke Care

2005 ◽  
Vol 10 (2) ◽  
pp. 105-117 ◽  
Author(s):  
Yong-Suk Kim ◽  
Jun Wang ◽  
Douglas Mann ◽  
Susan Gaylord ◽  
Hye-Jung Lee ◽  
...  
Keyword(s):  
Health Care ◽  
Stroke Care ◽  
Future Research ◽  
Primary Health Care System ◽  
Oriental Medicine ◽  
Primary Health ◽  
Preliminary Study ◽  
Sasang Constitutional Medicine ◽  
Constitutional Medicine ◽  
Korean Hand Acupuncture

Korean Oriental medicine (KOM), known as Hanbang in Korea, is the primary health care system for more than 20% of the population in Korea. Often integrated with allopathic Western medicine, it has been used and studied extensively in Korea for a variety of conditions, including stroke and Parkinson’s disease. Although KOM shares its origins with traditional Chinese medicine, its unique cultural contributions include a number of innovations in diagnosis and technique, such as Sasang constitutional medicine, Saam acupuncture, herbal acupuncture, and Korean hand acupuncture. This article reviews the development and use of KOM in Korea, focusing on a major component, Sasang constitutional medicine. It describes a preliminary study of effectiveness of Sasang constitutional medicine in the treatment of stroke and discusses the directions of future research in KOM.

Comparative Effects of High-Tech Visual Scene Displays and Low-Tech Isolated Picture Symbols on Engagement From Students With Multiple Disabilities

2019 ◽  
Vol 50 (4) ◽  
pp. 693-702 ◽  
Author(s):  
Christine Holyfield ◽  
Sydney Brooks ◽  
Allison Schluterman
Keyword(s):  
Language Learning ◽  
Augmentative And Alternative Communication ◽  
Visual Analysis ◽  
Multiple Disabilities ◽  
Visual Scene ◽  
Future Research ◽  
High Tech ◽  
Single Subject ◽  
Wide Range ◽  
The Difference

Purpose Augmentative and alternative communication (AAC) is an intervention approach that can promote communication and language in children with multiple disabilities who are beginning communicators. While a wide range of AAC technologies are available, little is known about the comparative effects of specific technology options. Given that engagement can be low for beginning communicators with multiple disabilities, the current study provides initial information about the comparative effects of 2 AAC technology options—high-tech visual scene displays (VSDs) and low-tech isolated picture symbols—on engagement. Method Three elementary-age beginning communicators with multiple disabilities participated. The study used a single-subject, alternating treatment design with each technology serving as a condition. Participants interacted with their school speech-language pathologists using each of the 2 technologies across 5 sessions in a block randomized order. Results According to visual analysis and nonoverlap of all pairs calculations, all 3 participants demonstrated more engagement with the high-tech VSDs than the low-tech isolated picture symbols as measured by their seconds of gaze toward each technology option. Despite the difference in engagement observed, there was no clear difference across the 2 conditions in engagement toward the communication partner or use of the AAC. Conclusions Clinicians can consider measuring engagement when evaluating AAC technology options for children with multiple disabilities and should consider evaluating high-tech VSDs as 1 technology option for them. Future research must explore the extent to which differences in engagement to particular AAC technologies result in differences in communication and language learning over time as might be expected.

Understanding Limited Use of Amplification in Infants and Children Who Are Hard of Hearing

2015 ◽  
Vol 25 (1) ◽  
pp. 15-23 ◽  
Author(s):  
Ryan W. McCreery ◽  
Elizabeth A. Walker ◽  
Meredith Spratford
Keyword(s):  
Hard Of Hearing ◽  
Hearing Aid ◽  
Management Strategies ◽  
Infants And Children ◽  
Future Research ◽  
Research Needs ◽  
Case Examples ◽  
Hearing Aid Use ◽  
Wide Range ◽  
In Infants And Children

The effectiveness of amplification for infants and children can be mediated by how much the child uses the device. Existing research suggests that establishing hearing aid use can be challenging. A wide range of factors can influence hearing aid use in children, including the child's age, degree of hearing loss, and socioeconomic status. Audiological interventions, including using validated prescriptive approaches and verification, performing on-going training and orientation, and communicating with caregivers about hearing aid use can also increase hearing aid use by infants and children. Case examples are used to highlight the factors that influence hearing aid use. Potential management strategies and future research needs are also discussed.

The Attenuation of Very Low Frequency Brain Oscillations in Transitions from a Rest State to Active Attention

2009 ◽  
Vol 23 (4) ◽  
pp. 191-198 ◽  
Author(s):  
Suzannah K. Helps ◽  
Samantha J. Broyd ◽  
Christopher J. James ◽  
Anke Karl ◽  
Edmund J. S. Sonuga-Barke
Keyword(s):  
Brain Activity ◽  
Sampling Rate ◽  
Low Frequency ◽  
Future Research ◽  
Adhd Symptoms ◽  
Default Mode ◽  
Very Low Frequency ◽  
Wide Range ◽  
Interference Hypothesis ◽  
Mode Interference

Background: The default mode interference hypothesis ( Sonuga-Barke & Castellanos, 2007 ) predicts (1) the attenuation of very low frequency oscillations (VLFO; e.g., .05 Hz) in brain activity within the default mode network during the transition from rest to task, and (2) that failures to attenuate in this way will lead to an increased likelihood of periodic attention lapses that are synchronized to the VLFO pattern. Here, we tested these predictions using DC-EEG recordings within and outside of a previously identified network of electrode locations hypothesized to reflect DMN activity (i.e., S3 network; Helps et al., 2008 ). Method: 24 young adults (mean age 22.3 years; 8 male), sampled to include a wide range of ADHD symptoms, took part in a study of rest to task transitions. Two conditions were compared: 5 min of rest (eyes open) and a 10-min simple 2-choice RT task with a relatively high sampling rate (ISI 1 s). DC-EEG was recorded during both conditions, and the low-frequency spectrum was decomposed and measures of the power within specific bands extracted. Results: Shift from rest to task led to an attenuation of VLFO activity within the S3 network which was inversely associated with ADHD symptoms. RT during task also showed a VLFO signature. During task there was a small but significant degree of synchronization between EEG and RT in the VLFO band. Attenuators showed a lower degree of synchrony than nonattenuators. Discussion: The results provide some initial EEG-based support for the default mode interference hypothesis and suggest that failure to attenuate VLFO in the S3 network is associated with higher synchrony between low-frequency brain activity and RT fluctuations during a simple RT task. Although significant, the effects were small and future research should employ tasks with a higher sampling rate to increase the possibility of extracting robust and stable signals.

COVID-19 Outbreak Prediction with Machine Learning

2020 ◽  
Author(s):  
Sina Faizollahzadeh Ardabili ◽  
Amir Mosavi ◽  
Pedram Ghamisi ◽  
Filip Ferdinand ◽  
Annamaria R. Varkonyi-Koczy ◽  
...  
Keyword(s):  
Machine Learning ◽  
Prediction Models ◽  
Fuzzy Inference ◽  
Control Measures ◽  
Future Research ◽  
Complex Nature ◽  
Inference System ◽  
Wide Range ◽  
Standard Models ◽  
High Level

Several outbreak prediction models for COVID-19 are being used by officials around the world to make informed-decisions and enforce relevant control measures. Among the standard models for COVID-19 global pandemic prediction, simple epidemiological and statistical models have received more attention by authorities, and they are popular in the media. Due to a high level of uncertainty and lack of essential data, standard models have shown low accuracy for long-term prediction. Although the literature includes several attempts to address this issue, the essential generalization and robustness abilities of existing models needs to be improved. This paper presents a comparative analysis of machine learning and soft computing models to predict the COVID-19 outbreak as an alternative to SIR and SEIR models. Among a wide range of machine learning models investigated, two models showed promising results (i.e., multi-layered perceptron, MLP, and adaptive network-based fuzzy inference system, ANFIS). Based on the results reported here, and due to the highly complex nature of the COVID-19 outbreak and variation in its behavior from nation-to-nation, this study suggests machine learning as an effective tool to model the outbreak. This paper provides an initial benchmarking to demonstrate the potential of machine learning for future research. Paper further suggests that real novelty in outbreak prediction can be realized through integrating machine learning and SEIR models.

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