• The Journal of Information Technology
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• v.9 no.1
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• pp.21-32
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• 2006

Acrophobia is a symptom of feeling an abnormal fear of heights. Medications or cognitive-behavior methods have been mainly used to treat the acrophobia. In these days the virtua1 reality technology has been applied to treat such an anxiety disorders. In this thesis, an telemedicine assistant system for treatment of acrophobia using biomedical signals and virtual reality technique is proposed. I made two virtual reality simulations for treatment of acrophobia and telemedicine system for communication between doctor and patient using personal computer. A virtual environment provides patient with stimuli which arouses phobia, and exposition to such environment makes him have ability to overcome the fear. Recently, the patient can take diagnosis from a medical doctor in distance with the telemedicine system. Multimedia conference service, on-line questionary, signal transfer system are needed to configure such system. Virtual reality simulation system that composed of position sensor, head mount display, and audio system, is also included in this telemedicine system. I added virtual environment update system to this virtual reality telemedicine system for treatment of acrophobia. Former acrophobia treatment systems use only patient's score of the questionary to appraise. The new system developed in this thesis uses not only patient's score of the questionary but also biomedical signals such as HR, GSR amplitude, GSR RT to increase the objectivity and quantitativity. The experimental results show that HR and GSR amplitude are useful for decision of acrophobia. We will apply this system to the acrophobia patient in distance and be able to offer better medical treatment for mental illness in near future.

• Korean Journal of Biological Psychiatry
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• v.26 no.1
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• pp.1-7
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• 2019

Since non-cardiac chest discomfort (NCCD) can result in substantial healthcare burden and lower quality of life, interventions such as cognitive behavioral therapy (CBT) have been investigated for the relief of NCCD. In this review, we aimed to summarize the evidence on the efficacy of the CBT for the treatment of NCCD while introducing a newly-developed computerized CBT program for NCCD. Studies applying CBT to individuals with NCCD were searched for from both English and Korean electronic databases. Among 37 studies, 11 randomized controlled trials, 4 case-control studies, 1 case series, and 2 review articles were eligible for this review. Efficacy of conventional CBT for NCCD was shown in a series of studies as most of them reported improved symptom severity of NCCD or NCCD-related anxiety. However, a substantial variability existed among these studies in participants, treatment procedures and durations. High attrition rates were also reported in these studies on conventional CBT. Computerized CBT could be an alternative to the conventional CBT as it can be standardized and more easily accessible, but it was only reported in one previous study. In addition to the literature review, we presented a newly-developed computerized CBT program for NCCD which may overcome some of the limitations of conventional CBT. A computerized CBT could be an alternative treatment of NCCD, however, need further studies on its usefulness.

• Journal of the Korean Society of School Health
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• v.31 no.3
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• pp.186-195
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• 2018

Purpose: This study was performed to investigate the dietary behaviors and stress-related factors among male and female college students. Methods: A total of 405 college students (male-195, female-210) were recruited, of whom a questionnaire-based survey was conducted. The study investigated the general characteristics, health-related factors, dietary behaviors, and stress-related factors of the respondents. Results: The body mass index was significantly higher in males. The rates of underweight and overweight were significantly different between male and female respondents. The scores for workout frequency, health concerns and health condition were significantly higher in males, while the score for watching TV & playing computer games was significantly higher in females. The scores for meal regularity, frequency of breakfast consumption, and smoking were significantly higher in males. Eating problems showed a significant difference between males and females. The biggest source of stress was social factors, followed by college study and individual factors and the most experienced stress-induced symptom was anxiety, followed by headache and stomachache. The most popular way to overcome stress was taking a rest, followed by drinking & smoking and outdoor activity. The most preferred food under stressful conditions were alcohol or beverages, followed by hot & spicy food and sweet food, which showed a significant difference between males and females. Conclusion: These results indicate that stress affects dietary behaviors, drinking, smoking, and health status. Stress not only changes dietary behaviors, but is also related to health status. Therefore, it is necessary to develop appropriate programs for emotional stability and stress relief targeting college students which provide continuous nutrition education focused on desirable dietary behaviors and nutritional aspects.

• Women's Health Nursing
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• v.29 no.1
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• pp.20-31
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• 2023

Purpose: As more newborns have received expanded newborn screening (NBS) for metabolic disorders, the overall number of false-positive results has increased. The purpose of this study was to explore the psychological impacts experienced by mothers related to the NBS process. Methods: An online parenting community in Korea was selected, and questions regarding NBS were collected using web crawling for the period from October 2018 to August 2021. In total, 634 posts were analyzed. The collected unstructured text data were preprocessed, and keyword analysis, topic modeling, and visualization were performed. Results: Of 1,057 words extracted from posts, the top keyword based on 'term frequency-inverse document frequency' values was "hypothyroidism," followed by "discharge," "close examination," "thyroid-stimulating hormone levels," and "jaundice." The top keyword based on the simple frequency of appearance was "XXX hospital," followed by "close examination," "discharge," "breastfeeding," "hypothyroidism," and "professor." As a result of LDA topic modeling, posts related to inborn errors of metabolism (IEMs) were classified into four main themes: "confirmatory tests of IEMs," "mother and newborn with thyroid function problems," "retests of IEMs," and "feeding related to IEMs." Mothers experienced substantial frustration, stress, and anxiety when they received positive NBS results. Conclusion: The online parenting community played an important role in acquiring and sharing information, as well as psychological support related to NBS in newborn mothers. Nurses can use this study's findings to develop timely and evidence-based information for parents whose children receive positive NBS results to reduce the negative psychological impact.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.5
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• pp.1377-1393
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• 2023

Social media is used for various purposes including entertainment, communication, information search, and voicing their thoughts and concerns about a service, product, or issue. The social media data can be used for information mining and getting insights from it. The World Health Organization has listed COVID-19 as a global epidemic since 2020. People from every aspect of life as well as the entire health system have been severely impacted by this pandemic. Even now, after almost three years of the pandemic declaration, the fear caused by the COVID-19 virus leading to higher depression, stress, and anxiety levels has not been fully overcome. This has also triggered numerous kinds of discussions covering various aspects of the pandemic on the social media platforms. Among these aspects is the part focused on vaccines developed by different countries, their features and the advantages and disadvantages associated with each vaccine. Social media users often share their thoughts about vaccinations and vaccines. This data can be used to determine the popularity levels of vaccines, which can provide the producers with some insight for future decision making about their product. In this article, we used Twitter data for the vaccine popularity detection. We gathered data by scraping tweets about various vaccines from different countries. After that, various machine learning and deep learning models, i.e., naive bayes, decision tree, support vector machines, k-nearest neighbor, and deep neural network are used for sentiment analysis to determine the popularity of each vaccine. The results of experiments show that the proposed deep neural network model outperforms the other models by achieving 97.87% accuracy.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.3
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• pp.619-624
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• 2024

Scaling is one of the most basic dental gum treatments and involves removing tartar that has hardened on teeth. However, inexperienced and unprofessional removal of tartar may damage the gums, resulting in excessive bleeding or damage to the teeth. For this reason, scaling must be done delicately according to the gum structure of various people, and sufficient practice must be provided. Related departments at the university are conducting scaling exercises. However, from the perspective of students who have not had sufficient practice, selecting subjects and conducting practice is not easy, and practice subjects may also avoid participating in practice due to discomfort and anxiety. Accordingly, in this study, we designed and implemented a virtual reality practice system using VR to create a virtual patient rather than an actual subject and implement various gum shapes step by step to enable repetitive practice and various scaling experiences.

• Information Systems Review
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• v.18 no.4
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• pp.1-15
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• 2016

Electric cars are expected to increase quality of life by reducing air pollution and to contribute to economic growth by creating new businesses. However, electric car adoption has lagged and has not satisfied public expectation. One of the primary reasons for this outcome is the slow charging speed or inconvenience of charging a battery. Under the insufficient diffusion of electric cars, pushing business entities to construct charging facilities is undesirable for a policy maker to increase the adoption rate because of cost and management issues. This study adopts the design science methodology to interpret the problem of deploying electric car charging stations in the view of information systems. A trip planning algorithm is suggested on the basis of the theory of range anxiety. We investigate issues related to the current charging locations using data from drivers' car navigation devices. We also review its applicability to trip planning to obtain insights.

• Journal of the Korean Society of School Health
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• v.36 no.3
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• pp.113-125
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• 2023

Purpose: The purpose of this study is to develop a model for predicting mental health risk among adolescents based on health behavior information by employing a hybrid machine learning method. Methods: The study analyzed data of 51,850 domestic middle and high school students from 2022 Youth Health Behavior Survey conducted by the Korea Disease Control and Prevention Agency. Firstly, mental health risk levels (stress perception, suicidal thoughts, suicide attempts, suicide plans, experiences of sadness and despair, loneliness, and generalized anxiety disorder) were classified using the k-mean unsupervised learning technique. Secondly, demographic factors (family economic status, gender, age), academic performance, physical health (body mass index, moderate-intensity exercise, subjective health perception, oral health perception), daily life habits (sleep time, wake-up time, smartphone use time, difficulty recovering from fatigue), eating habits (consumption of high-caffeine drinks, sweet drinks, late-night snacks), violence victimization, and deviance (drinking, smoking experience) data were input to develop a random forest model predicting mental health risk, using logistic and XGBoosting. The model and its prediction performance were compared. Results: First, the subjects were classified into two mental health groups using k-mean unsupervised learning, with the high mental health risk group constituting 26.45% of the total sample (13,712 adolescents). This mental health risk group included most of the adolescents who had made suicide plans (95.1%) or attempted suicide (96.7%). Second, the predictive performance of the random forest model for classifying mental health risk groups significantly outperformed that of the reference model (AUC=.94). Predictors of high importance were 'difficulty recovering from daytime fatigue' and 'subjective health perception'. Conclusion: Based on an understanding of adolescent health behavior information, it is possible to predict the mental health risk levels of adolescents and make interventions in advance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.2
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• pp.435-442
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• 2017

Our anxiousness has risen for recent increase in unpredicatable disaster. Accordingly, for the future society's preventing measure in advance against current considerable disasters due to societal crisis, we need to prepare secure measure ahead. Hence, we need to recognize the significance of governmental role and the value of Big Data application as ICT developed country in order to manage social crisis all the time. This manuscript analyzes human anxiety from listed disasters and describes that our government seeks new way to utilize Big Data in public in order to visualize Big Data related issues and its significance and urgency. Also, it suggests domestic/international application trend of Big Data's public sector with new practical approach to Big Data. Then, it emphasizes e-Gov's role for its Big Data application and suggests policies implying governmental use of Big Data for social crisis management by case-studying disaster measures against unpredictable crisis.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.239-251
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• 2021

Traditional Chinese medicine has treated diseases and improved health in nature-based experience. Advanced nations began to be interested in naturopathic therapy in the late 19th century and it led China to research aromatherapy. This study searched previous researches related with aromatherapy and generally analyzed aroma oil, applied body parts, methods of use, and period of use. For research contents, scientific and society journals from 2000 to 2019 related with aromatherapy were searched in CNKI(www.cnki.com) and WANFANG DATE(www.wanfang.com). Finally, 30 papers were selected through 5-step qualitative evaluation and expert review and analyzed. Frequency and percentage(%) were calculated by means of the Excel 2013 Program and represented by a chart. The results of analyzing aromatherapy trends are as follows. All 30 papers were researched in the medical society. The most common symptom was irritation and anxiety that appeared in 13 papers. Lavender oil and bergamot oil were commonly used aroma oil. Commonly applied part and method were nose and nasal inhalation. For aroma oil associated with symptoms, lavender oil was the best in irritative, anxious, and negative emotion, depression, labor pain, sleep disorder, migraine, tension, and vomiting, pain, and fatigue after operation. Lemon, ginger, and peppermint oil was good for nausea. Based on the findings, this study derived applied body parts, methods of use, and period of use in aromatherapy. However, most aromatherapy was used for patients in the nursing and medical fields in the simple form of inhalation and local massage. This study will suggest a standard ground that aromatherapy is good for pain, colic pain, and tension in a short period but needs a long period for the efficacy of psychological and neurological symptoms.