Youngbum Lee

Metabolic syndrome and its association with white blood cell count in children and adolescents in Korea: the 2005 Korean National Health and Nutrition Examination Survey.

BACKGROUND AND AIMS To estimate the prevalence of metabolic syndrome (MS) and determine its association with white blood cell (WBC) count as a marker of low-grade systemic inflammation in children and adolescents in Korea. METHODS AND RESULTS We investigated the prevalence of MS and its association with WBC count in 928 children and adolescents. MS was defined as having 3 or more conditions based on the modified criteria of the National Cholesterol Education Program-Adult Treatment Panel III (NCEP-ATP III). The odds ratios (ORs) for MS were also calculated using multivariate logistic regression analysis across WBC count quartiles (Q1, <5200; Q2, 5200-6100; Q3, 6200-7200; and Q4, >or=7300 cells/microL for boys; Q1, <5200; Q2, 5200-6000; Q3, 6100-7000; and Q4, >or=7100 cells/microL for girls). The prevalence of MS in children and adolescents in Korea was 6.7% (8.5% in boys, 4.5% in girls, P<0.001). MS was more prevalent in overweight and obese children and adolescents in both boys and girls. The mean WBC counts continuously increased with each additional component of MS in both boys and girls. The ORs (95% CIs) for MS in each WBC quartile were 1.00, 1.56 (0.43-5.67), 4.47 (1.42-14.07), and 5.25 (1.71-16.07) in boys and 1.00, 1.05 (0.15-7.61), 2.89 (0.55-15.17), and 7.47 (1.61-36.67) in girls after adjusting for age, household income, and residential area. CONCLUSION In summary, this study shows that a substantial number of children and adolescents in Korea have MS, and elevated WBC count may be a surrogate marker for MS.

Reading nutrition labels is associated with a lower risk of metabolic syndrome in Korean adults: the 2007-2008 Korean NHANES.

BACKGROUND AND AIMS Several studies demonstrated that reading nutrition labels was associated with healthier food choices, despite some controversy. This study investigated the association between the use of nutrition labels and metabolic syndrome (MetS) in Korean adults. METHODS AND RESULTS This cross-sectional study included 7756 individuals who participated in the 2007-2009 Korean National Health and Nutrition Examination Survey (KNHANES). A self-reported questionnaire was used to determine participants awareness of nutrition labels. Modified Asian criteria based on a harmonizing definition of MetS were adopted. Individuals in the group that read nutrition labels (the Reading Group) were youngest and leanest, but their daily caloric intake fell between that of the group that did not read nutrition labels (the Non-Reading Group) and the group that did not know about them (the Not-Knowing Group). The prevalence of MetS was 16.8% in the Reading Group, 27.2% in the Non-Reading Group, and 47.3% in the Not-Knowing Group. In comparison to participants in the Reading Group, the odds ratios (95% confidence interval) for MetS in the participants in the Non-Reading Group and Not-Knowing Group were 1.85 (1.60-2.14) and 4.44 (3.79-5.20), respectively, when not adjusted. The relationship between the use of nutrition labels and MetS remained statistically significant even after adjusting for covariates such as age, sex and socioeconomic status including household income and education level [1.27 (1.05-1.53) in the Non-Reading Group and 1.34 (1.05-1.70) in the Not-Knowing Group]. CONCLUSION Reading nutrition labels appeared to be associated with a lower prevalence of MetS in a nationally representative sample of Korean adults.

SMS Application Using EMG Signal of Clenching Teeth for e-Health Communication

A proposed system using a Short Message Service (SMS) application based on electromyography (EMG)-controlled human-computer interface method by clenching teeth was evaluated. This system consists of an EMG signal processing device and SMS Software module on the PC. We can use SMS by a simple combination of two clenching patterns. The purpose of this study is to evaluate easy and comfortable communication methods for the disabled and rehabilitation patients as an e-health tool.

Relationship between non‐alcoholic fatty liver disease and pulmonary function

Background:  It has been observed that non‐alcoholic fatty liver disease (NAFLD) is associated with an increased risk of cardiovascular disease and insulin resistance. Pulmonary function is also known to be related with cardiovascular disease and metabolic syndrome.

Wearable sensor glove based on conducting fabric using electrodermal activity and pulse-wave sensors for e-health application.

Improvement of the quality and efficiency of health in medicine, both at home and the hospital, calls for improved sensors that might be included in a common carrier such as a wearable sensor device to measure various biosignals and provide healthcare services that use e-health technology. Designed to be user-friendly, smart clothes and gloves respond well to the end users for health monitoring. This study describes a wearable sensor glove that is equipped with an electrodermal activity (EDA) sensor, pulse-wave sensor, conducting fabric, and an embedded system. The EDA sensor utilizes the relationship between drowsiness and the EDA signal. The EDA sensors were made using a conducting fabric instead of silver chloride electrodes, as a more practical and practically wearable device. The pulse-wave sensor measurement system, which is widely applied in oriental medicinal practices, is also a strong element in e-health monitoring systems. The EDA and pulse-wave signal acquisition module was constructed by connecting the sensor to the glove via a conductive fabric. The signal acquisition module is then connected to a personal computer that displays the results of the EDA and pulse-wave signal processing analysis and gives accurate feedback to the user. This system is designed for a number of applications for the e-health services, including drowsiness detection and oriental medicine.

Performance evaluation of a motor-imagery-based EEG-Brain computer interface using a combined cue with heterogeneous training data in BCI-Naive subjects

BackgroundThe subjects in EEG-Brain computer interface (BCI) system experience difficulties when attempting to obtain the consistent performance of the actual movement by motor imagery alone. It is necessary to find the optimal conditions and stimuli combinations that affect the performance factors of the EEG-BCI system to guarantee equipment safety and trust through the performance evaluation of using motor imagery characteristics that can be utilized in the EEG-BCI testing environment.MethodsThe experiment was carried out with 10 experienced subjects and 32 naive subjects on an EEG-BCI system. There were 3 experiments: The experienced homogeneous experiment, the naive homogeneous experiment and the naive heterogeneous experiment. Each experiment was compared in terms of the six audio-visual cue combinations and consisted of 50 trials. The EEG data was classified using the least square linear classifier in case of the naive subjects through the common spatial pattern filter. The accuracy was calculated using the training and test data set. The p-value of the accuracy was obtained through the statistical significance test.ResultsIn the case in which a naive subject was trained by a heterogeneous combined cue and tested by a visual cue, the result was not only the highest accuracy (p < 0.05) but also stable performance in all experiments.ConclusionsWe propose the use of this measuring methodology of a heterogeneous combined cue for training data and a visual cue for test data by the typical EEG-BCI algorithm on the EEG-BCI system to achieve effectiveness in terms of consistence, stability, cost, time, and resources management without the need for a trial and error process.

Implementation of Wearable Sensor Glove using Pulse-wave Sensor, Conducting Fabric and Embedded System

Today, there are research trends about the wearable sensor device that measures various bio-signals and provides healthcare services to user using e-health technology. This study describes the wearable sensor glove using pulse-wave sensor, conducting fabric and embedded system. This wearable sensor glove is based on the pulse-wave measurement system which is able to measure the pulse wave signal in much use of oriental medicine on the basis of a research trend of e-health system.

Development of Integrated Module using Wireless Accelerometer and ECG Sensor for ADL Monitoring

This research implements wireless ECG and acceleration measurement device that is small enough to put on body and operating by embedded battery. The module has connector for 3 ECG electrodes socket and embedded 3-axis accelerometer sensor. Also, it has SD memory slot and store all data within 2 GB. And it transmits the data using wireless module so we can measure the subjects ECG and activity transition value. Using the correlation between accelerometer signal and ECG signal, we can determine the activity assessment more precisely and also detect the cardiovascular abnormality.

Indoor Positioning System for Moving Objects on an Indoor for Blind or Visually Impaired Playing Various Sports

We have proposed an indoor positioning system for moving objects and / for the blind or visually impaired to play various sports. [ for a blind or visually impaired playing various sports.] This system consists of a wireless heart rate monitor, wireless sensor network and / 4 ultrasound satellites [ configuration with four ultrasound satellite modules) at the corners of the room. This system provides / the real-time measurement of the location and heart rate of the person in the room[ noninvasive measurement method of the heart rate and the location of a person in real time ], and will help the [a] blind or visually impaired enjoy sports more easily.

Implementation of Safety Driving System Using e-Health and Telematics Technology

This research aimed to develop a safety driving system using e-health and telematics technology. Biosignal sensors were installed in an automobile to check the drivers health status with an automatic diagnosis system providing health information to the driver. Measured data were sent to the e-health center through a telematics device, and a medical doctor analyzed these data, sending diagnosis and prescription information to the driver. This system recognizes the drivers sleeping, drinking impairment, excitability, and fatigue using biosensors. The system initially provides alerts in the automobile. It also controls the driving environment in the car, searches for a highway service area using Global Positioning System (GPS), and provides additional information for safety driving. If a car accident has occurred, it makes an emergency call to the nearest hospital, emergency center, and insurance company. A conceptual and prototype model for an imbedded system is presented with initial data for driver condition. Such a system could prevent car accidents caused by drivers driving while intoxicated and falling asleep at the wheel using the drivers biosignals measured by biosensors. The system can provide various e-health services using a telematics system to enhance the technical compatibility of the automobile.