Se Dong Min

Noncontact Respiration Rate Measurement System Using an Ultrasonic Proximity Sensor

This research presents the ultrasonic proximity sensor approach to respiration measurement. The ultrasonic proximity sensor measures respiration signatures and rates in real-time and for long-term monitoring, which is necessary for mobility from the end-user perspective. The study used a 240 kHz ultrasonic sensor to measure the time of flight of a sound wave between the transmitted signal and received signal during respiration in the abdominal wall-motion. Respiration rates measured with the ultrasonic proximity sensor were then compared with those measured with a thermocouple sensor on ten male subjects. Data from the measurement of respiration rates at 100 cm is provided. We have used this data from the method comparison study to confirm agreement with the reference signal to determine that the current version of respiratory rate detection system using ultrasonic can successfully measure respiration rates. The proposed respiratory measurement method could be used to monitor an unconscious person without the need to apply electrodes or other sensors in the correct position and to wire the subject to the system. Monitoring respiration using ultrasonic sensor offers a promising possibility of noncontact measurement of respiration rates. In particular, this technology offers a potentially inexpensive means to extend applications to consumer home-healthcare and mobile-healthcare products. Further advances in the sensor design, system design and signal processing can increase the range and quality of the measurement, broadening the potential application areas of this technology.

Adaptive Motion Artifacts Reduction Using 3-axis Accelerometer in E-textile ECG Measurement System

The electro-conductive fabric (e-textile or e-fabric) as an electrode for ECG measurement is one of the best application for ubiquitous healthcare system. However, it is difficult to measure the bio-signal due to its sensitivity variation caused by impedance change, especially by motion of the subject. In this paper, adaptive motion artifacts reduction using motion information from 3-axis accelerometer is proposed and analyzed in quantitative manner.

Simplified Structural Textile Respiration Sensor Based on Capacitive Pressure Sensing Method

We propose a simplified structural textile capacitive respiration sensor (TCRS) for respiration monitoring system. The TCRS is fabricated with conductive textile and Polyester, and it has a simple layered architecture. We derive the respiration by the distance changes between two textile plates in the TCRS, which measures the force from the abdominal diameter changes with the respiratory movement. To evaluate the reliability of TCRS, both linearity test and comparison test were carried out. Three times of tensile experiment were performed to confirm the linearity of change in capacitance by the distance change. The result shows that the coefficient of determination (R2) of proposed TCRS is 0.9933. For comparative study, 16 subjects were participating in the experiment. As a result, the proposed respiratory rate detection system using TCRS successfully measures respiration compared with nasal airflow detection (R = 0.9846, p <; 0.001). In Bland-Altman analysis, the upper limit agreement is 0.5018 respirations per minute and lower limit of the agreement is -0.5049 respirations per minute. From these results, we confirmed that the TCRS could be used for monitoring of unconscious persons, avoiding the uncomfortness of subjects. Monitoring respiration using TCRS offers a promising possibility of convenient measurement of respiration rates. In particular, this technology offers a potentially inexpensive implementation that could extend applications to consumer home-healthcare and mobile-healthcare products.

The e-Health Landscape: Current Status and Future Prospects in Korea

The e-health infrastructure in Korea has come a long way within a short period since the establishment of the Korea e-Health Association in 2003 by the Korean Ministry of Commerce, Industry and Energy. Since then, four related government departments in the Ministry of Health and Welfare, Ministry of Information and Communication, Ministry of National Defense, and the Ministry of Science and Technology have also started planning and promoting their own strategies for e-Health applications. We have defined standardization, law and policy planning, human resources development, research and development for e-health products, and international collaboration as the five core pillars for the development of a successful e-health industry. In 2008, through the reorganization of government ministries, e-health has become an even more important growth industry for the Korean economy. Consequently, relevant government ministries have more concrete and robust action plans for realization of e-health in effect.

Actual Condition of Korean e-Health: What Do Enterprisers Want for Developing e-Health Industry?

In this paper, we present actual condition of Korean e- Health from an industrial aspect. We have investigated the status of e-Health industry from 326 companies in Korea. The questionnaire consisted of four categories which are: the potential of e-Health industry, the key domain of e-Health industry, the bottleneck in the governments policies, and the importance of national policy for developing e-Health. As a result of this investigation, we have found out that many businesses have expected that e-Health industry will be a powerful industry in the next generation, and mobile healthcare domain will be expected as a core technology.

An arrhythmia classification algorithm using a dedicated wavelet adapted to different subjects.

BackgroundNumerous studies have been conducted regarding a heartbeat classification algorithm over the past several decades. However, many algorithms have also been studied to acquire robust performance, as biosignals have a large amount of variation among individuals. Various methods have been proposed to reduce the differences coming from personal characteristics, but these expand the differences caused by arrhythmia.MethodsIn this paper, an arrhythmia classification algorithm using a dedicated wavelet adapted to individual subjects is proposed. We reduced the performance variation using dedicated wavelets, as in the ECG morphologies of the subjects. The proposed algorithm utilizes morphological filtering and a continuous wavelet transform with a dedicated wavelet. A principal component analysis and linear discriminant analysis were utilized to compress the morphological data transformed by the dedicated wavelets. An extreme learning machine was used as a classifier in the proposed algorithm.ResultsA performance evaluation was conducted with the MIT-BIH arrhythmia database. The results showed a high sensitivity of 97.51%, specificity of 85.07%, accuracy of 97.94%, and a positive predictive value of 97.26%.ConclusionsThe proposed algorithm achieves better accuracy than other state-of-the-art algorithms with no intrasubject between the training and evaluation datasets. And it significantly reduces the amount of intervention needed by physicians.

Medical Endoscopic Image Segmentation with Multi-resolution Deformation

Image segmentation is an essential technique in image analysis. In spite of issues in contour initialization, boundary concavities and high-level computation, active contour models, also known as snake, are a popular and successful method for segmentation among researchers. Segmentation process in snakes consists of calculation of energy and deformation of contour. In this paper, we present a new deformation method for active contour model, multi-resolution deformation algorithm ensuring powerful time reduction in convergence of the contour to target boundary.

A Localization Method for First and Second Heart Sounds Based on Energy Detection and Interval Regulation

The present study suggests a localization method for the first (S1) and the second (S2) feature of heart sounds, based on an algorithm involving frequency filtering, energy detection, and interval regulation. Localization accuracy was evaluated by comparing the algorithm with the traditional Hilbert transform-based localization method. Results show that the sensitivity and the positive predictivity value of proposed method, respectively, were 97.27 % and 99.94 % in S1 detection and 94.99 % and 100 % in S2 detection.

Evaluation of the Ambient Temperature Effect for the Autonomic Nervous Activity through the Time Domain Analysis of the Heart Rate Variability

The purpose of this paper is to investigate the autonomic nervous system activity in various ambient temperature situation. To evaluate autonomic function, we use the time domain analysis of heart rate variability. Electrocardiogram was recorded to derive heart rate variability in 3 different temperature room which temperature is controlled in 18℃(low), 25℃ (mid) and 38℃(high), respectively. Totally 22 subjects were participated in the experiment. The result shows that the time-domain variables such as AVNN, SDNN, SDSD, RMSSD, NN50, pNN50, NN20 and pNN20 show the significant difference between low and high temperature (p 0.05) between mid and high except on AVNN, RMSSD and pNN20. AVNN, RMSSD shows the highest significance (p<0.001) according to the various temperature environment.