• Journal of the Korean Magnetics Society
• /
• v.23 no.4
• /
• pp.135-143
• /
• 2013

The clip-type pulsimeter equipped with a Hall sensor has a permanent magnet attached in the "Chwan" position to the center of a radial artery. The clip-type pulsimeter is composed of a hardware system measuring voltage signals. These electrical bio-signals display pulse rate, non-invasive blood pressure, respiratory rate, pulse wave velocity (PWV), and spatial pulse wave velocity (SPWV) simultaneously measured by using the radial artery pulsimeter, the electrocardiograph (ECG), and the photoplethysmograph (PPG). The findings of this research may be useful for developing a oriental-western biomedical signal storage device, that is, the new and fusion patient monitor, for a U-health-care system.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.22 no.2
• /
• pp.287-297
• /
• 2019

Monitoring for the physiological state of a solider is essential to the realization of individual combat system. Despite all efforts over the last decades, there is no report to point out the optimal location of the wearable biosensors considering both monitoring accuracy and operational robustness. In response, we quantitatively measure body temperature and heartrate from 34 body parts using 2 kinds of biosensor arrays, each of which consists of a thermocouple(TC) sensor and either a photoplethysmography(PPG) sensor or an electrocardiography(ECG) sensor. The optimal location is determined by scoring each body part in terms of signal intensity, convenience in use, placement durability, and activity impedance. The measurement leads to finding the optimal location of wearable biosensor arrays. Thumb and chest are identified as best body parts for TC/PPG sensors and TC/ECG sensors, respectively. The findings will contribute to the successful development of individual combat system.

• Proceedings of the IEEK Conference
• /
• 2005.11a
• /
• pp.493-496
• /
• 2005

For home healthcare, the unconstrained measurement of physiological signal is highly required to avoid the inconvenience of users. The recording and analysis of the fundamental parameters during sleep like respiration and heart beat provide valuable information on his/her healthcare. Using the air mattress sensor system, the respiration and heart beat movements can be measured without any harness or sensor on the subject's body. The differential measurement technique between two air cells is adopted to enhance the sensitivity. The balancing tube between two air cells is used to increase the robustness against postural changes during the measurement period. The meaningful frequency range could be selected by the pneumatic filter with balancing tube. ECG (Electrocardiography) and respiration sensor (plethysmography) were measured for comparison with the signal from air mattress. To extract the heart beat information from air pressure sensor, digital signal processing technique was used. The accuracy for breathing interval and heart beat monitoring was acceptable. It shows the potentials of air mattress sensor system to be the unconstrained home sleep monitoring system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2010.05a
• /
• pp.233-236
• /
• 2010

This paper describes the packet traffic management of the Ubiquitous Healthcare System. In this system, ECG signal and accelerometer signal is transmitted from a wearable health shirt (WHS) to the base station. However, with the increment of users in this system, traffic over-load issue occurs. The main aim of this paper is to reduce the traffic over-load issue between sensor nodes by only transmitting the required signals to the base station when irregular activities are observed. In order to achieve this, in-network processing is adapted where the process of observation is conducted inside the sensor node of WHS. Results shows that irregular activities such as fall can be detected on real-time inside the sensor node and thus resolves traffic over-load issue.

• KIISE Transactions on Computing Practices
• /
• v.22 no.4
• /
• pp.195-200
• /
• 2016

With development of wearable devices, there is an increased interest in bio-signal monitoring techniques that can measure the user's health condition. However, embedding several bio-signal sensors in one wearable device has some inherent problems in terms of limited resources such as its size. Furthermore, such problem also arise when new bio-signal sensors are added. In this paper, we introduced the Bio-Cradle, which is a Plug-in module that can transfer the biological signals in real time from the accelerometer, ECG, or PPG sensor to other wearable devices at the request from the user of wearable devices. When the Bio-Cradle plugged in to the other device, it can transfer several synchronized bio-signals regardless of the type of device.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.8 no.2
• /
• pp.187-193
• /
• 2015

In this study, regressive models were employed to predict the blood velocity by using independent variables which measured by 3 sensors, such as electrocardiogram (ECG), photo-plethysmogram (PPG), pulse diagnosis sensor, without ultrasound device at high cost. In experiment, the high predictable model was induced to estimate the blood velocity correctly by comparing correlation values and significance probabilities between independent variables and blood velocities. Results showed that the model induced by two or three independent variables had a higher predictability than those by a single independent variable.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.53 no.10
• /
• pp.733-740
• /
• 2004

In this paper, an improved algorithm for the extraction of respiration signal from the electrocardiogram (ECG) is proposed. The whole system consists of two-lead electrocardiogram acquisition (lead Ⅰ and Ⅱ), baseline fluctuation elimination, R-wave detection, adjustment of sudden change in R-wave area using moving average, and optimal lead selection. In order to solve the problem of previous algorithms for the ECG-derived respiration (EDR) signal acquisition, we proposed a method for the optimal lead selection. An optimal EDR signal among the three EDR signals derived from each lead (and arctangent of their ratio) is selected by estimating the instantaneous frequency using the Hilbert transform, and then choosing the signal with minimum variation of the instantaneous frequency. The proposed algorithm was tested on 15 subjects, and we could obtain satisfactory respiration signals that shows high correlation (r>0.9) with the signal acquired from the chest-belt respiration sensor.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.14 no.2
• /
• pp.479-484
• /
• 2010

Researches of Healthcare have been fulfilled lively with an advanced age and change of lifestyles. Especially, medical field has focused on researches of Healthcare due to that reasons. The Healthcare service requires the foundation technologies, such as sensor aggregating, data saving and data transmitting/analysis. In this research, we proposed the unrestricted equipment which can save a lot of aggregated patient's medical data to guarantee the patient's movement in Healthcare service. Moreover, we research the method which can transmit the aggregated data as soon as possible. Also, we implemented the system which can transmit the patient's medical data automatically for convenient use.

• Journal of Sensor Science and Technology
• /
• v.20 no.2
• /
• pp.118-123
• /
• 2011

Heart related diseases mainly caused by heavy work load and increasing stress in human daily life. Therefore, researches on mobile healthcare monitoring for daily life has been carried out. Notably, wearable healthcare monitoring system which has least restriction has been tried to provide an emergency alert of abnormal heart rate. In this study, we developed chair type unconstrained BCG measurement system which able to perform continuous heart status monitoring at the office and daily life in the unconstrained way. Furthermore, adaptive threshold is used to detect the heart rate from BCG signals. The HRV(heart rate variability) is calculated from heart rate interval. ECG signal measured using conventional method and BCG signal measured using unconstraint system are carried out simultaneously for the purpose of performance evaluation. From the comparison result, BCG signal shows a similar heart beat characteristic as ECG signal. This proves the possibility of practical implementation of unconstraint healthcare monitoring system. In addition, medical examination like valsalva maneuver is performed to observe the changes in HRV due to stress. By performing valsalva maneuver, heart is said to be placed under an artificial physical stress condition. Under this artificial physical stress condition, the time and frequency domain of HRV parameters are evaluated.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2011.06a
• /
• pp.67-70
• /
• 2011

본 논문에서는 고성능 컴퓨팅 시스템의 성능 향상을 위한 효율적인 동적 작업부하 균등화 정책을 제안한다. 이 정책은 시스템 자원인 CPU와 메모리를 효율적으로 사용하여 고성능 컴퓨팅 시스템의 처리량을 최대화하고, 각 작업의 수행시간을 최소화한다. 또한 이 정책은 수행중인 작업의 메모리 요구량과 각 노드의 부하 상태를 파악하여 작업을 동적으로 할당한다. 이때 작업을 할당 받은 노드가 과부하 상태가 되면 다른 노드로 작업을 이주시켜 각 노드의 작업부하를 균등하게 유지함으로써 작업의 대기시간을 줄이고, 각 작업의 수행시간을 단축한다. 본 논문에서는 시뮬레이션을 통하여 제안하는 동적 작업부하 균등화 정책이 기존의 메모리 기반의 작업부하 균등화 정책에 비해 고성능 컴퓨팅 시스템의 성능 향상 면에서 우수함을 보인다.