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Microwave Radiometry 원리를 이용한 생체 내부 온도 추정
김경섭,이정환,Kim, Kyeong-Seop,Lee, Jeong-Whan 대한의용생체공학회 2006 의공학회지 Vol.27 No.6
Microwave Radiometry is the spectral measurement of eleclromagnetic radiation at frequency bands in the microwave region. One particular application of Microwave Radiometry is for analyzing temperature difffrentials of inside of human body to detect and diagnose pathologic conditions in which the temperature differentials are related with the symptoms of certain diseases. To accomplish this aim, we propose a new calibration method for estimating subcutaneous temperature by Microwave Radiometer and we also suggest a tumor-imitator phantom structure for simulating heat diffusion propagated by tissues around tumors to evaluate the discernment of brighuless temperature difffrentials.
스마트폰 연동 생체신호 왜곡보정을 위한 디지털 필터 설계 및 구현
김정환(Jeong-Hwan Kim),김경섭(Kyeong-Seop Kim),신승원(Seung-Won Shin),김현태(Hyun-Tae Kim),이정환(Jeong-Whan Lee),김동준(Dong-Jun Kim) 대한전기학회 2012 전기학회논문지 Vol.61 No.10
In this study, the novel digital filtering algorithms are implemented to suppress the noisy characteristics embedded in ambulatory electrocardiogram signals by an android smartphone platform. With this aim, Graphical User Interface (GUI) is designed and implemented by utilizing multithread-Java programming to realize Finite Impulse Response and Infinite Impulse Response filter. With simulating our implemented digital filters built in an android smartphone, we can find the fact that we can efficiently suppresses the noisy characteristics due to baseline wandering and 60 ㎐ powerline source fluctuations especially in electrocardiograms.
김정환(Jeong-Hwan Kim),신승원(Seung-Won Shin),김현태(Hyun-Tae Kim),윤태호(Tae-Ho Yoon),김경섭(Kyeong-Seop Kim),이정환(Jeong-Whan Lee),엄광문(Gwang-Moon Eom) 대한전기학회 2012 전기학회논문지 Vol.61 No.6
In this study, ambulatory electrocardiogram(ECG) signal and the rhythms of heart beats are visualized in terms of R-R intervals and Heart Rate Variability(HRV) in the environment of an android plaform. With this aim, Graphical User Interface(GUI) is implemented by executing multi-thread Java programming modules including ECG, heart-beats, tachogram and visualization unit. ECG signals are acquired in an android device by receiving the data from ambulatory ECG sensory system. Finite Impulse Response(FIR) filters are implemented to eliminate the baseline wandering noises contained in the ambulatory signals and DC-offset level in R-R interval data. With simulating the normal or stress emotional state of a subject, we can find the fact that HRV can be successfully estimated and visualized in an android smart phone platform.