• 융합신호처리학회논문지
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• 제3권1호
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• pp.27-32
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• 2002

본 논문에서 제안한 텔레미트리 시스템은 생체신호를 중거리로 전송하기 위한 RF 송신기와 전자파 간섭의 영향이 없는 광을 매체로한 수신기이다. 텔레미트리 시스템은 of 65$\times$125$\times$45mm크기이며, RF 송신부, 광 수신부와 생체신호 처리를 위한 CMOS 칩으로 구성되어 있다. 제안된 텔레메트리 장점은 전자파에 노출을 최소화하면서 중거리(50m) 텔레메트리가 가능하여, 자유로운 상태에서의 모니터링이 가능하다. 관측 시스템은 실시간 처리를 위해 dual-processor구조로 설계했다. 본 연구에서는 1 채널 360Hz, 16 Bits의 심전도 데이터를 1.42초 간격으로 실시간 웨이브렛 변환할 수 있었다.

• 산업융합연구
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• 제21권2호
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• pp.85-92
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• 2023

비정상적인 척추 질환 및 기능은 단순한 근·골격계 문제 외에도 항상성을 방해하고 직·간접적인 생리적 부작용을 일으킬 수 있다. 특히 척추를 통해 나오는 신경이 면역체계를 조절하는 기관에 적절한 신호를 전달하지 못하면 면역 기능의 일부 또는 전부에 문제가 생겨 더 많은 질병에 노출될 수 있다. 이 연구는 기본적인 해부학 및 생리학적 지식에 초점을 맞추고 척추 기능이 잠재적으로 면역 기능을 유지하거나 개선하는 데 도움이 될 수 있는 잠재적 메커니즘을 고찰하고자 한다. 이를 위해 조혈, 스트레스, 호흡, 척추와 신경의 관계, 면역체계와 관련된 척추의 역할을 살펴보고 이러한 역할이 면역기능에 영향을 미칠 수 있음을 확인한다.

• 한국HCI학회논문지
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• 제12권4호
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• pp.75-80
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• 2017

최근 인지과학의 활발한 연구와 기술의 발달로 인해 사회과학분야에서 정신생리학적 연구를 통한 뇌의 다양한 측정과 정교한 분석 기법이 개발 되었다. 그러나 뇌파를 이용한 뉴미디어활용에 관한 연구는 장비들을 장착하는 과정에서의 한계점으로 인해 진행되지 못하였다. 이러한 문제를 극복하고자, 가상현실장비를 착용한 상태에서도 전 영역의 뇌파측정이 가능한 캡을 디자인하고 활용방법을 제안한다.

• BMB Reports
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• 제46권12호
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• pp.600-605
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• 2013

Interplay between calcium ions ($Ca^{2+}$) and reactive oxygen species (ROS) delicately controls diverse pathophysiological functions of vascular smooth muscle cells (VSMCs). However, details of the $Ca^{2+}$ and ROS signaling network have been hindered by the absence of a method for dual measurement of $Ca^{2+}$ and ROS. Here, a real-time monitoring system for $Ca^{2+}$ and ROS was established using a genetically encoded hydrogen peroxide indicator, HyPer, and a ratiometric $Ca^{2+}$ indicator, fura-2. For the simultaneous detection of fura-2 and HyPer signals, 540 nm emission filter and 500 nm~ dichroic beamsplitter were combined with conventional exciters. The wide excitation spectrum of HyPer resulted in marginal cross-contamination with fura-2 signal. However, physiological $Ca^{2+}$ transient and hydrogen peroxide were practically measurable in HyPer-expressing, fura-2-loaded VSMCs. Indeed, distinct $Ca^{2+}$ and ROS signals could be successfully detected in serotonin-stimulated VSMCs. The system established in this study is applicable to studies of crosstalk between $Ca^{2+}$ and ROS.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1997년도 추계학술대회
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• pp.48-51
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• 1997

The purpose of this paper is to propose a method to protect the drowsiness of a driver. We measured the physiological signals, response time, and ace expression of the subjects in normal and drowsy state. Those data are used to establish the drowsiness index and fuzzy system. We employed the computer vision technology to extract and eye, track eyelids and measure the parameters related to drowsiness. These parameters were ed into the fuzzy system to decide the drowsiness level, When the drowsiness was detected, the fuzzy system generated warning signals which cons ist of sound and fragrance. Our system was available in decision of the drowsiness level and improvement of subjects' state.

• 대한의용생체공학회:의공학회지
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• 제26권6호
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• pp.373-381
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• 2005

The respiratory and heart beat signals are the fundamental physiological signals for sleep monitoring in the home. 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 which makes long term measurement difficult and troublesome. The differential measurement technique between two air cells is adopted to enhance the sensitivity. The concept of the balancing tube between two air cells is suggested to increase the robustness against postural changes during the measurement period. With this balancing tube, the meaningful frequency range could be selected by the pneumatic filter method. The mathematical model for the air mattress and balancing tube was suggested and the validation experiments were performed for step and sinusoidal input. The results show that the balancing tube can eliminate the low frequency component between two cells effectively. This technique was applied to measure the respiration and heart beat on the bed, which shows the potential applications for sleep monitoring device in home. With the analysis of the waveform, respiration intervals and heart beat intervals were calculated and compared with the signal from conventional methods. The results show that the measurement from air mattress with balancing tube can be used for monitoring respiration and heart beat in various situations.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1995년도 춘계학술대회
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• pp.160-163
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• 1995

An optimal EEG and artifact classifier is proposed using neural network operating characteristics. The neural network operating characteristics are two dimensional parametric representations of the right and false identification probabilities of the network classifier. Since the EEG and EP signals acquired from multi -channel electrodes placed on the head surface are often interfered by other relatively large physiological signals such as electromyogram (EMG) or electroculogram (EOG), the removal of the artifact-affected EEGs is one of the key elements in neuro-functional mapping. Conventionally this task has been carried out by human experts spending lots of examination time. Using the neural-network based classification, human expert's efforts and time can be substantially reduced. From experiments, the neural-network based classification performs as good as human experts: variation of decisions between the neural network and human expert appears even smaller than that between human experts.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2016년도 춘계학술대회
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• pp.515-517
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• 2016

본 논문에서는 신체 정보를 추출하여 감성인지 서비스를 제공할 수 있는 스트레처블 웨어러블 디바이스를 개발한다. 감성인지를 위한 생체신호는 직물센서를 활용한 피부전도도(EDR), 피부 온도(SKT) 및 심박수(HRV)를 통하여 수집되며 감성정보 검출 알고리즘을 이용하여 사용자에게 필요한 서비스를 제공한다. 또한 제안한 스트레처블 웨어러블 디바이스는 현재 유통 중인 웨어러블 디바이스의 주요 불만 요소인 짧은 배터리 수명, 스마트폰에 의존할 수밖에 없는 네트워크 범위 및 액세서리 제품으로서의 개성을 살릴 수 없는 디자인 문제점을 해결할 수 있다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.3243-3244
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• 2000

From ancient times, the diagnosis method of the oriental medicine has been performed by curing diseases by means of rectifying and adjusting the unbalance in the physiological function of the five viscera and the six bowels of a human body. Diseases have been diagnosed by the condition of blood circulation that cycles a human body through blood vessels by dint of the vitality of the heart. Based on such a systematic pulse diagnosis method, the article presents parameters that will be beneficial to clinical application on the basis of its analysis of the filtering for eliminating noises from pulse signals inputted from sensor group, the digital hardware dealing with signals necessary for recognition algorithm, and the structure of diagnosis algorithm and components of pulse waveform.

• 산업경영시스템학회지
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• 제37권1호
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• pp.1-8
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• 2014

This paper proposes an emotion classifier from EEG signals based on Bayes' theorem and a machine learning using a perceptron convergence algorithm. The emotions are represented on the valence and arousal dimensions. The fast Fourier transform spectrum analysis is used to extract features from the EEG signals. To verify the proposed method, we use an open database for emotion analysis using physiological signal (DEAP) and compare it with C-SVC which is one of the support vector machines. An emotion is defined as two-level class and three-level class in both valence and arousal dimensions. For the two-level class case, the accuracy of the valence and arousal estimation is 67% and 66%, respectively. For the three-level class case, the accuracy is 53% and 51%, respectively. Compared with the best case of the C-SVC, the proposed classifier gave 4% and 8% more accurate estimations of valence and arousal for the two-level class. In estimation of three-level class, the proposed method showed a similar performance to the best case of the C-SVC.