• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2009.05a
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• pp.209-210
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• 2009

수면단계는 수면감성을 평가하는데 있어서 중요한 생리지표로서 사용되어왔다. 그러나 수면다원검사를 이용한 전통적 수면단계 분류방법은 뇌전도, 안전도, 심전도, 근전도 등을 종합적으로 측정하므로 수면단계를 비교적 정확히 분류할 수 있지만 피험자에게 심한 구속감을 주는 문제가 있다. 본 연구에서는, 각성상태에서 교감신경계가 지배적인 반면에 수면 중에는 부교감신경계가 더 활동적인 점에 착안하여 수면단계를 간단히 분류할 수 있는 방법을 찾고자 수면단계에 따른 심박동변이도(heart rate variability: HRV)를 분석하였다. 단일채널 심전도를 이용하여 수면단계별로 HRV 의 교감신경계/부교감신경계 활성도의 비율을 분석한 결과, W(wakefulness) 단계가 NREN(non REM) 2 단계, 3 단계, 4 단계에 비하여 높게 나타났으며, NREM 4 단계는 REM(rapid eye movement) 단계와 NREM 1단계에 비하여 낮게 나타났다. 또한 교감신경계/부교감신경계 활성도 비율의 수면단계에 따라 변화하는 양상은 W, REM, NREM 1, 2, 3, 4 단계의 순으로 단조 감소하였다.

• Annual Conference of KIPS
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• 2014.04a
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• pp.1012-1013
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• 2014

본 논문에서는 일상생활 중 지속적으로 심장 상태를 모니터링 할 수 있는 무구속 의자형 심탄도 측정시스템을 개발하였다. 또한 구현된 시스템에서 측정된 생체신호를 이용하여 주관적인 감정자극의 스트레스를 분석하기 위한 연구를 수행하였다. 수준을 분석하고자 하였다. 실험은 시스템에 착석하여 실시간으로 시청각 자극 실험을 수행하였고, 심박수와 심박변이도의 시간영역 및 주파수영역 파라미터를 확인하였다. 확인된 심박변이도의 파라미터는 시청각 도중 기술한 인간의 감정들을 체계화하여 2차원 공간에 여러 감정들의 관계를 나타낸 제임스 러셀(J. Russell)의 감정모델을 주관적인 감정 자극에 의한 스트레스 지표 나타내어 비교 분석하였다. 실험결과는 RMSSD, LF/HF 파라미터가 스트레스 수준 분류에 사용될 수 있는 잠재력을 가지고 있음을 증명한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.519-520
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• 2021

본 논문에서는 딥러닝 기반의 얼굴인식과 Harr Cascade 분류기를 이용한 눈인식, 스마트워치를 매개로 한 심박수 측정을 활용하여 운전자 졸음운전 경고 시스템을 제안하였다. 제안하는 시스템은 PERCLOS 방법을 적용하여 운전자의 눈 감은 시간을 누적시켜 졸음 상태 유무를 판단하고, 스마트워치의 HR센서를 활용한 운전자의 심박수 값 모니터링을 진행하여 졸음 발생 시 경고음을 발생시켜 졸음운전으로 인한 교통사고를 예방할 수 있다.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.6
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• pp.100-105
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• 2017

This work presents an ECG biometric recognition system for the purpose of biometric authentication. ECG biometric approaches are divided into two major categories, fiducial-based and non-fiducial-based methods. This paper proposes a new non-fiducial framework using discrete cosine transform and a Random Forest classifier. When using DCT, most of the signal information tends to be concentrated in a few low-frequency components. In order to apply feature vector of Random Forest, DCT feature vectors of ECG heartbeats are constructed by using the first 40 DCT coefficients. RF is based on the computation of a large number of decision trees. It is relatively fast, robust and inherently suitable for multi-class problems. Furthermore, it trade-off threshold between admission and rejection of ID inside RF classifier. As a result, proposed method offers 99.9% recognition rates when tested on MIT-BIH NSRDB.

• The KIPS Transactions:PartD
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• v.16D no.1
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• pp.11-26
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• 2009

In order to diagnose cardiovascular disease, we proposed EP-based(emerging pattern- based) classification technique using multi-parametric diagnosis indexes. We analyzed linear/nonlinear features of HRV for three recumbent postures and extracted four diagnosis indexes from ST-segments to apply the multi-parametric diagnosis indexes. In this paper, classification model using essential emerging patterns for diagnosing disease was applied. This classification technique discovers disease patterns of patient group and these emerging patterns are frequent in patients with cardiovascular disease but are not frequent in the normal group. To evaluate proposed classification algorithm, 120 patients with AP (angina pectrois), 13 patients with ACS(acute coronary syndrome) and 128 normal people data were used. As a result of classification, when multi-parametric indexes were used, the percent accuracy in classifying three groups was turned out to be about 88.3%.

• The Korean Journal of Nuclear Medicine Technology
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• v.19 no.1
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• pp.57-61
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• 2015

Purpose We considered the correlation of Ejection Fraction (EF) which was analyzed by Multi Gated Blood Pool Scan (MUGA) and Echocardiography (ECHO) for the patients who were classified according to the condition of cardiac function. Materials and Methods We analyzed the patients (female 60) who were diagnosed with breast cancer and were examined by both MUGA and ECHO. The 30 patients (age: $58.27{\pm}13.48$) who were analyzed into less than 50% to 70% of EF were categorized as normal group and the other 30 patients (age: $53.70{\pm}8.45$) who were analyzed into less than 50% of EF were categorized as abnormal group. Statistical analysis with SPSS ver. 18 was applied. Results Each of the value of mean and standard deviation of normal group was $66.43{\pm}5.80$ (MUGA), $60.50{\pm}4.93$ (ECHO). There was a significant difference (p<0.001). Each of the value of mean and standard deviation of abnormal group was $41.93{\pm}7.58$ (MUGA), $41.70{\pm}11.49$ (ECHO). There was no significant difference (p>0.001). In the result, all 30 cases of normal group showed the same reading. 8 out of 30 cases in abnormal group showed inconsistency of the reading. Conclusion We could confirm the correlation of the EF in MUGA and ECHO statistically. There was difference between abnormal groups from the result of reading. If we are aware of the result according to the different cardiac function categorization, MUGA and ECHO can be used as even more accurate interchangeable test.

• Journal of Korea Game Society
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• v.9 no.2
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• pp.3-12
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• 2009

In this study, by both qualitative and quantitative measurement on the purpose of deriving the sensitive amusement factor. I consider the fear of horror games as "the amused fear" and analyze it, which is based on the play theory by Roger Caillois. On the basis of this, I classified the amusement fear in horror games into the 4 factors. I conducted some positive tests through the player's response in order to verify them. The test is conducted measuring the heart rate of each experimenter by cardiometer while they are playing horror games. By analyzing the video data, I gave a name to the point that the amusement fear factors are expected to influence psychologically and physiologically as the fear point. At this point, I examined if the measured heart rate makes the outstanding difference or not, when compared average heart rate with experimenter's heart rate. In addition, I also examined if there is a statistical correlation of heart rate by attaching player's subjective data through the questionnaire. Consequently, it was statistically turned out that the experimenter's heart rate which is measured rose dramatically than usual, and that there are close correlations among subjective data. I also found out that the amusement fear factor at the relevant point plays a major role in experimenter's psychological and physiological response. In this study, I could prove the horror factor as a meaning of amusement factor using both theoretical method and positive method establishing a standard set that is helpful for further production and planning of the game.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2009.05a
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• pp.63-66
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• 2009

본 연구의 목표는 사용자에게 적합한 매트리스를 선택하는데 도움을 주는 신체적, 심리적 지표를 개발하고, 이를 분석하여 개인의 주관적 만족도와의 상관성을 알아보는 것이다. 시중에 판매되고 있는 5개의 매트리스의 강도를 2개씩 짝지어진 매트리스별 pared t-test를 통하여 강도별 순위를 5등급으로 분류하였다. 10명의 실험 참가자들의 신체적 지표(근전도, 심박수, 산소포화도 측정), 심리적 지표(개인 특성 설문 조사), 체압 및 주관적 만족도 측정을 실시하고, 상관분석을 통해서 이 측정결과와 개인간 주관적 만족도(선호하는 침대의 탄성)와도 일관성이 있는지 조사하였다. 연구 결과, 압력집중도(r=0.818)과 허리근육이완도(r=0.766) 그리고 심박수(r=0.670)가 주관적 만족도와 유의한 상관관계를 가지는 것으로 나타났다.

• Annual Conference of KIPS
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• 2023.05a
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• pp.627-629
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• 2023

생체 신호를 분석하여 사용자의 건강과 정신 상태를 예측하고, 관련 질병에 관해 예방하는 연구가 늘어나고 있다. 생체 신호 중 심박은 사람의 육체, 정신적인 상태를 반영하는 대표적인 신호이지만 기존의 접촉 패드를 통한 ECG나 광학 센서를 통한 PPG로 심박을 예측할 때는 구속적인 환경이 필요하여 일상적인 상황 속에 적용하기 어려웠다. 이러한 단점을 해결하고자 본 논문은 UBFC-RPPG 데이터셋의 동영상 프레임을 RGB 채널마다 다른 가중치를 적용하는 전처리를 하여 학습 데이터의 크기를 줄이면서 정확도를 높이고, 3D-CNN을 활용한 딥러닝으로 순간적인 영상에서도 PPG 신호를 예측할 수 있도록 1초 전처리 영상을 학습한 후, 신호를 예측하는 것을 목표로 한다. 이렇게 비접촉식으로 취득된 신호는 더 다양한 환경에서의 감정분류, 우울증 진단, 질병 감지 등 다양한 분야에 활용될 수 있다.

• The Journal of the Korea Contents Association
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• v.9 no.7
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• pp.225-232
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• 2009

This study conducted the following experiment to examine effects of cardiovascular function on lumbar stabilization exercise(LSE) in floor or swiss ball. This experiment was conducted to compare heart rate, systolic blood pressure, diastolic blood pressure and peripheral vascular oxygen saturation effects by lumbar stabilization exercise in floor or swiss ball with 18 normal adult and it divided 9 subjects. experiment group (1) is applying LSE on floor group and (2) is applying LSE on swiss ball group. Heart rate was measured by portable heart rate manometer, blood pressure was measured by hemodynamometer, and peripheral vascular oxygen concentration was measured using a computerized NURYTEC measuring apparatus analysis. These result lead us to the conclusion that systolic blood pressure and peripheral vascular oxygen concentration were influenced by LSE. but there was not differential effect between each groups. These results suggest that LSE has the capability to improve heart rate, blood pressure, peripheral vascular oxygen concentration. Consequently, LSE would be lead to increment of cardiovascular function.