• 한국전기전자재료학회논문지
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• 제23권1호
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• pp.76-85
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• 2010

In general, anesthetic depth is evaluated by experience of anesthesiologist based on the changes of blood pressure and pulse rate. So it is difficult to guarantee the accuracy in evaluation of anesthetic depth. The efforts to develop the objective index for evaluation of anesthetic depth were continued but there was few progression in this area. Heart rate variability provides much information of autonomic activity of cardiovascular system and almost all anesthetics depress the autonomic activity. Novel monitoring system which can simply and exactly analyze the autonomic activity of cardiovascular system will provide important information for evaluation of anesthetic depth. We investigated the anesthetic depth as following 7 stages. These are pre-anesthesia, induction, skin incision, before extubation, after extubation, Post-anesthesia. In this study, temporal, frequency and chaos analysis method were used to analyze the HRV time series from electrocardiogram signal. There were NN10-NN50, mean, SDNN and RMS parameter in the temporal method. In the frequency method, there are LF and HF and LF/HF ratio, 1/f noise, alphal and alpha2 of DFA analysis parameter. In the chaos analysis, there are CD, entropy and LPE. Chaos analysis method was valuable to estimate the anesthetic depth compared with temporal and frequency method. Because human body was involved the choastic character.

• 한국정보전자통신기술학회논문지
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• 제2권3호
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• pp.9-15
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• 2009

분만시 국내에서 영아 사망률은 약 1%에 이르고, 태아의 질병 발생과 사망은 계속적으로 일어나고 있으므로 저가의 태아 모니터링기술의 개발이 절실하다. 이를 위하여 본 연구에서는 임산부의 복부로부터 태아의 움직임과 심음을 검출할 수 있는 증폭기를 설계하여 고성능 태아 포노그램용 전자청진장치를 개발하고자 한다. 장치로부터 검출된 태아의 청진 신호는 듣거나 녹음할 수 있으며, PC에서 태아의 심음을 분석할 수도 있다. 개발된 증폭기를 이용하여 잡음에 노출된 일반 대학병원 환경에서 30명의 임산부를 대상으로 임상실험을 수행한 결과, 개발된 증폭기는 저잡음, 고이득의 특성을 나타내고, 임산부 중에서 빠른 경우 22주에서도 태아의 심음을 검출할 수 있었고, 심음의 주기검출이 가능하였다.

• 문화기술의 융합
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• 제8권6호
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• pp.905-910
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• 2022

졸음운전은 교통사고 발생률을 높이고 사망사고로 이어지기 때문에 많은 사회적 관심이 필요하다. 졸음운전으로 인한 사고 건수는 매년 증가하고 있다. 따라서 전 세계적으로 이 문제를 해결하기 위해 다양한 생체신호 측정을 위한 연구가 수행되고 있다. 본 논문에서는 그 중에 비접촉 방식의 생체신호 분석에 중점을 두고 있다. 주행중인 차량에서는 엔진, 타이어, 차체 진동 등 다양한 노이즈가 발생한다. 압전센서로 주행중인 차량에서 운전자의 심박수와 호흡수를 측정하기 위해 차량 진동을 완충할 수 있는 센서 플레이트를 설계했고 차량에서 발생하는 노이즈를 줄일 수 있었다. 또한 압전센서의 신호 기반 CNN-LSTM 앙상블 학습 기법으로 모델을 추출하여 운전자가 수면중인지 아닌지 분류하는 시스템을 개발했다. 수면 상태를 학습시키기 위해 30초마다 피험자의 생체 신호를 획득하였고, 797개의 데이터를 비교 분석하였다.

• 한국전자파학회논문지
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• 제20권12호
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• pp.1325-1332
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• 2009

본 논문에서는 인체의 호흡 및 심박수 측정을 위해 2.4 GHz에서 동작하는 바이오 레이더 시스템의 소형화 및 성능 개선 방안으로서 하나의 원형 편파 안테나와 PLL 회로를 갖는 시스템을 설계하고 그 측정 결과를 제시 하였다. 제작된 바이오 레이더는 $90^{\circ}$ 하이브리드를 이용하여 원형 편파 특성과 송수신 격리 특성을 갖는 마이크 로스트립 안테나, 저잡음 증폭기, 전력 증폭기, 위상 고정 루프를 갖는 전압 제어 발진기, 직교 복조기 및 아날로그 회로로 구성된다. 특히, 단일 원형 편파 안테나를 소형화하기 위하여 annular-ring 형태의 마이크로스트립 안 테나를 송수신 회로와 적층함으로써, $40\times40mm^2$의 크기로 소형화할 수 있었다. 또한, 누설 송신 신호에 인한 수신부의 위상 잡음의 영향을 최소화하기 위하여 PLL 회로를 채용함으로써, 개선된 신호대 잡음비 성능을 갖도록 하였다. 설계된 바이오 레이더 시스템은 특별한 신호 처리 없이 50 cm 떨어진 사람의 호흡 및 심박수를 측정할 수 있음을 확인하였다.

• 센서학회지
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• 제25권3호
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• pp.196-201
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• 2016

Rehabilitation exercises are the treatments designed to help patients who are in the process of recovery from injury or illness to restore their body functions back to the original status. However, many patients suffering from chronic diseases have found difficulties visiting hospitals for the rehabilitation program due to lack of transportation, cost of the program, their own busy schedules, etc. Also, the program usually contains a few medical check-ups which can cause patients to feel uncomfortable. In this paper, we develop a remote rehabilitation system with bio-signals by a stereo camera. A Kinect stereo camera manufactured by Microsoft corporation was used to recognize the body movement of a patient by using its infrared(IR) camera. Also, we detect the chest area of a user from the skeleton data and process to gain respiratory status. ROI coordinates are created on a user's face to detect photoplethysmography(PPG) signals to calculate heart rate values from its color sensor. Finally, rehabilitation exercises and bio-signal detecting features are combined into a Windows application for the cost effective and high performance remote rehabilitation system.

• 한국멀티미디어학회논문지
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• 제20권9호
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• pp.1509-1518
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• 2017

Although several methods have been used to assess the pain levels, few practical methods for classifying presence or absence of the pain using pattern classifiers have been suggested. The aim of this study is to design an pattern classifier that classifies the presence or absence of the pain using electrocardiogram (ECG). We measured the ECG signal from 10 subjects with the painless state and the pain state(Induced by mechanical stimulation). The 10 features of heart rate variability (HRV) were extracted from ECG - MeanRRI, SDNN, rMSSD, NN50, pNN50 in the time domain; VLF, LF, HF, Total Power, LF/HF in the frequency domain; and we used the features as input vector of the pattern classifier's artificial neural network (ANN) / support vector machine (SVM) for classifying the presence or absence of the pain. The study results showed that the classifiers using ANN / SVM could classify the presence or absence of the pain with accuracies of 81.58% / 81.84%. The proposed classifiers can be applied to the objective assessment of pain level.

• 센서학회지
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• 제15권6호
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• pp.417-424
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• 2006

An ubiquitous healthcare monitoring system for elderly person at home was designed for continuous healthy monitoring of elderly person or patients. Human vital signals, such as ECG and body temperature, were monitored by terminal PC or PDA via ECG and temperature sensor nodes on the patient's body. From the ECG data, the heart rate, tachycardia, bradycardia and arrhythmia were diagnosed on the terminal PC or PDA to assist doctor's or nurse's aid or patient itself to monitor the patient's condition and give medical examination. Artificial judgement support system was designed in server computer and the system support a doctor or nurser for management or treatment of the patient. This system can be applied to vital signal monitoring system for solitude elderly person at self house or home health care service part. And this ubiquitous healthcare system can reduce the medical expenses in coming aging or aged society.

• 대한전기학회논문지:시스템및제어부문D
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• 제54권3호
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• pp.198-205
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• 2005

In this paper, we proposed a new algorithm for the separation of fetal ECG from single channel abdominal ECG. The algorithm consists of a stage of demixing vector calculation for initial signal and a stage of fetal beat detection for the rest of signal. The demixing vector was obtained by applying independent component analysis technique to projected signals into time-frequency domain. For the test of this algorithm, simulation signals, De Lathauwer's data and some measured data, which was acquired from 8 healthy volunteers whose pregnant periods ranged from 22 weeks to 35 weeks and whose ages from 27 to 37, were used. For each data, the accuracy of fetal beat detection was $100\%$ and with the location of fetal beats, fetal heart rate variability and morphology could be offered. In conclusion, this proposed algorithm showed the possibility of fetal beat separation with a single channel abdominal ECG and it might be adopted to a fetal health monitoring system, by which a single channel abdominal ECG is acquired.

• 대한인간공학회지
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• 제27권4호
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• pp.95-101
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• 2008

This research is to develop PPG filtering method for respiration measurement in U-Health Care system. Respiration rate was determined by filtering PPG and analyzing its spectrum. Optimal filter of PPG has been selected to get respiration by testing 120 sets of experiment data using 700 filtering cases. As a result, 2nd order Bessel-filter that used band-pass cutoff frequency at 0.175~0.4Hz with second order was good at developing respiration signal. Respiration signal in time domain could be continuously analyzed by converting frequency domain using spectrum analysis. 24 seconds has been found to be optimal time duration of collecting PPG data for determining respiration. Therefore, this study was successful of getting not only heart activity but also respiration by only PPG. Minimal invasive measurement obtaining multi-bio information by one sensor can be expected to apply to U-Health Care and human computer interaction.

• 디지털산업정보학회논문지
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• 제17권1호
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• pp.7-14
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• 2021

With the increased attention about healthcare and management of heart diseases, smart healthcare services and related devices have been actively developed recently. R wave is the largest representative signal among ECG signals. R wave detection is very important because it detects QRS pattern and classifies arrhythmia. Several R wave detection algorithms have been proposed with different features, but the remaining problem is their implementation in low-cost portable platforms for real-time applications. In this paper, we propose R wave detection based on optimal threshold and arrhythmia classification through QRS pattern considering complexity in smart healthcare environments. For this purpose, we detected R wave from noise-free ECG signal through the preprocessing method. Also, we classify premature ventricular contraction arrhythmia in realtime through QRS pattern. The performance of R wave detection and premature ventricular contraction arrhythmia classification is evaluated by using 9 record of MIT-BIH arrhythmia database that included over 30 premature ventricular contraction. The achieved scores indicate the average of 98.72% in R wave detection and the rate of 94.28% in PVC classification.