• Journal of Biomedical Engineering Research
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• v.35 no.3
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• pp.55-61
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• 2014

In sleep monitoring system, polysomnography (PSG) is the gold-standard but previous studies revealed that attaching numerous amount of sensors disturb sleep during the test which is the fundamental disadvantage of PSG. We suggest an unconstrained rapid-eye-movement (REM) sleep monitoring method measured with polyvinylidene (PVDF) film-based sensor for the normal and the obstructive sleep apnea (OSA) patients. Nine normal subjects and seventeen OSA patients have participated in the study. During REM sleep, rate and variability of respiration are known to be greater than in other sleep stages. Based on this phenomena, respiratory signals of participants were unconstrainedly measured using the PVDF-based sensor with the PSG and REM sleep were extracted from the average rate and variability of respiration. In epoch-by-epoch REM sleep detection, proposed method classified REM sleep with an average sensitivity of 72.3%, specificity of 92.5%, accuracy of 88.9%, and kappa statistic of 0.60 compared to the results of PSG. Student's t-test showed no significant difference between the results of normal and OSA group. This method is potentially applicable to REM sleep detection in homing environment or ambulatory monitoring.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.4
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• pp.97-104
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• 2010

In this paper, we provide an embedded type non-contact bio-radar heart and respiration rate monitoring system. We implemented the rate finding algorithm into the embedded system. The high-speed and reliable real-time signal processor is then tested. To avoid null-point data loss problem, we applied quadrature demodulation. Among several other combining techniques, we suggest arctangent demodulation for quadrature channel combining and DSP is used for real-time signal processing. We also suggest DC-offset compensation technique to preserve the wanted DC components of the IQ signals for accurate demodulation while keeping the dynamic range of the ADC lower. Using Texas Instrument C6711 series DSP and external 12Bit ADC, we implemented proper elliptic digital filter and autocorrelation detection algorithm for robust commercial hand held device.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.4
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• pp.418-425
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• 2014

This paper presents a Ku-Band Doppler Radar System to measure respiration and heart rate. It was measured by using simultaneous radar and ECG(Electrocardiogram). Arctangent demodulation without dc offset compensation can be applied to transmitted I/Q(In-phase & Quadrature-phase) signal in order to improve the RMSE(Root Mean Square Error) about 50 %. The power leaked to receiving antenna from the transmitting antenna is always generated because of continuously opening the transceiver of CW(Continuous Wave) Doppler radar. As the output power increase, leakage power has an effect on the SNR(Signal-to-Noise Ratio) of the system. Therefore, in this paper, leakage cancellation technique that adds the signal having the opposite phase of the leakage power to the leakage power was implemented in order to minimize the decline of receiver sensitivity. By applying the leakage cancellation techniques described above, it is possible to measure the heart rate and respiration of the human at a distance of up to 35 m. the heart rate of the measured data at a distance of 35 m accords with the heart rate extracted from the ECG data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.9
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• pp.813-821
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• 2013

In this paper, a vital signal sensor based on impedance variation of resonator is presented. Proposed vital signal sensor can detect the vital signal, such as respiration and heart-beat signal. System is composed of resonator, oscillator, surface acoustic wave (SAW) filter, and power detector. The cyclical movement of a dielectric such as a human body, causes the impedance variation of resonator within the near-field range. So oscillator's oscillation frequency variation is effected on resonator's resonant frequency. SAW filter's skirt characteristic of frequency response can be transformed a small amount of frequency deviation to a large variation. Aim to enhance the existing sensor detection range, proposed sensor operates in 870 MHz ISM band, and detect respiration and heart-beat signal at distance of 120 mm.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.4
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• pp.412-417
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• 2022

Capacitive-type humidity sensors with a high sensitivity and fast response/recovery times have attracted a great attention in non-contact respiration biological signal monitoring applications. However, complicated fabrication processes involving high-temperature heat treatment for the hygroscopic film is essential in the conventional ceramic-based humidity sensors. In this study, a non-toxic ceramic/metal halide (BaTiO₃(BT)/NaCl) humidity sensor was prepared at room temperature using a solvent-free aerosol deposition process (AD) without any additional process. Currently prepared BT/NaCl humidity sensor shows an excellent sensitivity (245 pF/RH%) and superior response/recovery times (3s/4s) due to the NaCl ionization effect resulting in an immense interfacial polarization. Furthermore, the non-contact respiration signal variation using the BT/NaCl sensor was determined to be over 700% by maintaining the distance of 20 cm between the individual and the sensor. Through the AD-fabricated sensor in this study, we expect to develop a non-contact biological signal monitoring system that can be applied to various fields such as respiratory disease detection and management, infant respiratory signal observation, and touchless skin moisture sensing button.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.9
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• pp.1010-1019
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• 2008

In this paper, we present a noise analysis and measurement results of a bio-radar system that can detect human heartbeat and respiration signals. The noise analysis including various phase noise effects is very important in designing the bio-radar system, since the frequency difference between the received signal and local oscillator is very small and the received power is very low. All of the noise components in a bio-radar system are considered from the point of view of SNR. From this analysis, it can be concluded that the phase noise due to antenna leakage is a dominant factor and is a function of range correlation. Therefore, the phase noise component with range correlation effect, which is the most important noise contribution, is measured using the measurement setup and compared with the calculated results. From the measurement results, our measurement setup can measure a closed-in phase noise of a free-running oscillator. Based on these results, it is possible to design a 2.4 GHz bio-radar system quantitatively which has a detection range of 50 cm and low power of 1 mW without additional PLL circuits.

• Journal of Biomedical Engineering Research
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• v.16 no.3
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• pp.353-358
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• 1995

The impedance pneumography which is widely used in monitoring respiration is simple to use and noninvasive, but it is sensitive to motion artifacts and insensitive to detect obstructive apnea. A 3-channel respiratory inductive plethysmography (RIP) developed in this study detects inductance change of the inductance band induced by cross-sectional area change of thorax or abdomen as one breathes. It was confirmed that RIP was less sensitive to various motion artifacts but more sensitive to detection of obstructive apnea than impedance pneumography.

• ETRI Journal
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• v.45 no.1
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• pp.105-118
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• 2023

We tested the feasibility of automated discrimination of patients with panic disorder (PD) from healthy controls (HCs) based on multimodal physiological responses using machine learning. Electrocardiogram (ECG), electrodermal activity (EDA), respiration (RESP), and peripheral temperature (PT) of the participants were measured during three experimental phases: rest, stress, and recovery. Eleven physiological features were extracted from each phase and used as input data. Logistic regression (LoR), k-nearest neighbor (KNN), support vector machine (SVM), random forest (RF), and multilayer perceptron (MLP) algorithms were implemented with nested cross-validation. Linear regression analysis showed that ECG and PT features obtained in the stress and recovery phases were significant predictors of PD. We achieved the highest accuracy (75.61%) with MLP using all 33 features. With the exception of MLP, applying the significant predictors led to a higher accuracy than using 24 ECG features. These results suggest that combining multimodal physiological signals measured during various states of autonomic arousal has the potential to differentiate patients with PD from HCs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.1
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• pp.166-174
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• 2013

QRS detection of ECG is the most popular and easy way to detect cardiac-disease. But it is difficult to analyze the ECG signal because of various noise types. The important problem in recording ECG signal is a baseline wandering, which is occurred by rhythm of respiration and muscle contraction attaching to an electrode. Particularly, in the healthcare system that must continuously monitor people's situation, it is necessary to process ECG signal in realtime. In other words, the design of algorithm that exactly detects QRS region using minimal computation by analyzing the person's physical condition and/or environment is needed. Therefore, baseline wander removing method based on morphological filter for efficient QRS detection method is presented in this paper. For this purpose, we detected QRS through the preprocessing method using morphological filter, adaptive threshold, and window. The signal distortion ratio of the proposed method is compared with other filtering method. Also, R wave detection is evaluated by using MIT-BIH arrhythmia database. Experiment result show that proposed method removes baseline wanders effectively without significant morphological distortion.

• Journal of the Korea Society of Computer and Information
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• v.26 no.10
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• pp.139-145
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• 2021

In this paper, by using the cattle feed intake, rumination, and in heat monitoring technology, RFI (Residual Feed Intake) monitoring and wearable devices and PCs for predicting abnormalities in budding target web and smart A monitoring system using a phone application was designed and implemented. With the development of this system, the farmer is expected to increase economic efficiency. By analyzing the feed intake, it is possible to identify the difference between the recommended feed amount based on the cow's weight and the feed amount consumed by the cow, and it is expected that early detection of metabolic disorders (abnormality of metabolism) is possible. Farmers using the results of this thesis can distinguish the cows with the most efficient performance, and the 6-axis motion sensor signals input from the wearable device attached to the cow's skin (neck) and the microphone attached to the wearable device. It is possible to measure the cow's rumination and feed intake through the sound of the cow's throat. In the future, improvements will be made to measure additional vital signs such as heart rate and respiration.