• Journal of the Korean Institute of Telematics and Electronics D
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• v.36D no.6
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• pp.87-96
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• 1999

For analog optical transmission of narrow-band microwave signal, a novel all-optical linearization technique of electro-absorption (EA) optical modulator by using dual modulation scheme is proposed and theoretically investigated. By using the dual modulation scheme where the sub-modulator has a different length, DC bias and band-gap wavelength, the DC bias operation point where the third-order intermodulation products of ~30dB and the following increase of spurious free dynamic range (SFDR) of ~20dB wave achieved in sub-octave narrow band operation.

• Journal of the Korea Society of Computer and Information
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• v.11 no.5 s.43
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• pp.267-272
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• 2006

In this paper, an integrated and small Ka-band transceiver module has been developed for measuring distance at the radar systems. Oscillator of cavity type, The MMIC such as VCO, power amplifier, LNA, and mixer, and passive components are integrated on carriers and these are assembled in the transceiver module directly. The test result shows the output power of 21dBm and the noise figure of 5dB using developed transceiver module. Using developed FMCW transceiver module. We can measure the 60m range target by detecting the beat frequency and distinguish both earth and sky using radiometer signal. So we defined that the integrated module using MMIC had a good performance for the radar and radiometer at Ka-band.

• Journal of Sensor Science and Technology
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• v.22 no.5
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• pp.338-345
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• 2013

Premature ventricular contractions are the most common of all arrhythmias and may cause more serious situation like ventricular fibrillation and ventricular tachycardia in some patients. Therefore, the detection of this arrhythmia becomes crucial in the early diagnosis and the prevention of possible life threatening cardiac diseases. Most methods for detecting arrhythmia require pp interval, or the diversity of P wave morphology, but they are difficult to detect the p wave signal because of various noise types. Thus, it is necessary to use noise-free R wave. So, the new approach for the detection of PVC is presented based on the rhythm analysis and the beat matching in this paper. For this purpose, we removed baseline wandering of low frequency band and made summed signals that are composed of two high frequency bands including the frequency component of QRS complex using the wavelet filter. And then we designed R wave detection algorithm using the adaptive threshold and window through RR interval. Also, we developed algorithm to classify PVC using RR interval. The performance of R wave and PVC detection is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate average detection rate of 99.76%, sensitivity of 99.30% and specificity of 98.66%; accuracy respectively for R wave and PVC detection.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.1
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• pp.82-89
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• 2014

This paper discusses the methods for reducing the sampling time quantization errors of the body dither type ring laser gyroscope. A ring laser gyroscope has the angle quantization error which is generated by the frequency counting method of the laser beat signal and sampling time quantization error which is generated by the demodulation method for eliminating the body dithering in which the sampling periods are fitted to the dither periods. Generally, because the dither periods are longer than the calculation periods of the inertial navigation system, vehicle navigation errors are produced by long time attitude update missing during the vehicle move with a high dynamical motion. In this paper, the double demodulation method is proposed for reducing the sampling time quantization error and its effects under the dynamic situation are confirmed by simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.8A
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• pp.1163-1168
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• 1999

This paper proposes a wireless positioning method using the CDMA mobile communicaton network. The proposed method is time-based positioning method that uses mobile-station arrival time of forward link signal from base-stations. In this mehtod there are TDOA and TOA methods that use time-difference-of-arrival and time-of-arrival, respectively. Error characteristics and implementation simplicity of the two methods are compared and analyzed each other. As a results, it showed that TDOA has advantage of less sensitivity to the time error compared to TOA but has disadantage of more sensitivity to the spatial error. Also, from architecture of the CDMA system that is time synchronized to only active base-station it is analyzed that adoption of TDOA method is more advantageous than TOA because time difference of signal arrival from the neighbor base-stations against the active base-station can be measured more easily. Therefore, conclusion is made that TDOA is beat suit to the time-based positioning method for the present CDMA mobile communication networkgorithm performs block-by-block coherent decoding with the aid of pilot symbols. It is shown that the complexity of the algorithm grows linearly as a function of sequence length. The performance of the algorithm is shown to better than that of the conventional pilot symbol aided (PSI) algorithm. Simulation results are presented to assess the performance of the algorithm and the results are compared with that of the conventional PSI alforithm.

• Journal of the Korea Society of Computer and Information
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• v.26 no.7
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• pp.29-36
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• 2021

In this paper, we classify ECG signal data for mobile devices using deep learning models. To classify abnormal heartbeats with high accuracy, three factors of the deep learning model are selected, and the classification accuracy is compared according to the changes in the conditions of the factors. We apply a CNN model that can self-extract features of ECG data and compare the performance of a total of 48 combinations by combining conditions of the depth of model, optimization method, and activation functions that compose the model. Deriving the combination of conditions with the highest accuracy, we obtained the highest classification accuracy of 97.88% when we applied 19 convolutional layers, an optimization method SGD, and an activation function Mish. In this experiment, we confirmed the suitability of feature extraction and abnormal beat detection of 1-channel ECG signals using CNN.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.3
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• pp.38-46
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• 2012

Atrial fibrillation is needed to be detected at paroxysmal stage and to be treated. But, paroxysmal atrial fibrillation ECG is hardly obtained with 12-lead electrocardiographs but Holter systems. Presently, the averaged beat subtraction(ABS) method is solely used to estimate atrial fibrillatory waves even with somewhat large residual error. As an alternative, in this study, we suggested an ESAF(event-synchronous adaptive filter) based algorithm, in which the AF ECG was treated as a primary input and event-synchronous impulse train(ESIT) as a reference. And, ESIT was generated so to be synchronized with the ventricular activity by detecting QRS complex. We tested proposed algorithm with simulated AF ECGs and real AF ECGs. As results, even with low computational cost, this ESAF based algorithm showed better performance than the ABS method and comparable performance to algorithm based on PCA(principal component analysis) or SVD(singular value decomposition). We also proposed an expanded version of ESAF for some AF ECGs with multi-morphologic ventricular activities and this also showed reasonable performance. Ultimately, with Holter systems including our proposed algorithm, atrial activity signal can be precisely estimated in real-time so that it will be possible to calculate atrial fibrillatory rate and to evaluate the effect of anti-arrhythmic drugs.

• Journal of the Korea Society of Computer and Information
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• v.15 no.2
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• pp.65-74
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• 2010

We propose a system that automatically recognizes the tense or relaxed condition of scrolling-shooting game subject that plays. Existing study compares the changed values of source of stimulation to the player by suggesting the source, and thus involves limitation in automatic classification. This study applies SOM of unsupervised learning for automatic classification and recognition of player's condition change. Application of SOM for automatic recognition of tense and relaxed condition is composed of two steps. First, ECG measurement and analysis, is to extract characteristic vector through HRV analysis by measuring ECG after having the player play the game. Secondly, SOM learning and recognition, is to classify and recognize the tense and relaxed conditions of player through SOM learning of the input vectors of heart beat signals that the characteristic extracted. Experiment results are divided into three groups. The first is HRV frequency change and the second the SOM learning results of heart beat signal. The third is the analysis of match rate to identify SOM learning performance. As a result of matching the LF/HF ratio of HRV frequency analysis to the distance of winner neuron of SOM based on 1.5, a match rate of 72% performance in average was shown.

• Journal of Navigation and Port Research
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• v.28 no.6
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• pp.497-501
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• 2004

In this paper, it is presented a level sensor for measuring a level of the contents of cargo tank using frequency modulated continuous wave(FMCW). The frequency range is 10∼11 GHz, the radar cross section(RCS) of test target is $0.8\textrm{m}^2$ of metal plate. The experiment is performed in laboratory and open ground, the sweep time of the signal is 100 ms, the pyramidal horn antenna of about 22 dBi gain is used, and input power of antenna is about 8 dBm The beat frequency according to the target moving to 40 m is measured. There is a good agreement between measured and calculated results. But the resolution of the FMCW radar is measured about 10 cm due to nonlinear of voltage controlled oscillator(VCO).

• Journal of Biomedical Engineering Research
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• v.28 no.4
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• pp.503-511
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• 2007

Heart rate variability(HRV) is the clinical consequence of various influences of the autonomic nervous system(ANS) on heart beat. HRV can estimate the potential physiologic rhythm from the interval between consecutive beats(RR interval or HRV data), but cardiovascular system governed by ANS is in relation to respiration and autonomic regulation. It is known as RSA representing respiration-related HR rhythmic oscillation. Because the mechanism linking the variability of HR to respiration is complex, it has so far been unknown well. In this paper, we tried to evaluate 5-min RR interval segments under control of respiration in order to find out a proper respiration rate that can estimate the ANS function. 10 healthy volunteers were included to evaluate 5-min HRV data under 4 different respiration-controlled environments; 0.03Hz, 0.1Hz, 0.2Hz, and 0.4Hz respiration. HRV data were analyzed both in the frequency and the time domain, with cross-correlation coefficient(cross-coeff.) for HRV and respiration signal. The results showed maximum cross-coeff. of 0.84 at 0.1 Hz and minimum that of 0.16 at 0.4Hz respiration. Cross-coeff was decreased at a faster rate from 0.1Hz respiration. All mean SDNN, RMSSD, and pNN50 of time domain measures were 108.7ms, 71.85ms, and 28.47%, respectively, and LF, HF, and TP of frequency domain measures were $12,722ms^2,\;658.8ms^2$, and $7,836.64ms^2$ at 0.1Hz respiration, respectively. In conclusion, 0.1Hz respiration was observed to be very meaningful from time domain and frequency domain analysis in relation to respiration and autonomic regulation of the heart.