• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.3
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• pp.705-711
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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. Also 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 wave using minimal computation and classifies PVC by analyzing the persons's physical condition and/or environment is needed. Thus, efficient QRS detection and PVC classification based on profiling method is presented in this paper. For this purpose, we detected QRS through the preprocessing method using morphological filter, adaptive threshold, and window. Also, we applied profiling method to classify each patient's normal cardiac behavior through hash function. The performance of R wave detection, normal beat and PVC classification is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.77% in R wave detection and the rate of 0.65% in normal beat classification error and 93.29% in PVC classification.

• Journal of Biomedical Engineering Research
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• v.20 no.3
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• pp.299-305
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• 1999

In thls paper, the representative beal textraction algorIthms for the diagnostic parameter extraction in noisy signal were compared. We used the avernge, median, mode, and trmmed mean to calculale the central tendency. In our experimenl, we have restricted to four kinds of noises -EMG noise, 60Hz powerline inlerference, ahrupl baseline shift, and baselme drift due to respimtion-which were commonly occurred in ECG mgnal, then we have calculated signal-to-noise ratios(SNRs) for the ECG corrupted with each noise and all noises together. As the result of this paper, we have proved that the average method has super lor performance than the others in the ECG corrupted wilh EMG noise. When the signal mcludes extreme value such as abrupt baseline shIft, the median, mode, trimmed mean methods have supenor performance in the SNR ratios. Especially when the ECG corrupted with baseline drift due to respirallon, the trimmed mean method was most efficient because ST level change was 0 V.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.4
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• pp.377-387
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• 2016

Design of X-band frequency FMCW based imaging radar with multi-resolutions and performances of the self-manufactured radar system are presented in this study. In order to implement the multi-bandwidths, a ramp sequence of the FMCW signal is consisting of two kinds of 'saw-tooth' waveform with different bandwidth, and a receiver circuit consisting of L-band source and frequency converter circuit is used to effectively extract spectra of beat-frequency from the received signal of X-band frequency. The system setups for performance measurement of self-manufactured radar system are maximum output power of 35 dBm, sampling frequency of 1.2 MHz and sweep time of 1 ms. Then, the measured resolutions of the modulated signal having bandwidth of 500 MHz and 300 MHz in range & azimuth-direction are (0.28 m, 0.26 m) and (0.44 m, 0.27 m), respectively.

• Journal of Biomedical Engineering Research
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• v.29 no.4
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• pp.278-285
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• 2008

In this study the complex-valued continuous wavelet transform (CWT) has been applied in detection of Electrocardiograms (ECG) as response to various signal classification methods such as Fourier transforms and other tools of time frequency analysis. Experiments have shown that CWT may serve as a detector of non-stationary signal changes as ECG. The tested signal is corrupted by short time events. We applied CWT to detect short-time event and the result image representation of the signal has showed us that one can easily find the discontinuity at the time scale representation. Analysis of ECG signal using complex-valued continuous wavelet transform is the first step to detect possible changes and alternans. In the second step, modulus and phase must be thoroughly examined. Thus, short time events in the ECG signal, and other important characteristic points such as frequency overlapping, wave onsets/offsets extrema and discontinuities even inflection points are found to be detectable. We have proved that the complex-valued CWT can be used as a powerful detector in ECG signal analysis.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.4
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• pp.427-436
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• 1999

This paper describes an ECG signal labeling algorithm based on fuzzy clustering, which is very useful to the automated ECG diagnosis. The existing labeling methods compares the crosscorrelations of each wave form using IF-THEN binary logic, which tends to recognize the same wave forms such as different things when the wave forms have a little morphological variation. To prevent this error, we have proposed as ECG signal labeling algorithm using fuzzy clustering. The center and the membership function of a cluster is calculated by a cluster validity function. The dominant cluster type is determined by RR interval, and the representative beat of each cluster is determined by MF (Membership Function). The problem of IF-THEN binary logic is solved by FCM (Fuzzy C-Means). The MF and the result of FCM can be effectively used in the automated fuzzy inference -ECG diagnosis.

• Korean Journal of Optics and Photonics
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• v.14 no.2
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• pp.161-165
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• 2003

Optical 60 ㎓ millimeter-wave (MMW) signal generation is demonstrated using the sideband injection-locking method in the master/slave configuration, where two slave lasers are locked to two among several side-bands produced by the direct rf-modulation of a master laser. These two locked slave laser outputs beat against each other in the photo-detector and produce stable and very pure 60 ㎓ signals.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2511-2517
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• 2009

Recently, a FMCW radar is used for the various purposes in the short range detection and tracking of targets. The main advantages of a FMCWradar are the comparative simplicity of implementation and the low peak power transmission characterizing the very low probability of signal interception. Since it uses the frequency modulated continuous wave for transmission and demodulation, the received beat frequency represents the range and Doppler information of targets. Detection and extraction of useful information from targets are performed in this beat frequency domain. Therefore, the resolution and accuracy in the estimation of a beat spectrum are very important. However, using the conventional FFT estimation method, the high resolution spectrum estimation with a low sidelobe level is not possible if the acquisition time is very short in receiving target echoes. This kind of problems deteriorates the detection performance of adjacent targets having the large magnitude differences in return echoes and also degrades the reliability of the extracted information. Therefore, in this paper, the model parameter estimation methods such as autoregressive and eigenvector spectrum estimation are applied to mitigate these problems. Also, simulation results are compared and analyzed for further improvement.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.331-334
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• 1998

In this paper, we have presented an improved design of the microwave level meter based on the principle of FM-CW radar. First, we have analyzed the effect of VCO nonlinearity on the spectral broadening of the beat signal, and presented a new type of design theory to linearize VCO tuning curve adopting FFT algorithm. Simulation results for a VCO having the linearity of 25% have been presented, which show the usefulness of the design algorithm.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.163-166
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• 2001

본 논문에서는 ITS(Intelligent Transportation System) 기술중의 하나인 차량 충돌 방지 시스템의 신호처리부를 설계 구현하였다. 제안된 시스템은 FMCW (Frequency Modulated Continuous Wave)방식의 770Hz 밀리미터파 레이더를 기준으로 파라미터 값을 설계하여 거리와 속도를 실시간 검출하도록 구현되었다. 제안된 시스템은 TI사의 TMS320C31-40 DSP 와 AT89C52 Bbit 마이크로프로세서로 구현되어 10Hz 이상의 갱신율, 0.2m의 거리 분해능 및 2knvh의 속도 분해능을 제공하고 있다. 실험 환경으로 주파수 발생기(Function Generator)에서 비트주파수(Beat Frequency)를 생성하여 동작을 확인하였다.

• Journal of Biomedical Engineering Research
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• v.35 no.3
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• pp.42-49
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• 2014

We propose an individual identification method using a single-lead electrocardiogram signal. In this paper, lead I ECG is measured from subjects in various physical and psychological states. We performed a noise reduction for lead I signal as a preprocessing stage and this signal is used to acquire the representative beat waveform for individuals by utilizing the ensemble average. From the P-QRS-T waves, features are extracted to identify individuals, 19 using the duration and amplitude information, and 16 from the QRS complex acquired by applying Pan-Tompkins algorithm to the ensemble averaged waveform. To analyze the effect of each feature and to improve efficiency while maintaining the performance, Relief-F algorithm is used to select features from the 35 features extracted. Some or all of these 35 features were used in the support vector machine (SVM) learning and tests. The classification accuracy using the entire feature set was 98.34%. Experimental results show that it is possible to identify a person by features extracted from limb lead I signal only.