• Journal of the Institute of Convergence Signal Processing
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• v.20 no.1
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• pp.51-56
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• 2019

This paper proposes an improved heartbeat signal extraction method for ballistocardiography(BCG)-based heart-rate measurement on mobile environment. First, from a mobile facial video, a handshake-free head motion signal is extracted by tracking facial features and background features at the same time. Then, a novel signal periodicity computation method is proposed to accurately separate out the heartbeat signal from the head motion signal. The proposed method could robustly extract heartbeat signals from mobile facial videos, and enabled more accurate heart rate measurement (measurement errors were reduced by 3-4 bpm) compared to the existing method.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.39-42
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• 1988

In speech signal processing, it is necessary to estimate exactly the pitch. We propose a new algorithm which uses the correlation coefficient between the original and the repeated segmental waveform in the frame as a parameter in the pitch extraction. The correlation coefficient in the frame reflects the periodic component and the transient ratio of the waveform.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.519-526
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• 2013

ECG signal has the feature that is repeated in a cycle of P, Q, R, S, and T waves and is sampled at a high sampling frequency in general. By using the feature of periodic ECG signals, maximizing compression efficiency while minimizing the loss of important information for diagnosis is required. However, the periodic characteristics of such amplitude and period is not constant by measuring time and patients. Even though measured at the same time, the patient's characteristics display different periodic intervals. In this paper, an adaptive multi-level coding is provided by coding adaptively the dominant and non-dominant signal interval of the ECG signal. The proposed method can maximize the compression efficiency by using a multi-level code that applies different compression ratios considering information loss associated with the dominant signal intervals and non-dominant signal intervals. For the case of long time measurement, this method has a merit of maximizing compression ratio compared with existing compression methods that do not use the periodicity of the ECG signal and for the lossless compression coding of non-dominant signal intervals, the method has an advantage that can be stored without loss of information. The effectiveness of the ECG signal compression is proved throughout the experiment on ECG signal of MIT-BIH arrhythmia database.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.4
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• pp.1050-1056
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• 1994

When a vibration data for a rotating machine such as a pump or a compressor is concerned, the frequency fluctuation of the energy contents at an instant time may provide useful information on understanding the vibration characteristics of the rotating machinery, rather than the averaged energy distribution along the frequency axis. Especially, when a periodic signal has different spectral contents, the approach to use the averaged frequency distribution, called the normal frequency analysis, may not be appropriate to extract vibration source characteristics of the structure. This paper introduces a way to analyze the signal based on an instant time. In order to evaluate the performance of the various approach, the investigatation compares three different algorithms which are frequently implemented in the instantaneous frequency analysis. Also for the noise effect embodied in the true signal, various cases for different SN ratio have been examined. The result shows that the noise level is crucial to evalute the instantaneous frequency analysis. In order to implement the instantaneous frequency analysis, the extraction of the relevant information from the measured signal should have the high S/N ratio, i, e., 40 dB or above.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.6
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• pp.67-75
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• 1993

ECG pattern was classified using a back-propagation neural network. An improved feature extractor of ECG is proposed for better classification capability. It is consisted of preprocessing ECG signal by an FIR filter faster than conventional one by a factor of 5. QRS complex recognition by moving-window integration, and peak extraction by quadratic approximation. Since the FIR filter had a periodic frequency spectrum, only one-fifth of usual processing time was required. Also, segmentation of ECG signal followed by quadratic approximation of each segment enabled accurate detection of both P and T waves. When improtant features were extracted and fed into back-propagation neural network for pattern classification, the required number of nodes in hidden and input layers was reduced compared to using raw data as an input, also reducing the necessary time for study. Accurate pattern classification was possible by an appropriate feature selection.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2007.05a
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• pp.274-279
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• 2007

The fault identification of electrical rotating machinery have been special interests due to one of important elements in the industrial production line. It is directly related with products quality and production costs. The sudden breakdown of a motor will affect to the shut down of the whole processes. Therefore, rotating machines are required to a periodic diagnosis and maintenance for improving its reliability and increasing their lifetime. The objective of this work is to develop the diagnosis system with current signals for the effective identification of healthy and faulty motors using the developed diagnosis algorithm, which consists of the feature calculation, feature extraction, and feature classification procedures.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.11 no.1
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• pp.48-60
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• 2007

Palpation of the pulse has been used in Korean traditional medicine since ancient times to assess physical health. Pulse wave contour may be obtained by measuring arterial pressure or blood volume change of skin. The latter is called as Photoplethysmography(PPG) or digital volume pulse(DVP). The PPG signal is measured by a device comprising an infrared light sourece and a photodetector. Although less widely used, this technique deserves further consideration because of its simplicity and ease of use. The contour of the PPG is formed as a result of a complex interaction between the left ventricle and the systemic circulation. It usually exhibits an early systolic peak and an early diastolic peak. the first peak is formed mainly by pressure trasmitted along a direct path from the left ventricle to the finger. The second peak is formed in part by pressure transmitted along the aorta and large arteries to sites of impedance mismatch in the lower body. The contour of the PPG is sensitive to changes in arterial tone and is influenced by ageing and large artery stiffness. Measurements taken directly from the PPG or from its second derivative can be used to assess these properties. In some mathematical approaches, the extraction of periodic components using frequency analysis was tried to analysis of the PPG. But we don't understand yet what kind of factor in the cardiovascular system or human body is related with the respective specific Fourier components of PPG. This review describes the background to measurement principles, representative contour, contour analysis and frequency domain analysis of PPG, and current and future.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.12A
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• pp.1279-1284
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• 2004

In this paper, we propose a novel and simple optical technique for the detection of subcarrier-multiplexed(SCM) labels using optical interleavers. Optical-baseband packet signals with suppressed subcarriers appear at the through-pass port of the optical interleaver and SCM labels with suppressed optical carrier exit from the optical SCM extraction port. Since it does not require optical circulators, this structure shows less insertion loss than the previously proposed optical label detectors. The periodic nature of the interleaver transfer function makes it possible to detect multiple SCM channels simultaneously from an incoming wavelength-multiplexed signal stream. Detection of a 155-Mb/s ASK modulated 9.79-GHz subcarrier using a 10-GHz SCM optical label detector has been performed successfully and verified through optical spectra and bi t-error-rate measurements.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.6
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• pp.690-699
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• 2014

Jet engine modulation(JEM) is a technique used to identify the jet engine type from the radar target signature modulated by periodic rotation of the jet engine mounted on the aircraft target. As a new approach of JEM, this paper proposes an automatic algorithm for extracting the jet engine information. First, the rotation period of the jet engine is yielded from auto-correlation of the JEM signal preprocessed by complex empirical mode decomposition(CEMD). Then, the final blade number is estimated by introducing the DM(Divisor-Multiplier) rule and the 'Scoring' concept into JEM spectral analysis. Application results of the simulated and measured JEM signals demonstrated that the proposed algorithm is effective in accurate and automatic extraction of the jet engine information.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.5
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• pp.33-42
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• 2010

In this study, we have proposed a simple cardiorespiratory monitoring method based on displacements of human body which occurs due to periodic heartbeat and breathing. The proposed system consists of an aircushion, pressure sensing hardware and heartbeat and respiration signals extraction algorithm. The aircushion was used for unconstrained measurement of the respiration and heartbeats without a sensor attached on the subject's skin surface. The displacements of subject sitting on the aircushion cause small pressure variations. These variations are amplified and filtered with the pressure sensing hardware. Finally, heart rate and respiration rate are extracted by signal processing algorithm based on frequency domain filter. To evaluate the performance, extracted respiration and heart rate from proposed system were compared with conventional methods. The average sensitivity of respiration and heart rate are 98.67% and 99.24%, respectively. These results show the proposed method has advantages of installing and processing simplicity so as to be used easily in unconstrained respiration and heart rate monitoring in daily life.