• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.04a
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• pp.929-932
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• 2012

Beat map shows the distribution property of the beating sound in the bell structure. Using the beat map, beat control and beat estimation are available. To draw the beat map, mode pair parameters of the bell are required. However, in case of large bell which is struck by a heavy wooden hammer, it is very difficult to measure the excitation force and to obtain the mode pair parameters. In this paper, we determined the mode pair parameters of the bell from the transmissibility between the roving signal and reference signal, using ODS(operational deflection shape) method. The mode pair data are input to the theoretical model of the beat response and beating waves are generated on the bell circumference. All the numerical and beat map drawing procedures are automatized using Matlab. Finally, the reliability of the beat map generated by the program is verified.

• Journal of Biomedical Engineering Research
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• v.24 no.3
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• pp.151-158
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• 2003

Numerous studies of short-term, beat-to-beat variability in cardiovascular signals have used linear analysis techniques. However, no study has been done about the appropriateness of linear techniques or the comparison between linearities and nonlinearities in short-term, beat-to-beat variability. This paper aims to verify the appropriateness of linear techniques by investigating nonlinearities in short-term, beat-to-beat variability. We compared linear autoregressive moving average(ARMA) with nonlinear neural network(NN) models for predicting current instantaneous heart rate(HR) and mean arterial blood pressure(BP) from past HRs and BPs. To evaluate these models. we used HR and BP time series from the MIMIC database. Experimental results indicate that NN-based nonlinearities do not play a significant role and suggest that 10 technique provides adequate characterization of the system dynamics responsible for generating short-term, beat-to-beat variability.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.10
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• pp.2187-2193
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• 2010

A specific radar system can be implemented more easily using the frequency modulated continuous wave comparing with the pulse Doppler radar. It also has the advantage of LPI (low probability of interception) because of the low power and wide bandwidth characteristics. These radars are usually used to cover the short range area and to obtain the high resolution measurements of the target range and velocity information. The transmitted waveform is used in the mixer to demodulate the received echo signal and the resulting beat signal can be obtained. This beat signal is analyzed using the FFT method for the purpose of clutter removal, detection of a target, extraction of velocity and range information, etc. However, for the case of short signal acquisition time, this FFT method can cause the serious leakage effect which disables the detection of weaker echo signals masked by strong side lobes of the clutter. Therefore, in this paper, the weighting window method is analyzed to suppress the strong side lobes while maintaining the proper main lobe width. Also, the results of FFT beat spectrum analysis are shown under various environments.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1206-1210
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• 2005

This paper presents performance improvement in optical CDMA system under the presence of beat noise using a cancellation technique. Optical fibers and atmospheric optical communications have been proposed the connection between base stations and central station. The optical signal beat noise is due to interference between lightwave, many optical waves are simultaneously incident on each receiver photodiode. Since the photodiode acts as a square-law detector, beat noise can occur in the receiver. While A two-stage cancellation technique is analyzed and verified via simulation employed here because of its system simplicity. By using the random ingredients of all user signals are estimated, the beat noise is rebuilt and removed from the intended signal. In addition to cancellation technique cancel the inherent multiuser interference (MUI) in CDMA system and nonlinear distortion (NLD) in optical system. It is performed at the receiver of the central station where the random ingredients of all user signals are estimated and the MUI and the NLD are rebuilt and removed from the received signal. The validity of the cancellation technique is theoretically analyzed and shown by numerical results. The increasing of capacity in two stage cancellation are obtained.

• IEMEK Journal of Embedded Systems and Applications
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• v.5 no.2
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• pp.93-102
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• 2010

The FMCW(Frequency Modulation Continuous Wave) radar possesses range-velocity ambiguity to identify the correct combination of beat frequencies for each target in the multi-target situation. It can lead to ghost targets and missing targets, and it can reduce the detection probability. In this pap er, we propose an effective identification algorithm for the correct pairs of beat frequencies and the signal processing hardware architecture to effectively support the algorithm. First, using the correlation of the detected up- and down-beat frequencies and Doppler frequencies, the possible combinations are determined. Then, final pairing algorithm is completed with the power spectrum density of the correlated up- and down-beat frequencies. The proposed hardware processor has the basic architecture consisting of beat-frequency registers, pairing table memory, and decision unit. This method will be useful to improve the radar detection probability and reduce the false alarm rate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.9
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• pp.1840-1846
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• 2011

It is necessary to estimate the Doppler spectrum for each range cell for the extraction of useful information from the return echoes in radar systems used for the remote sensing purpose such as detection of moving targets and weather surveillance. The signal amplitude in the beat frequency band is the important parameter in the detection and tracking of targets. However, strong clutter echoes do exist in most radar operation environments and the system phase noise spreads both the clutter and signal echoes of the target. In this paper, the effects of this system phase noise are analyzed concerning the clutter and the signal beat spectrum. It is shown that the separation capability of adjacent beat signal depends on the degree of spread in the clutter and beat signal caused by the radar system phase noise

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.30-40
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• 2022

Electrocardiogram (ECG) signal's shape and characteristic varies through each individual, so it is difficult to classify with one neural network. It is difficult to classify the given data directly, but if corresponding normal beat is given, it is relatively easy and accurate to classify the beat by comparing two beats. In this study, we classify the ECG signal by generating the reference normal beat through the template cluster, and combining with the input ECG signal. It is possible to detect abnormal beats of various individual's records with one neural network by learning and classifying with the imaged ECG beats which are combined with corresponding reference normal beat. Especially, various neural networks, such as GoogLeNet, ResNet, and DarkNet, showed excellent performance when using the comparative learning. Also, we can confirmed that GoogLeNet has 99.72% sensitivity, which is the highest performance of the three neural networks.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.493-496
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• 2005

For home healthcare, the unconstrained measurement of physiological signal is highly required to avoid the inconvenience of users. The recording and analysis of the fundamental parameters during sleep like respiration and heart beat provide valuable information on his/her healthcare. Using the air mattress sensor system, the respiration and heart beat movements can be measured without any harness or sensor on the subject's body. The differential measurement technique between two air cells is adopted to enhance the sensitivity. The balancing tube between two air cells is used to increase the robustness against postural changes during the measurement period. The meaningful frequency range could be selected by the pneumatic filter with balancing tube. ECG (Electrocardiography) and respiration sensor (plethysmography) were measured for comparison with the signal from air mattress. To extract the heart beat information from air pressure sensor, digital signal processing technique was used. The accuracy for breathing interval and heart beat monitoring was acceptable. It shows the potentials of air mattress sensor system to be the unconstrained home sleep monitoring system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.4
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• pp.731-739
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• 2015

In arrhythmia ECG signal, abnormal beat that has various abnormal shape depending on the generation site and conduction disorders is included and it is very important to diagnose heart disease such as arrhythmia. In this paper, we propose a PVC abnormal beat detection algorithm associated with ventricular disease. The PVC abnormal beat is characterized by distortion of the QRS complex occurs among the components of the ECG signal. Therefore it is possible to detect PVC abnormal beat according to the degree of distortion of the QRS complex. First, quantify the distortion of the QRS complex by using the potential of the R-peak, kurtosis and period. By using the mean and standard deviation, PVC abnormal beat is detected depending on the degree of distortion from the normal beat. The proposed algorithm can detect the average over 98% of the AAMI-V class type abnormal beat associated with ventricular disease in MIT-BIH arrhythmia database.

• Journal of Biomedical Engineering Research
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• v.36 no.5
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• pp.143-149
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• 2015

In this paper, we proposed a novel method for automatic detection for snoring and heart beat using a single piezoelectric sensor. For this study multi-rate signal processing technique was applied to detect snoring and heart beat from the single source signal. The sound event duration and intensity features were used to snore detection and heart beat was found by autocorrelation. The performance of the proposed method was evaluated on clinical database, which is the nocturnal piezoelectric snoring data of 30 patients that suffered obstructive sleep apnea. The method achieved sensitivity of 88.6%, specificity of 96.1% with accuracy of 95.6% for snoring and sensitivity of 94.1% and positive predictive value of 87.6% for heart beat, respectively. These results suggest that the proposed method can be a useful tool in sleep monitoring and sleep disordered breathing diagnosis.