• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.7
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• pp.898-902
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• 2018

A novel heart beat interval estimation algorithm is presented based on parabola approximation method. This paper presented a two-step processing scheme; a first stage is finding R-peak in the Electrocardiogram (ECG) by Shannon energy envelope estimator and a secondary stage is computing the interpolated peak location by parabola approximation. Experimental results show that the proposed algorithm performs better than with the previous method using low sampled ECG signals.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.825-826
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• 2006

In this paper, we propose an algorithm that applies Rolle's theorem to automatically detect and label peak III and V of the normal, suprathreshold auditory brainstem response (ABR). ABR waveform were recorded from 55 normal-hearing ears at screening levels varying from 30 to 60 dBnHL. For each ABR waveform, the peak-finding algorithm proceeded in fourth steps: (1) Select maximum and minimum values of the target ABR waveform, (2) divide this range into n equal parts, (3) effective candidate peaks in the ABR waveform are identified using Rolle's theorem (4) peak III and V are identified from these candidate peaks based on their latency and morphology. As a result, proposed auto dectection method showed high correlation and accuracy with manual detection method performed by clinician. By using proposed algorithm, clinician can detect and label peak III and V faster and more efficient than manual detection method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.1
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• pp.47-54
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• 2019

An improved method of spectrum detection algorithm for mass spectrum analysis system is proposed. In the conventional spectrum detection algorithm that utilizes the results of the linear approximation and quadratic curve fitting on the ion signal block of each mass index, it is possible to reduce the detection error in the mass spectrum detection by further improving the condition of eliminating the invalid ion signals. Also, the proposed method can reduce the estimation error of the peak value of the mass spectrum by using the result of quadratic curve fitting for the effective ion signal block in which the peak position error is corrected. To evaluate the effectiveness of the proposed method, computer simulations were carried out step by step using the measured ion signal. Also, by comparing the rate of false detection for several inputs, the proposed method showed better detection performance than the conventional method.

• Journal of Biomedical Engineering Research
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• v.35 no.4
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• pp.87-94
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• 2014

Recent technological advances have increased interest in personal health monitoring. Electrocardiogram(ECG) monitoring is a basic healthcare activity and can provide decisive information regarding cardiovascular system status. In this study, we developed a capacitive ECG measurement system that can be included within a cloth mattress pad. The device permits ECG data to be obtained during sleep by using capacitive electrodes. However, it is difficult to detect R-wave peaks automatically because signals obtained from the system can include a high level of noise from various sources. Because R-peak detection is important in ECG applications, we developed an algorithm that can reduce noise and improve detection accuracy under noisy conditions. Algorithm reliability was evaluated by determining its sensitivity(Se), positive predictivity(+P), and error rate(Er) by using data from the MIT-BIH Polysomnographic Database and from our capacitive ECG system. The results showed that Se = 99.75%, +P = 99.77%, and Er = 0.47% for MIT-BIH Polysomnographic Database while Se = 96.47%, +P = 99.32%, and Er = 4.34% for our capacitive ECG system. Based on those results, we conclude that our R-peak detection method is capable of providing useful ECG information, even under noisy signal conditions.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.4
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• pp.292-297
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• 2013

In this paper, unusual waveform detection algorithm based on Refractory Period in arrhythmia ECG signal is proposed. Most of arrhythmia ECG signals consist of unusual waveforms with average 10% rate. Thus tremendous benefit can be obtained in terms of time and cost by providing unusual waveform samples reduced more than 90% to medical staffs who have to monitor and analyze for a long time. The proposed algorithm detects the R-peak using the features of R wave and variable refractory period. For the detected R-peak, unusual waveforms are found using means and standard deviation of electric potential and kurtosis of the R-peaks which are not included in unusual waveform. The proposed algorithm was applied to all records of the MIT-BIH arrhythmia database and showed more than average 90% of compression ratio.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.6
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• pp.390-394
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• 2016

This paper presents a new comparison method for haze-removal algorithms in next-generation automotive systems. Compared to previous peak signal-to-noise ratio-based comparisons, which measure similarity, the proposed modulation transfer function-based method checks sharpness to select a more suitable haze-removal algorithm for lane detection. Among the practical filtering schemes used for a haze-removal algorithm, experimental results show that Gaussian filtering effectively preserves the sharpness of road images, enhancing lane detection accuracy.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.11
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• pp.193-196
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• 1995

An algorithm using topological mapping has been developed for a real-time detection of the QRS complexes of ECG signals. As a measurement of QRS complex energy, we used topological mapping from one dimensional sampled ECG signals to two dimensional vectors. These vectors are reconstructed with the sampled ECG signals and the delayed ones. In this method, the detection rates of CRS complex vary with the parameters such as R-R interval average and peak detection threshold coefficient. We use mean, median, and iterative method to determint R-R interval average and peak estimation. We experiment on various value of search back coefficient and peak detection threshold coefficient to find optimal rule.

• Journal of the Semiconductor & Display Technology
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• v.11 no.3
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• pp.57-61
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• 2012

In order to analyze the ECG, it is important to pinpoint the repeat interval of the ECG. In this paper, we present an efficient algorithm for finding the QRS complex on the ECG. We escaped from the conventional methods to go through multiple steps of preprocessing to make ECG easier to find the QRS complex. We selected the candidate peak that has the possibility of the QRS complex in original ECG, and used technique to find the QRS complex among the candidate peak. In this way, we could get similar efficiency to Pan & Tompkins Algorithm that is most representative QRS complex detection algorithm, just used fewer operations than Pan & Tompkins Algorithm.

• Journal of Communications and Networks
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• v.11 no.6
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• pp.556-563
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• 2009

A side channel analysis is a very efficient attack against small devices such as smart cards and wireless sensor nodes. In this paper, we propose an efficient key detection method using a peak selection algorithm in order to find the advanced encryption standard secret key from electromagnetic signals. The proposed method is applied to a correlation electromagnetic analysis (CEMA) attack against a wireless sensor node. Our approach results in increase in the correlation coefficient in comparison with the general CEMA. The experimental results show that the proposed method can efficiently and reliably uncover the entire 128-bit key with a small number of traces, whereas some extant methods can reveal only partial subkeys by using a large number of traces in the same conditions.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2008.05a
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• pp.383-386
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• 2008

We developed a fiber-optic Bragg grating sensor system using a SOA fiber laser for over heat detection in power systems. To compensate the nonlinear wavelength tuning of the fiber laser, we used fixed passband wavelengths from Fabry-Perot ITU filter as reference wavelengths. Gaussian line-fitting algorithm was also used to reduce the FBG peak detection error. Compared with a highest-peak-detection and a polynomial-fitting method, the proposed Gaussian fitting algorithm could drastically reduce the measurement errors. Also the SOA fiber laser made it possible to enhance the signal-to-noise-ratio even with several kilometers of lead fiber.