• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.8
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• pp.1947-1954
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• 2013

Previous works for detecting arrhythmia have mostly used nonlinear method such as artificial neural network, fuzzy theory, support vector machine to increase classification accuracy. Most methods require accurate detection of P-QRS-T point, higher computational cost and larger processing time. But it is difficult to detect the P and T wave signal because of person's individual difference. Therefore it is necessary to design efficient algorithm that classifies different arrhythmia in realtime and decreases computational cost by extrating minimal feature. In this paper, we propose arrhythmia detection based on binary coding using QRS feature varibility. For this purpose, we detected R wave, RR interval, QRS width from noise-free ECG signal through the preprocessing method. Also, we classified arrhythmia in realtime by converting threshold variability of feature to binary code. PVC, PAC, Normal, BBB, Paced beat classification is evaluated by using 39 record of MIT-BIH arrhythmia database. The achieved scores indicate the average of 97.18%, 94.14%, 99.83%, 92.77%, 97.48% in PVC, PAC, Normal, BBB, Paced beat classification.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.11 no.2
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• pp.29-33
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• 2012

ECG widely used in cardiac function test is a graph that is recorded by measuring the electrical impulses occurred in the heart. Normal ECG has the form of similar sections that are repeated, and each section has the information occurred in a heart beat. Thus, In order to make the correct diagnosis, correct grasp of the sections and formed analysis must be done. In this research, a system that detects the sections of ECG is proposed. The system is based on ECG stored in the form of files. The ECG can easily have a noise caused by an outside factor. The noise of ECG is easily caused by external factors. Through a band-pass filter, it can be removed. and then, to get this ECG without a noise, interval detection algorithm using R-peak is applied. The clean, intuitive interface will help the above functions to be used without any difficulties.

• The KIPS Transactions:PartC
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• v.13C no.3 s.106
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• pp.311-316
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• 2006

We propose the optical sensor network using optical CDMA with bipolar receiver and modified Pseudorandom Noise codes which are widely used in the wireless communication network. We numerically analyze the performances in the optical sensor network. In the proposed network, multiple access interferences between two sensors are suppressed by performing synchronization between the optical encoder and the optical decoder and adjusting the delay times of optical delay lines. Numerical simulations confirm that the performance can be acquired by suppressing the beat noise among optical signals as the number of sensors increases.

• Journal of Broadcast Engineering
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• v.5 no.2
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• pp.159-166
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• 2000

This paper analyzed the transmission performance when we transmited digital TV signal through analog CATV network. We considered random noise, microreflection, and composite tripple beats as channel impairment factors, and random noise and CTB( Composite Tripple Beat) are modelled as Gaussian distribution and Weibull distribution respectively. Channel modellings for microreflections are classified as three cases, and we exploited carrier recovery and blind equalizer to minimize their effects. We developed a computer simulator for the digital transmission system using DVB-C specification to analyze digital transmission performance, and found BER values according to $E_{b}$/$N_{o}$ for each configuration.

• 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.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.05
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• pp.175-178
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• 1996

The purpose of this thesis is the propose of various signal processing algorithm for the ECG(electrocardiogram) and the design of realtime automated ECG analyzer feasible with these algorithms. The algorithms are composed of (1)filtering procedure fer the estimation and removal of baseline drift, 60Hz power line interference, and muscle artifacts (2)detection procedure of QRS complex and P wave (3)typification procedure for the pattern classification according to the morphologies (4) selection of representative beat, significant point and wave boundary decision procedure and (5) parameter extraction and diagnosis procedure. All verifications are carried out between the algorithms proposed in this paper and other algorithms already proposed by many researchers, for the objective comparison in each procedure. The efficiency of proposed algorithms are demonstrated with the aid of internationally validated CSE database and the performances of filtering procedure are compared on artificial noise signal as well as actual ECG signals with appropriate noise components. for the comparison on the performance of designed automated ECG analyzer, the diagnosis results were compared with ECG analyzer manufactered by Fukuda denshi in Japan.

• 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.28 no.3
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• pp.338-343
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• 2007

BOLD T2*-weighted MR images reflects cortical blood flow and oxygenation alterations. fMRI study relies on the detection of localized changes in BOLD signal intensity. Since fMRI measures the very small modulations in BOLD signal intensity that occur during changes in brain activity, it is also very sensitive to small signal intensity variations caused by physiologic noise during the scan. Due to the complexity of movement of various organs associated with heart beat, it is important to reduce cardiac related noise rather than other physiological noise which could be required with relatively simple method. Therefore, a number of methods have been developed for the estimation and reduction of cardiac noise in fMRI study. But, each method has limitation. In this study, we proposed a new estimation method for brain activities influenced by blood pulsation effect using regression analysis with blood pulsation signal and the correspond slice of fMRI. We could find out that the right anterior cingulate cortex and right olfactory cortex and left olfactory cortex were largely influenced by blood pulsation effect for new method. These observed areas are mostly on the structure of anterior cerebral artery in the brain. That is convinced with that our method would be valid and our new method is easier to apply in practice and reduce computational burden than the retrospective method.

• ETRI Journal
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• v.29 no.2
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• pp.162-168
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• 2007

A new scheme for bi-directional HDTV/Gigabit Ethernet/CATV transmission over a hybrid dense-wavelength-division-multiplexing passive optical network (DWDM-PON) is proposed and demonstrated. It is based on injection-locked vertical-cavity surface-emitting lasers and distributed-feedback laser diodes as transmitters. Services with 129 HDTV channels, a 1.25 Gbps Gigabit Ethernet connection, and 77 CATV channels are successfully demonstrated over 40 km single-mode fiber links. Good performance of bit error rate, carrier-to-noise ratio, composite second order, and composite triple beat is achieved in our proposed bidirectional DWDM-PON.

• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.628-631
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• 2000

A new control method for precision robust speed control of a PMSM(Permanent Magnet Synchronous Motor) using load torque observer is presented. With this system we can obtain more reliable eye moving singal(nystagmus) Until now rotating chair system which is called 2D-optokinetic stimulator is used to make dizzincess. However an inclined rotating chair system witch is 3D-optokinetic stimulator is needed to obtain the precise dizziness data. This 3D-optokinetic sitimulator include unbalanced load aused by unbalanced center of mass. For this case new compensation method is considered to obtain robust speed control using load torque observer. To reduce the effect of this disturbance we can use dead-beat observer which has high gain. The application of the load torque observer is published in [1] for position control. A problem of using speed information such as amplifying effect of noise is reduce by moving average process. The experimental results are depicted in this paper to show the effect of this proposed algorithm.