• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.6
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• pp.865-871
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• 2012

In this study, ambulatory electrocardiogram(ECG) signal and the rhythms of heart beats are visualized in terms of R-R intervals and Heart Rate Variability(HRV) in the environment of an android plaform. With this aim, Graphical User Interface(GUI) is implemented by executing multi-thread Java programming modules including ECG, heart-beats, tachogram and visualization unit. ECG signals are acquired in an android device by receiving the data from ambulatory ECG sensory system. Finite Impulse Response(FIR) filters are implemented to eliminate the baseline wandering noises contained in the ambulatory signals and DC-offset level in R-R interval data. With simulating the normal or stress emotional state of a subject, we can find the fact that HRV can be successfully estimated and visualized in an android smart phone platform.

• Proceedings of the KOSOMBE Conference
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• v.1990 no.11
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• pp.110-113
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• 1990

A new approach to impulsive noise rejection and background normalization of digitized electrocardiogram signals is presented using mathematical morphological operators that incoporate the shape information of a signal. A brief introduction to these nonlinear signal processing operators, as well as detailed description of the new algorithm, is presented. Empirical results show that the new algorithm has good performance in impulsive noise rejection and background normalization.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.1
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• pp.166-174
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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. The important problem in recording ECG signal is a baseline wandering, which is occurred by rhythm of respiration and muscle contraction attaching to an electrode. Particularly, 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 region using minimal computation by analyzing the person's physical condition and/or environment is needed. Therefore, baseline wander removing method based on morphological filter for efficient QRS detection method is presented in this paper. For this purpose, we detected QRS through the preprocessing method using morphological filter, adaptive threshold, and window. The signal distortion ratio of the proposed method is compared with other filtering method. Also, R wave detection is evaluated by using MIT-BIH arrhythmia database. Experiment result show that proposed method removes baseline wanders effectively without significant morphological distortion.

• The Journal of Korean Institute of Information Technology
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• v.15 no.12
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• pp.157-164
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• 2017

Mobile ECG signal measurement is a technique to measure small signals of several mV, and many studies have been conducted to remove noise including wandering scheme. Removal of the equipotential line noise caused by shaking or movement of the electrode cable is one of the core research contents for the electrocardiogram measurement. In this study, we proposed a modified step-size of combined NLMS(normalized least squares) and DLMS(delayed least squares) adaptive filter to eliminate baseline noise from ECG signals. The proposed method mainly adjusts initial filter step-size to reduce distortion of original ECG signals characteristic after eliminating baseline noise. The modified filter step-size is scaled by filter order size and distortion minimization factor. This method is suitable for portable ECG device with a small processor and less power consumption. This technique also decreases computation time which is essential for real-time filtering. The proposed filter also increase the signal to noise ratio (SNR) compared to conventional NLMS filter.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.10
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• pp.1518-1523
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• 2012

In this study, the novel digital filtering algorithms are implemented to suppress the noisy characteristics embedded in ambulatory electrocardiogram signals by an android smartphone platform. With this aim, Graphical User Interface (GUI) is designed and implemented by utilizing multithread-Java programming to realize Finite Impulse Response and Infinite Impulse Response filter. With simulating our implemented digital filters built in an android smartphone, we can find the fact that we can efficiently suppresses the noisy characteristics due to baseline wandering and 60 Hz powerline source fluctuations especially in electrocardiograms.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.6
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• pp.825-832
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• 2013

In this study, Independent Component Analysis (ICA) algorithms are suggested to extract the original ECG part from the mixed signal contaminated with the unwanted frequency components and especially 60Hz power line disturbances. With this aim, we implement a novel method to suppress the baseline-wandering disturbances and power line artefacts contained in patch-electrodes sensory ECG data by separating the unmixed signal with finding the optimal weight W based on Kurtosis value. With applying brutal force and gradient ascent searching algorithm to find W, we can conclude that the unwanted frequency components especially in the ambulatory ECG data can be eliminated by Independent Component Analysis.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.920-923
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• 2003

An wearable electrocardiogram (ECG) monitoring system is a widely used non-invasive diagnostic tool for ambulatory patient who may be at risk from latent life-threatening cardiac abnormalities. In this paper, we have a portable ECG monitoring system with conductive fiber which was characterized by the small-size and the low power consumption. The system consists of conductive fibers, one-chip microcontroller, ECG preprocessing circuit, and monitoring software to be able to record and analyze in PC. ECG preprocessing circuit is made of pre-amplifier with gain of 10, band-pass filter with bandwidth of 0.5-120Hz and 2.5V offset circuit for A/D conversion. ECG signals obtained by sensor are included with corrupted noises such as a baseline wandering, 60 Hz power noise and interference noise by body movement. For cancellation corrupted noises in signals obtained by conductive fiber, we used the wavelet decomposition of wavelet transforms in MATLAB toolbox.

• The KIPS Transactions:PartB
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• v.18B no.6
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• pp.341-348
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• 2011

ECG(Electrocardiogram), a field of Bio-signal, is generally experimented with classification algorithms most of which are SVM(Support Vector Machine), MLP(Multilayer Perceptron). But this study modified the Random Forest Algorithm along the basis of signal characteristics and comparatively analyzed the accuracies of modified algorithm with those of SVM and MLP to prove the ability of modified algorithm. The R-R interval extracted from ECG is used in this study and the results of established researches which experimented co-equal data are also comparatively analyzed. As a result, modified RF Classifier showed better consequences than SVM classifier, MLP classifier and other researches' results in accuracy category. The Band-pass filter is used to extract R-R interval in pre-processing stage. However, the Wavelet transform, median filter, and finite impulse response filter in addition to Band-pass filter are often used in experiment of ECG. After this study, selection of the filters efficiently deleting the baseline wandering in pre-processing stage and study of the methods correctly extracting the R-R interval are needed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.1
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• pp.174-183
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• 2011

This paper is about a bar code decoding algorithm developed for smart phone applications. The algorithm consists of bar code data extraction procedure, bar code signal estimation procedure, and bar code decoding procedure. To detect the peak bar code module, a DSTW had been applied because of its outstanding performance in ECG peak detection. In order to minimize errors due to non-uniform light effect, the proposed algorithm was acted as a baseline wandering filter based on module peaks detection. The algorithm had been tested to evaluate the performance under the conditions of blurring, non-uniformed light and white noises. The algorithm had shown excellent performance in reconstruction of bar code decoding, compared to other conventional methods. In order to show the possibility of applying the algorithm to a smart phone, a real UPC-A type 150 bar code pictures obtained from a smart phone camera was applied to the algorithm, achieving the correct recognition rate of 97.33%.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.5
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• pp.48-58
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• 1998

In this paper, we proposed a new algorithm using characteristics of th ereconstructed phase trajectory by topological mapping developed for a real-tiem detection of the QRS complexes of ECG signals. Using fill-factor algorithm and mutual information algorithm which are in genral used to find out the chaotic characteristics of sampled signals, we inferred the proper mapping parameter, time delay, in ECG signals and investigated QRS detection rates with varying time delay in QRS complex detection. And we compared experimental time dealy with the theoretical one. As a result, it shows that the experimental time dealy which is proper in topological mapping from ECG signals is 20ms and theoretical time delays of fill-factor algorithm and mutual information algorithm are 20.+-.0.76ms and 28.+-.3.51ms, respectively. From these results, we could easily infer that the fill-factor algorithm in topological mapping from one-dimensional sampled ECG signals to two-dimensional vectors, is a useful algorithm for the detemination of the proper ECG signals to two-dimensional vectors, is a useful algorithm for the detemination of the proper time delay. Also with the proposed algorithm which is very simple and robust to low-frequency noise as like baseline wandering, we could detect QRS complex in real-time by simplifying preprocessing stages. For the evaluation, we implemented the proposed algorithm in C-language and applied the MIT/BIH arrhythmia database of 48 patients. The proposed algorithm provides a good performance, a 99.58% detection rate.