• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.56 no.7
• /
• pp.1331-1338
• /
• 2007

A new method for detecting and eliminating the Electrocardiogram(ECG) artifact from the scalp Electroencephalogram(EEG) is proposed. Based on the single channel EEG, the proposed method consists of 4 procedures: emphasizing the R-wave of ECG artifact from EEG using the least squares acceleration(LSA) filter, detecting the R-wave from the LSA filtered EEG using the phase space method and R-R interval, generating the delayed impulse synchronized to the R-wave and elimination of the ECG artifacts based on the adaptive digital filter using the impulse and raw EEG. The performance of the proposed method was evaluated in the two separating parts of R-wave detection and, ECG estimation and elimination from EEG. In the R-wave detection, the proposed method showed the mean error rate of 6.285(%). In the ECG estimation and elimination using simulated and/or real EEG recordings, we found that the ECG artifacts were successfully estimated and eliminated in comparison with the conventional multi-channel techniques, in which independent component analysis and ensemble average method are used. From this we can conclude that the proposed method is useful for the detecting and eliminating the ECG artifact from single channel EEG and simple for ambulatory/portable EEG monitoring system.

• Proceedings of the KIEE Conference
• /
• 2007.07a
• /
• pp.1910-1911
• /
• 2007

A new method for estimating and eliminating electrocardiogram (ECG) artifacts from single channel scalp electroencephalogram (EEG) is proposed. The proposed method consists of emphasis of QRS complex from EEG using least squares acceleration (LSA) filter, generation of synchronized pulse with R-peak and ECG artifacts estimation and elimination using adaptive filter. The performance of the proposed method was evaluated using simulated and real EEG recordings, we found that the ECG artifacts were successfully estimated and eliminated in comparison with the conventional multi-channel techniques, which are independent component analysis (ICA) and ensemble average (EA) method. In conclusion, we can conclude that the proposed method is useful for the detecting and eliminating the ECG artifacts from single channel EEG and simple to use for ambulatory/portable EEG monitoring system.

• The Journal of the Korea Contents Association
• /
• v.21 no.2
• /
• pp.140-147
• /
• 2021

EEG(electroencephalogram) are measured to accurately determine the level of sleep in various sleep examinations. In general, measurements are more accurate as the number of sensor channels increases. EEG can interfere with sleep by attaching electrodes to the skin when measuring. It is necessary for self sleep care to select the minimum number of EEG channels that take into account both the user's discomfort and the accuracy of the measurement data. In this paper, we proposed a sleep stage analysis model based on machine learning and conducted experiments for using from one channel to four channels. We obtained estimation accuracy for sleep stage as following 82.28% for one channel, 85.77% for two channels, 80.33% for three channels and 68.87% for four channels. Although the measurement location is limited, the results of this study compare the accuracy according to the number of channels and provide information on the selection of channel numbers in the EEG sleep analysis.

• Journal of Biomedical Engineering Research
• /
• v.26 no.1
• /
• pp.49-54
• /
• 2005

This paper presents a design of 1-channel active dry electrode module for EEG from one's forehead. The IA(instrumentation amplifier) circuit inside the module is based on the configuration sown on the paper MettingVanRijn et al. We analyze the IA circuit to find out the related equation, and then compare its simulated characteristic with the result obtained from the real active dry electrode circuit. With the active dry electrode and the wet(Ag/AgCI) electrode connected to the separated analog processing module on one's forehead at the same time, their real time and FFT outputs of EEG are examined for comparison. The active dry electrode module has advantages over the wet electrode and its analog processing module: 1) The size of the analog processing circuit of the active dry electrode module is smaller than that of existing EEG analog processing module; 2) the total cost required to make the proposed analog processing circuit is much lower than that of the existing circuit, since the designed circuit needs smaller parts; 3) the electrical characteristic is comparable to the general EEG analog processing module even if the designed module has simpler circuit configuration.

• Journal of Biomedical Engineering Research
• /
• v.20 no.1
• /
• pp.81-90
• /
• 1999

This paper describes an EEG(electroencephalogram) software for two-channel cerebral function monitoring system to detect the cerebral ischemia. In the software, two-channel bipolar analog EEG signals are digitized and from the signals various EEG parameters are extracted and displayed on a monitor in real-time. Digitized EEG signal is transformed by FFT(Fast Fourier transform) and represented as CSA(compressed spectral array) and DSA(density spectral array). Additional 5 parameters, such as alpha ratio, percent delta, spectral edge frequency, total power, and difference in total power, are estimated using the FFT spectra. All of these are effectively merged in a monitor and displayed in real-time. Through animal experiments and clinical trials on men, the software is modified and enhanced. Since the software provides raw EEG, CSA, DSA, simultaneously with additional 5 parameters in a monitor, it is possible to observe patients multilaterally. For easy comparison of patient's status, reference patterns of CSA, DSA can be captured and displayed on top of the monitor. And user can mark events of surgical operation and patient's conditions on the software, this allow him jump to the points of events directly, when reviewing the recorded EEG file afterwards. Other functions, such as forward/backward jump, gain control, file management are equipped and these are operated by simple mouse click. Clinical tests in a university hospital show that the software responds accurately according to the conditions of patients and medical doctors can use the software easily.

• Korean Journal of Acupuncture
• /
• v.20 no.3
• /
• pp.49-60
• /
• 2003

The aim of this study was to examine the effects of electroacupuncture(EA) at the PC6 (Naegwan) on normal humans using KarhunenLoeve decomposition method. Electroencephalogram(EEG) is a multi-scaled signal consisting of several components of time series with different dominant frequency ranges and different origins. EEG KarhunenLoeve decomposition method exibit site-specific and state-related differences in specific frequency bands. In this study, KarhunenLoeve decomposition method was used as a measure(D2) of complexity. 30 channel EEG study was carried out in 10 subjects (10 males; $age=21.4{\pm}0.5$ years). Results : We found that the average values and standard deviations of D2 at FP1, FP2, FTC1, FTC2, TT1, TT2, T4, TCP1, P3, P4, T6, OZ channel (p<0.05) were higher than during the acupuncture treatment, and the average values and standard deviations of D2 at F3, F8 channels(p<0.05) were lowered than during the acupuncture treatment. However, the comparison with that before and after the treatment shows no significant differences in all channels.

• Journal of Biomedical Engineering Research
• /
• v.32 no.4
• /
• pp.295-304
• /
• 2011

In this study, we evaluated the EEG based BCI algorithm using common spatial pattern to find realistic applicability using neurofeedback EEG based BCI algorithm - EEG mode, feature vector calculation, the number of selected channels, 3 types of classifier, window size is evaluated for 10 subjects. The experimental results have been evaluated depending on conditioned experiment whether neurofeedback is used or not In case of using neurofeedback, a few subjects presented exceptional but general tendency presented the performance improvement Through this study, we found a motivation of development for the specific classifier based BCI system and the assessment evaluation system. We proposed a need for an optimized algorithm applicable to the robust motor imagery evaluation system with more useful functionalities.

• Journal of Biomedical Engineering Research
• /
• v.29 no.1
• /
• pp.17-24
• /
• 2008

The aim of this paper is to report our preliminary results of investigating the spatial focalization of Zen-meditation EEG (electroencephalograph) in alpha band (8-13 Hz). For comparison, the study involved two groups of subjects, practitioners (experimental group) and non-practitioners (control group). To extract EEG alpha rhythm, wavelet analysis was applied to multi-channel EEG signals. Normalized alpha-power vectors were then constructed from spatial distribution of alpha powers, that were classified by Fuzzy C-means based algorithm to explore various brain spatial characteristics during meditation (or, at rest). Optimal number of clusters was determined by correlation coefficients of the membership-value vectors of each cluster center. Our results show that, in the experimental group, the incidence of frontal alpha activity varied in accordance with the meditation stage. The results demonstrated three different spatiotemporal modules consisting with three distinctive meditation stages normally recognized by meditation practitioners. The frontal alpha activity in two groups decreased in different ways. Particularly, monotonic decline was observed in the control group, and the experimental group showed increasing results. The phenomenon might imply various mechanisms employed by meditation and relaxation in modulating parietal alpha.

• Journal of Acupuncture Research
• /
• v.19 no.3
• /
• pp.26-40
• /
• 2002

Objective : The aim of this study was to examine the effects of electroacupuncture(EA) at the PC6 (Naegwan) on nomal humans using power spectrum analysis. Methods : Electroencephalogram(EEG) is a multi-scaled signal consisting of several components of time series with different dominant frequency ranges and different origins. EEG power spectrum exibit site-specific and state-related differences in specific frequency bands. In this study, power spectrum was used as a measure of complexity. 30 channel EEG study was carried out in 8 subjects (8 males; age=$21.4{\pm}0.5$ years). Results : We found that the power values of the alpha wave at F7 channel (P<0.05) were highered than during the acupuncture treatment, and the power values of the delta wave at TCP1, CP1, TCP2, T5 channels(P<0.05) were lowered than during the acupuncture treatment. However, the comparison with that before and after the treatment shows no significant differences in all channels.

• Journal of Acupuncture Research
• /
• v.18 no.2
• /
• pp.67-78
• /
• 2001

The aim of this study was to examine the effects of low frequency electroacupuncture(EA) at the $B_{62}$ (Shinmaek) $K_6$(Chohae) on vascular dementia in humans using nonlinear dynamics. Electroencephalogram(EEG) is a multi-scaled signal consisting of several components of time series with different dominant frequency ranges and different origins. Nonlinear measures of the EEG like the correlation dimension ($D_2$) and the first positive Lyapunov exponent ($L_1$) reflect the complexity of the EEG. In this study, $D_2$ was used as a measure of complexity. Sixteen channel EEG study was carried out in six subjects (5 females and 1 males; $age=83.83{\pm}7.19years$). We found that the baseline $D_2$ values of the EEG at F4 and F8 channels (P<0.01) were lowered than during the acupuncture treatment, indicating decreased complexity of the EEG. However, the comparison with that before and after the treatment shows no significant differences in all channels.