• Advances in Traditional Medicine
• /
• v.10 no.4
• /
• pp.278-287
• /
• 2010

The present study was undertaken to evaluate the protective effect of ethanol (EtAS), ethyl acetate (EAAS) and aqueous (AQAS) extracts of Argyreia speciosa (AS) roots against Isoproterenol (ISO)-induced myocardial infarction in rats. The animals were exposed to isoproterenol (200 mg/kg. s.c) twice at an interval of 24 hrs. Cardioprotective effect was assessed by observing ECG parameters, serum marker enzymes and histopathology of the heart. Pretreatment of EAAS, and EtAS (200 mg/kg) resulted in a significant (P < 0.001) increase in P wave, QRS complex and R-R interval, whereas heart rate, QT interval and cardiac cycle were maintained near to normal values. EtAS and EAAS showed significant (P < 0.05; P < 0.001) reduction in all the tested diagnostic markers compared to ISO treated group. Histological studies on the structural changes of heart tissue supported the protective activity of AS. The result suggest that treatment of AS prior to ISO has a significant role in protecting the animals from ISO induced myocardial infarction.

• Journal of Multimedia Information System
• /
• v.3 no.2
• /
• pp.35-42
• /
• 2016

Electrocardiogram (ECG) signal gives a clear indication whether the heart is at a healthy status or not as the early notification of a cardiac problem in the heart could save the patient's life. Several methods were launched to clarify how to diagnose the abnormality over the ECG signal waves. However, some of them face the problem of lack of accuracy at diagnosis phase of their work. In this research, we present an accurate and successive method for the diagnosis of abnormality through Discrete Wavelet Transform (DWT), QRS complex detection and Support Vector Machines (SVM) classification with overall accuracy rate 95.26%. DWT Refers to sampling any kind of discrete wavelet transform, while SVM is known as a model with related learning algorithm, which is based on supervised learning that perform regression analysis and classification over the data sample. We have tested the ECG signals for 10 patients from different file formats collected from PhysioNet database to observe accuracy level for each patient who needs ECG data to be processed. The results will be presented, in terms of accuracy that ranged from 92.1% to 97.6% and diagnosis status that is classified as either normal or abnormal factors.

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

• Proceedings of the KOSOMBE Conference
• /
• v.1996 no.11
• /
• pp.217-220
• /
• 1996

In this paper, we compare three mehods to obtain PSD of HRV - FFT, AR modeling, and residual integration. Using these methods we speculate the balances of the LP and HF powers of HRV at $0^{\circ}$, $45^{\circ}$, $90^{\circ}$ tilt levels of head-up tilt table for young and healthy 24 men. R peaks are located at the highest point of QRS complex detected from modified spacial velocity algorithm. In general FFT is the most fast way to obtain PSD but PSD from FFT has too many peaks and valleies. AR PSD can show frequency of ANS activity effectively but LF component of PSD is often invisible due to interference of VLF power. The residual integration method that decomposes the AR PSD is very efficient way to extract LF component. Applying the above three methods to HRV we can visualize the trend of PSD variations along tilt levels.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.18 no.8
• /
• pp.2008-2016
• /
• 2014

With the increased attention about health care and management of heart diseases, ubiquitous healthcare services and related devices have been actively developed recently. In this paper we developed a mobile healthcare system which consists of smartphone and patch-type ECG measuring device. This system is capable of monitoring, storing, and sending bio signals such as ECG, heart rate, heart rate variability as well as exercise management functions through heart rate zones. With monitoring bio signal continuously by mobile healthcare system and wearable device like us, people can prevent chronic disease and maintain good health. Here we report our implementation results on real platforms.

• 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.

• Journal of Biomedical Engineering Research
• /
• v.43 no.6
• /
• pp.399-408
• /
• 2022

Because arrhythmia occurs irregularly, it should be examined for at least 24 hours for accurate diagnosis. For this reason, this paper developed firmware software for arrhythmia detection and prevented consumption of temporal and human resources and enabled continuous management and early diagnosis. Prior to the experiment, the interval between the R peaks of the QRS Complex was calculated using the Pan-Tompkins algorithm. The developed firmware software designed and implemented an algorithm to detect arrhythmia such as tachycardia, bradycardia, ventricular tachycardia, persistent tachycardia, and non-persistent tachycardia, and a data transmission format to monitor the collected data based on BLE. As a result of the experiment, arrhythmia was found in real time according to the change in BPM as designed in this paper. And the data quality for BLE communication was verified by comparing the sensor's serial communication value with the Android application reception value. In the future, wearable devices for real-time arrhythmia detection will be lightweight and developed firmware software will be applied.

• Journal of Ginseng Research
• /
• v.39 no.3
• /
• pp.206-212
• /
• 2015

Background: Ginseng total saponin (GTS) contains various ginsenosides. These ginsenosides are widely used for treating cardiovascular diseases in Asian communities. The aim of this study was to study the effects of GTS on cardiac injury after global ischemia and reperfusion (I/R) in isolated guinea pig hearts. Methods: Animals were subjected to normothermic ischemia for 60 minutes, followed by 120 minutes of reperfusion. GTS significantly increased aortic flow, coronary flow, and cardiac output. Moreover, GTS significantly increased left ventricular systolic pressure and the maximal rate of contraction ($+dP/dt_{max}$) and relaxation ($-dP/dt_{max}$). In addition, GTS has been shown to ameliorate electrocardiographic changes such as the QRS complex, QT interval, and RR interval. Results: GTS significantly suppressed the biochemical parameters (i.e., lactate dehydrogenase, creatine kinase-MB fraction, and cardiac troponin I levels) and normalized the oxidative stress markers (i.e., malondialdehyde, glutathione, and nitrite). In addition, GTS also markedly inhibits the expression of interleukin-$1{\beta}$ (IL-$1{\beta}$), IL-6, and nuclear factor-${\kappa}B$, and improves the expression of IL-10 in cardiac tissue. Conclusion: These data indicate that GTS mitigates myocardial damage by modulating the biochemical and oxidative stress related to cardiac I/R injury.

• Journal of Sensor Science and Technology
• /
• v.13 no.5
• /
• pp.383-391
• /
• 2004

In this study, we implemented the pulse transit time (PTT) system to examine usefulness of the monitoring method of distensibility and elasticity using photoplethysmography sensor in vivo. PTT is defined as the time interval between the peak of QRS complex in ECG signal and the maximum slope point of photoplethysmography. these two signals were converted to digital data by means of AID converter, then PTT was evaluated by heartbeat using PC. Results of analysis were displayed as a graph using spline interpolation method. The variance of PTT was measured repetitiously to verify efficiency of PTT system in resting state and hyperemic state. Repeated measurement of PTT was not same value but showed that coefficients of correlation were related with each other as 0.8302 (P<0.01) in resting state. And also repeated measurement of PTT showed significant correlation as 0.868 (P<0.01) in the hyperemic state. These result showed that PTT is reflect on transient pressure variance in the artery and is very useful method for the evaluation of prognosis of the hypertension and arteriosclerosis.

• Journal of Biomedical Engineering Research
• /
• v.28 no.4
• /
• pp.530-538
• /
• 2007

Magnetocardiography (MCG) is a device to measure the magnetic field from the heart. It is a noninvasive device and takes only few minutes to record magnetocardiogram from a subject. In this study, we compared the difference of MCG data recorded from 56 normal subjects in early twenties (28 males and 28 females, mean $age=21.0{\pm}1.6$ years) and 36 elderly subjects (20 males and 16 females, mean $age=61.9{\pm}6.9$ years) for the analysis of the age and gender difference. A total of 24 parameters used in the analysis were derived from QRS complex, R-wave, T-wave, and ST-T period. As a result, seven parameters including maximum current angle and map angle showed the significant difference (p<0.01 and p<0.05, respectively) between young males and young females. Significant difference (p<0.05) between elderly males and elderly females was found from a parameter, pole distance at T-wave peak. In the comparison of age difference, seven parameters regarding current moment, pole distance, and dynamics showed the significant difference between young and elderly males. Eight parameters also showed significant difference (p<0.05) between two younger and elderly female groups. Results showed that parameters regarding current moment, pole distance, and dynamics might be changed when people get older. In conclusion, gender and age difference should be considered when MCG data are analyzed for certain parameters.