• Journal of Multimedia Information System
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• v.3 no.2
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• pp.1-8
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• 2016

In this paper, we propose a method to automatically diagnose various diseases. The input data consists of electrocardiograph (ECG) recordings. We extract R-to-R interval (RRI) signals from ECG recordings, which are preprocessed to remove trends and ectopic beats, and to keep the signal stationary. After that, we perform some prospective analysis to extract time-domain parameters, frequency-domain parameters, and nonlinear parameters of the signal. Those parameters are unique for each disease and can be used as the statistical symptoms for each disease. Then, we perform feature selection to improve the performance of the diagnosis classifier. We utilize the selected features to diagnose various diseases using machine learning. We subsequently measure the performance of the machine learning classifier to make sure that it will not misdiagnose the diseases. The first two steps, which are R-to-R extraction and preprocessing, have been successfully implemented with satisfactory results.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.127-134
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• 2022

Generally developed for medical testing, electrocardiogram (ECG) recordings seizure the cardiac electrical signals from the surface of the body. ECG study can consequently be a vital first step to support analyze, comprehend, and expect cardiac ailments accountable for 31% of deaths globally. Different tools are used to analyze ECG signals based on computational methods, and explicitly machine learning method. In all abovementioned computational simulations are prevailing tools for cataloging and clustering. This review demonstrates the different effective methods for heart disease based on computational methods for ECG analysis. The accuracy in machine learning and three-dimensional computer simulations, among medical inferences and contributions to medical developments. In the first part the classification and the methods developed to get data and cataloging between standard and abnormal cardiac activity. The second part emphases on patient analysis from entire ECG recordings due to different kind of diseases present. The last part represents the application of wearable devices and interpretation of computer simulated results. Conclusively, the discussion part plans the challenges of ECG investigation and offers a serious valuation of the approaches offered. Different approaches described in this review are a sturdy asset for medicinal encounters and their transformation to the medical world can lead to auspicious developments.

• Journal of Preventive Medicine and Public Health
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• v.37 no.2
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• pp.182-189
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• 2004

Objectives : The objective of this study is to compare the circadian patterns of heart rate variability assessed by 24-hour ambulatory electrocardiographic (ECG) recordings during day shift and night shift among the workers in the 5 days-concecutive-12-hour shift in an automobile factory in Korea. Methods : The study population consisted 300 workers, who were randomly selected among the 8700 total workers in one car factory. To analyse circadian variation, the 24-hour ECG recordings (Marquette) were measured during day shift (08:00-20:00 h) and night shift (20:00-08:00 h). Analysis was performed for all time and frequency domain measures of HRV. 233 workers completed taking 24-hour ECG recordings. Results : This study shows that the 24 hourcircadian variation mainly follows work/sleep cycle rather than day/night cycle among shift workers. This study also shows that among the night shift, the circadian variation between work and sleep cycle decreased compared to the work/sleep cycle among day shift workers. All time and frequency domain parameters (except LF/HF ratio) show significantly different between work and sleep in the day shift and night shift. Conclusion : These changes in heart rate variability circadian rhythms reflect significant reductions in cardiac parasympathetic activity with the most marked reduction in normal vagal activity among the shift workers. Especially, it suggests the circadian rhytm has blunted among the night workers. The quantification of the circadian variation in HRV can be a surrogates of workers' potential health risk, as well as suggests possible mechanisms through which the shift works compromise workers' health.

• Journal of Biomedical Engineering Research
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• v.10 no.3
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• pp.351-360
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• 1989

This paper describes the design of portable arrhythmia monitor and associated algorithm for automated diagnosis based-on microcomputer in the ambulatory ECG recording, analysis, and transmitting to a hospital host computer immediately through the telephone system. The device differs from Molter recorder in that it does not store normal ECG signals but captures and alarms the ECG during suspected abnormal periods and selected temporal epochs to a central hospital site. This porta file arrhythmia monitor makes use of a general purpose computer and software will be changed to meet the custom requirements of individual physicians and patients. At present it is very obvious that each cardiologist has his own method of analyzing ECG recordings and utilizes past experience more than the firm quantitative analysis of data.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.7
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• pp.1331-1338
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• 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
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• 2007.07a
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• pp.1910-1911
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• 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.

• Biomedical Science Letters
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• v.21 no.3
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• pp.135-143
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• 2015

Electrocardiogram measures the electric impulses generated by the heart during its cycle. Recently genome-wide association studies on electrocardiogram traits revealed many relevant genetic loci. Therefore, these findings need to be validated and investigated to determine the underlying mechanisms using mouse models. Invasive radiotelemetry has been widely used to record the electrocardiogram in mice because it has several advantages over non-invasive measurements. However, radiotelemetry is expensive and requires complicated surgery. On the other hand, a non-invasive method using 3 electrodes (one for earth) for lead II is easy to establish and allows for rapid measurement. In this study, eleven mice were measured with this non-invasive method and no statistical difference among them was found in any ECG measurements. In addition, repeat measurement in the same mouse was performed in 9 sets of experiment and the results indicated that non-invasive method was reliable for reproducibility. Further it was shown that measurements for 1, 5, 10, and 15 minutes were not different so that a short recording such as 5 minutes was enough to estimate the ECG values including heart rate. Further this method was validated by measuring the ECG of Balb/c and FVB that were previously shown to differ in ECG values by radiotelemetry. Significant differences were found in heart rate, PR interval and corrected QT interval between these mouse strains. This study partially proved that non-invasive method also could provide the accuracy and reproducibility. Based on these results, the non-invasive ECG recordings of lead II is recommended as a useful method for quick test in mouse model.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.50 no.2
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• pp.163-170
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• 2024

In the literature, inhalation of cosmetic fragrances, including natural extracts or natural essential oils, has been reported to induce brainwave changes. Angelica gigas (AG) and Cnidium officinale (CO) are widely used in East Asian countries as traditional medicines to improve health, but there have been no previous reports of inhaling their aromas and assessing changes in brain activity through electroencephalogram (EEG) recordings. In this study, the scent of natural herbal extracts such as Artemisia princeps var. orientalis (Compositae), AG, and CO was inhaled and evaluated whether emotional state changes were caused by olfactory stimuli, and brain activity was confirmed through EEG records before and after inhaling the scent of natural herbal extracts in subjects aged 20 to 30. We also used an electrocardiogram (ECG) to record the electrical activity of the heart during fragrance administration. The test results indicated that inhaling the scents of Compositae, AG, and CO extracts, as well as the positive control lavender, significantly increased the relative alpha power and the alpha/beta ratio of brain waves across the brain regions. The ECG recordings indicated that the inhalation of Compositae fragrance significantly decreased the low-frequency/high-frequency ratio, and that the inhalation of traditional herbal extract fragrances resulted in comfort and relaxation.

• Journal of Veterinary Clinics
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• v.23 no.3
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• pp.329-333
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• 2006

A 9-month-old neutered male German Shepherd dog was referred with the primary complaint of episodic collapse. Apparent abnormal findings were not observed in physical examination, routine biochemistry, and diagnostic imaging studies. In the 12-lead surface ECG after collapse, the dog showed frequent ventricular premature contractions (VPCs) with torsade de pointes. The frequency of VPCs was reduced after lidocaine infusion. Based on the history, findings in event recordings oi the ECG and lidocaine response test, the dog was diagnosed as inherited malignant ventricular tachyarrhythmia. Although the dog was initially responded to oral sotalol therapy, the dog was died suddenly. This report described the first case of malignant ventricular tachyarrhythmia of German Sheperd in Korea.

• Child Health Nursing Research
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• v.15 no.3
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• pp.299-305
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• 2009

Purpose: Multiple studies have documented that high resting levels of cardiac vagal tone suggest higher levels of self-regulation. The aim of this study was to evaluate cardiac vagal tone as an indicator of autonomic nervous function in healthy newborn and premature infants. Methods: This study was conducted using a descriptive comparison design and a convenience sampling strategy. The participants were 72 healthy and 62 premature infants delivered in a university hospital. Continuous heart rate data recordings from the infant's ECG were analyzed and Mxedit software was used to calculate mean heart period and an index of cardiac vagal tone. Results: The healthy infants had significantly higher cardiac vagal tone than the premature infants, when the influence of gestational age was removed using analysis of covariance. However, there were no significant differences in heart rate and heart period between the two groups when the influence of gestational age was removed using analysis of covariance. Conclusion: The results of this study show that cardiac vagal tone may be used as an index for determining infant's autonomic nervous function. Nursing staff in pediatric departments can use cardiac vagal tone with ease, as this index can be calculated in a noninvasive method from the ECG.