• Electronics and Telecommunications Trends
• /
• v.38 no.5
• /
• pp.61-70
• /
• 2023

We investigated technological trends in an electrocardiogram (ECG)-based biometric cryptosystem that uses physiological features of ECG signals to provide personally identifiable cryptographic key generation and authentication services. The following technical details of the cryptosystem were investigated and analyzed: preprocessing of ECG signals, extraction of personally identifiable features, generation of quantified encryption keys from ECG signals, reproduction of ECG encryption keys under time-varying noise, and new security applications based on ECG signals. The cryptosystem can be used as a security technology to protect users from hacking, information leakage, and malfunctioning attacks in wearable/implantable medical devices, wireless body area networks, and mobile healthcare services.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.67 no.7
• /
• pp.898-902
• /
• 2018

A novel heart beat interval estimation algorithm is presented based on parabola approximation method. This paper presented a two-step processing scheme; a first stage is finding R-peak in the Electrocardiogram (ECG) by Shannon energy envelope estimator and a secondary stage is computing the interpolated peak location by parabola approximation. Experimental results show that the proposed algorithm performs better than with the previous method using low sampled ECG signals.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.05a
• /
• pp.237-240
• /
• 2009

We suggested the portable measurement system that estimate heart-condition for heart disease patients and healthy. We used informations of ECG and PCG in this system. The informations of ECG and PCG obtained by using electrodes and microphone, respectively.

• The Journal of Internal Korean Medicine
• /
• v.29 no.4
• /
• pp.1130-1137
• /
• 2008

Objectives : Oriental medical doctors usually use the three-finger pulse diagnosis method to observe disease. Since it is difficult to diagnose ischemic heart disease (IHD) objectively by this diagnostic method, we performed the study to diagnose it as soon as possible by using Yuk Bu Jung Wee Jin Mac(六部定位診脈) and electrocardiogram(ECG). Methods : Patients who had abdominal discomfort were observed by Yuk Bu Jung Wee Jin Mac(六部定位診脈) and we presumed they had heart disease and checked them with electrocardiogram(ECG). Results : We diagnosed it early by using Yuk Bu Jung Wee Jin Mac(六部定位診脈) and electrocardiogram (ECG). Conclusions : The study suggests that it is easy to diagnose IHD early using Yuk Bu Jung Wee Jin Mac(六部定位診脈) and ECG. More data related to IHD is needed.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.60 no.3
• /
• pp.654-661
• /
• 2011

This paper is about a personal identification algorithm using an ECG that has been studied by a few researchers recently. Previously published algorithm can be classified as two methods. One is the method that analyzes of ECG features and the other is the morphological analysis of ECG. The main characteristic of proposed algorithm can be classified the method of analysis ECG features. Proposed algorithm adopts DSTW(Down Slope Trace Wave) for extracting ECG features, and applies SVM(Support Vector Machine) to training and testing as a classifier algorithm. We choose 18 ECG files from MIT-BIH Normal Sinus Rhythm Database for estimating of algorithm performance. The algorithm extracts 100 heartbeats from each ECG file, and use 40 heartbeats for training and 60 heartbeats for testing. The proposed algorithm shows clearly superior performance in all ECG data, amounting to 93.89% heartbeat recognition rate and 100% ECG recognition rate.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.4
• /
• pp.611-616
• /
• 2023

ECG(electrocardiogram) is a test used to measure the rate and regularity of heartbeats, as well as the size and position of the chambers, the presence of any damage to the heart, and the cause of all heart diseases can be found. Because the ECG signal obtained using the ECG-KIT includes noise in the ECG signal, noise must be removed from the ECG signal to apply to the deep learning. In this paper, the noise of the ECG signal was removed using the digital IIR Butterworth low-pass filter. When the performance evaluation of the three activation functions, sigmoid(), ReLU(), and tanh() functions, was compared using the deep learning model of LSTM, it was confirmed that the activation function with the smallest error was the tanh() function. Also, When the performance evaluation and elapsed time were compared for LSTM and GRU models, it was confirmed that the GRU model was superior to the LSTM model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2008.05a
• /
• pp.285-288
• /
• 2008

In ubiquitous computing environment the biological signal ECG (Electrocardiogram signal) is usually recorded with noise components. Adaptive interference (or noise) canceller do adaptive filtering of the noise reference input to maximally match and subtract out noise or interference from the primary (signal plus noise) input thereby adaptively eliminate unwanted interference from the ECG signal. Measured Stress ECG (or exercise ECG signal) signal have three major noisy component like baseline wander noise, motion artifact noise and EMG (Electro-mayo-cardiogram) noise. These noises are not only distorted signal but also root of incorrect diagnosis while ECG data are analyzed. Motion artifact and EMG noises behave like wide band spectrum signals, and they considerably do overlapping with the ECG spectrum. Here the multidimensional adaptive method used for filtering which is more effective to improve signal to noise ratio.

• Proceedings of the IEEK Conference
• /
• 2009.05a
• /
• pp.193-195
• /
• 2009

In this paper, we propose an effective compression method for electrocardiogram(ECG) signals. 1-D ECG signals are reconstructed to 2-D ECG data by period and complexity sorting schemes with image compression techniques to Increase inter and intra-beat correlation. The proposed method added block division and mean-period normalization techniques on top of conventional 2-D data ECG compression methods. JPEG 2000 is chosen for compression of 2-D ECG data. Standard MIT-BIH arrhythmia database is used for evaluation and experiment. The results show that the proposed method outperforms compared to the most recent literature especially in case of high compression rate.

• Biomedical Science Letters
• /
• v.21 no.3
• /
• pp.135-143
• /
• 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 Biomedical Engineering Research
• /
• v.28 no.4
• /
• pp.441-448
• /
• 2007

Heart rate variability (HRV) in electrocardiogram (ECG) is an important index for understanding the health status of heart and the autonomic nervous system. Most HRV analysis approaches are based on the proper heart rate (HR) data. Estimation of heart rate is thus a key process in the HRV study. In this paper, we report an innovative method to estimate the heart rate. This method is mainly based on the concept of periodicity transform (PT) and instantaneous period (IP) estimate. The method presented is accordingly called the "PT-IP method." It does not require ECG R-wave detection and thus possesses robust noise-immune capability. While the noise contamination, ECG time-varying morphology, and subjects' physiological variations make the R-wave detection a difficult task, this method can help us effectively estimate HR for medical research and clinical diagnosis. The results of estimating HR from empirical ECG data verify the efficacy and reliability of the proposed method.