Mi-Hye Song

Adaptive Noise Canceling of Electrocardiogram Artifacts in Single Channel Electroencephalogram

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. From this 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.

New real-time heartbeat detection method using the angle of a single-lead electrocardiogram

This study presents a new real-time heartbeat detection algorithm using the geometric angle between two consecutive samples of single-lead electrocardiogram (ECG) signals. The angle was adopted as a new index representing the slope of ECG signal. The method consists of three steps: elimination of high-frequency noise, calculation of the angle of ECG signal, and detection of R-waves using a simple adaptive thresholding technique. The MIT-BIH arrhythmia database, QT database, European ST-T database, T-wave alternans database and synthesized ECG signals were used to evaluate the performance of the proposed algorithm and compare with the results of other methods suggested in literature. The proposed method shows a high detection rate-99.95% of the sensitivity, 99.95% of the positive predictivity, and 0.10% of the fail detection rate on the four databases. The result shows that the proposed method can yield better or comparable performance than other literature despite the relatively simple process. The proposed algorithm needs only a single-lead ECG, and involves a simple and quick calculation. Moreover, it does not require post-processing to enhance the detection. Thus, it can be effectively applied to various real-time healthcare and medical devices.

A New Acupuncture Point Detection Using the Impedance Measurement System Based on ANF and Phase-Space-Method

In this study, a new method for acupuncture point detection using the impedance measurement system based on the PSM (phase space method) is presented. The developed device has been developed as detectors for acupuncture points which are used for diagnosis and treatment in acupuncture. In this system, multi-frequency current injection and voltage measurements are both performed by the surface electrodes, which are controlled by a microcontroller. Also, the microcontroller process continuous time demodulation of the modulated signal by multi frequency components using the adaptive notch filter. After that, PSM is applied about each frequency using an acupuncture equivalent model which is proposed in the pre-study.

The Novel Method for the Fetal Electrocardiogram Extraction from the Abdominal Signal

In this paper, we have proposed a new method to extract the fetal ECG from a pregnant womans abdominal signal using least square acceleration (LSA) filter and adaptive impulse correlation (AIC) filter. To evaluate the performance, the proposed method and other fetal ECG extraction techniques were processed using the synthetic and real ECG data and then the results were compared. According to comparative results, the proposed method is powerful and successful for extracting the fetal ECG. It was able to separate perfectly even though the fetal beats overlap with the QRS wave of the maternal beats and to extract fetal ECG using any single-channel abdominal signal measured from pregnant womans abdominal surface. Also, it could be implemented easily by fast computation time and simple structure. It is sure that our method could be useful for portable fetal monitoring system.

Development of Mobile Units and Integrated System for Emergency

In this study, we developed six types of mobile units and an integrated system which can manage vital signs from each unit using Bluetooth wireless communication. The six kinds of mobile unit were so designed that each has different function to be applied according to the condition of patient properly. The mobile units can measure ECG signal of single or 12 channel, blood pressure, pulse and SpO2 signal from a patient. Also, to reduce the uncomfortable measurement, several types of units such as belt type, wrist type and necklace type were designed. Our proposed system can integrate and monitor several biological signals from different patients by using Bluetooth wireless communication simultaneously. The developed system was evaluated in the simulated emergent situation and showed the system can monitor 6 patients in maximum according to the data quality. It showed the possibilities that the developed system can be used effectively for emergency situation or in- or out-hospital transport of patient. In future, with the combination of mobile communication technique, a patient who is in emergency situation can be provided with proper first-aid and a doctor can pile the information of patient and give better diagnosis and treatments

A ventricular activity cancellation algorithm based on event synchronous adaptive filter for single-lead electrocardiograms

Recently, it has become very important to analyze atrial activity (AA) and to detect arrhythmic AAs and, for this, complete ventricular activity (VA) cancellation is prerequisite. There have been several VA cancellation algorithms for multi-lead ECG but VA cancellation algorithm for single-lead is quite a few. In this study, we have modeled thoracic ECG and, based on this model, proposed a novel VA cancellation algorithm based on event synchronous adaptive filter (ESAF). In this ESAF, the AF ECG was treated as a primary input and event-synchronous impulse train (ESIT) as a reference. And, ESIT was generated so to be synchronized with the ventricular activity by detecting QRS complex. To evaluate the performance, it was applied to the AA estimation problem in atrial fibrillation electrocardiograms. As results, even with low computational cost, this ESAF based algorithm showed better performance than the ABS method and comparable performance to algorithm based on PCA (principal component analysis) or SVD (singular value decomposition). We also proposed an expanded version of ESAF for some AF ECGs with bimorphic VAs and this also showed reasonable performance. Ultimately, our proposed algorithm was found to estimate AA precisely even though it is possible to implement in real-time. We expect our algorithm to replace the most widely used method, that is, the ABS (averaged beat subtraction) method.

Development of Mobile Monitoring System for Emergency Situation

In this paper, we have developed a mobile biosignal monitoring system which was able to measure and transmit the bio-signal simply for emergency situation and transport of critical care patients inter- or intra-hospital. The developed system was made up of bio-signal measurement modules, wireless communication module, LCD for display, main controller for module integration, and battery. The system was able to measure not only multi-channel ECG signals, diastolic and systolic blood pressure, SpO2, respiration and body temperature but also image of the affected part from a patient or disaster area. The acquired data was transmitted to ultra mobile PC or PDA with a Bluetooth wireless communication. And the data could be transmitted to the central emergency center using CDMA communication via a laptop PC. Additionally, the system includes the real-time automatic algorithm to detect abnormal ECG activity. The experimental test with simulated situation showed the possibility to be effectively used at emergency situation.