• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.62-69
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• 2022

An electrocardiogram (ECG) is one of the most important biosignals, and in particular, continuous ECG monitoring is very important in patients with arrhythmia. There are many different types of arrhythmia (sinus node, sinus tachycardia, atrial premature beat (APB), and ventricular fibrillation) depending on the cause, and continuous ECG monitoring during daily life is very important for early diagnosis of arrhythmias and setting treatment directions. The ECG signal of arrhythmia patients is very unstable, and it is difficult to detect the R-peak point, which is a key feature for automatic arrhythmias detection. In this study, we develped a continuous measuring Holter ECG monitoring device and software for analysis and confirmed the utility of R-peak of the ECG signal with MIT-BIH arrhythmia database. In future studies, it needs the validation of algorithms and clinical data for morphological classification and prediction of arrhythmias due to various etiologies.

• Proceedings of the Safety Management and Science Conference
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• 2004.05a
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• pp.241-245
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• 2004

In this paper, we implement a portable bioelectric signal measurement system for the safety of industrial workers. The developed system consists of two parts: the one is boielectric signal measurement unit and the other is signal analyzer system with PDA. The former includes signal processing part, A/D convertor, and 8051 based microprocessor, the latter includes software for signal analysis and display. The developed system detects industrial worker's ECG and displays and stores it to PDA. The ECG data in PDA can be transmitted to PC located in a distance, allowing a doctor to review the ECG and make a treatment decision. A doctor analyzes the ECG data and gives medical treatment to industrial worker.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.817-822
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• 1992

Distortion analysis of digital filters for the ECG signal processing is presented. Several band pass and band reject filters are designed for the analysis. Computer simulations are performed to compare the distortions of the Butterworth type filters and linear phase optimal fitters. The designed filters are applied to power line interference cancelling in ECG signals.

• Journal of Information Processing Systems
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• v.18 no.1
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• pp.97-114
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• 2022

Interest is increasing in electrocardiogram (ECG) signal analysis for embedded devices, creating the need to develop an algorithm suitable for a low-power, low-memory embedded device. Linear approximation of the ECG signal facilitates the detection of fiducial points by expressing the signal as a small number of vertices. However, dynamic programming, a global optimization method used for linear approximation, has the disadvantage of high complexity using memoization. In this paper, the calculation area and memory usage are improved using a linear approximated template. The proposed algorithm reduces the calculation area required for dynamic programming through local optimization around the vertices of the template. In addition, it minimizes the storage space required by expressing the time information using the error from the vertices of the template, which is more compact than the time difference between vertices. When the length of the signal is L, the number of vertices is N, and the margin tolerance is M, the spatial complexity improves from O(NL) to O(NM). In our experiment, the linear approximation processing time was 12.45 times faster, from 18.18 ms to 1.46 ms on average, for each beat. The quality distribution of the percentage root mean square difference confirms that the proposed algorithm is a stable approximation.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.8
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• pp.691-697
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• 2002

Myocardial ischemia is a disorder of cardiac function caused by insuficient blood flow to the muscle tissue of the heart. We can diagnose myocardial ischemia by observing the change of ST-segment, but this change is temporary. Our primary purpose is to detect the temporary change of the 57-segment automatically In the signal processing, the wavelet transform decomposes the ECG(electrocardiogram) signal into high and low frequency components using wavelet function. Recomposing the high frequency bands including QRS complex, we can detect QRS complex more easily. Amplitude comparison method is adopted to detect QRS complex. Reducing the effect of noise to the minimum, we grouped ECG by 5 data and compared the amplitude of maximum value. To recognize the ECG .signal pattern, we adopted the polynomial approximation partially and statistical method. The polynomial approximation makes possible to compare some ECG signal with different frequency and sampling period. The ECG signal is divided into small parts based on QRS complex, and then, each part is approximated to the polynomials. After removing the distorted ECG by calculating the difference between the orignal ECG and the approximated ECG for polynomial, we compared the approximated ECG pattern with the database, and we detected and classified abnormality of ECG.

• Journal of the Institute of Convergence Signal Processing
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• v.16 no.2
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• pp.56-62
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• 2015

In this study, we implemented an unconstraint ECG monitoring system on a chair. Nowadays, modern people spend most of their time sitting on the chair. Therefore, it is necessary to have an unconstraint ECG monitoring system that can be used for a long time. The implemented system can perform measurement even with clothes on and it has great advantage on motion artifacts. A pair of unconstraint electrodes are placed on the back of the chair. Amplifier and filters are designed to remove motion artifacts, The baseline noise and power line noise are filtered and very low level of bio-signal is amplified to give a final measurement. Control unit and wireless transmission unit are implemented. Analog signal is converted into digital signal and transmits biological signal to the PC and the smart phone. Therefore continuous ECG monitoring in daily life is made possible. A comparison experiment between Ag / AgCl electrode and unconstraint electrode is conducted to evaluate the performance of the implemented system. As a result, we confirm our unconstraint system can be used for daily life ECG monitoring.

• The KIPS Transactions:PartC
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• v.18C no.3
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• pp.195-198
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• 2011

Recent expansion of the ubiquitous environment and improvement of the USN give lots of U-healthcare systems. In this paper, we design and implement a wireless ECG measurement system that can send ECG signals among the sensors and collector. It can also give almost the same precision as a hospital ECG system with mobility. The most important fact of the mobile ECG system is the signal data connectivity among the sensors and device such as signal cables or wires. we can eliminate the signal cable through the Zigbee sender and collector via implementing Zigbee-SD communication system that can receive the ECG signal data. We also implement ECG app software on the smart phone that can analyze and show the data results directly. It can give lots of mobility and usability under ubiquitous environment and would be a very efficient wireless ECG system for U-healthcare service.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.889-890
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• 2006

This paper pertains to introducing the design of adaptive filters for the cancellation of muscle noise among several types of noise sources from the ECG signal. We used EMG signals measured along with ECG at the same time to use it as the reference input to the adaptive filter for the experiments. PSD results showed that the statistical characteristics of ECG are closely correlated with those of EMG.

• Journal of Biomedical Engineering Research
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• v.22 no.3
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• pp.285-291
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• 2001

In this paper, we designed two preprocessing adaptive filter - high pass filter and notch filter - using FPGA. For minimizing the calculation load of multi-channel and high-resolution ECG system, we utilize FPGA rather than digital signal processing chip. To implement the designed filters in FPGA, we utilize FPGA design tool(Altera corporation, MAX-PLUS II) and CSE database as test data. In order to evaluate the performance in terms of processing time, we compared the designed filters with the digital filters implemented by ADSP21061(Analog Devices). As a result, the filters implemented by FPGA showed better performance than the filters based on ADSP21061. As a consequence of examination, we conclude that FPGA is a useful solution in multi-channel and high-resolution signal processing.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2006.06a
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• pp.113-116
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• 2006

최근 무선센서네트워크 기술을 이용한 다양한 시도가 이루어지고 있으며 특히 헬스케어분에서 활발히 연구되어지고 있다. 본 연구에서는 무선센서노드를 이용하여 계측된 생체신호를 바탕으로 환자의 상태 및 진단을 위한 기초자료를 활용하기 위한 시스템을 구현하였다. 생체신호로 ECG(electrocardiogram)와 체온 파라미터를 사용하였으며 ECG신호의 QRS특성점을 축출하기 위해 Pan&Tomkins에 개발된 알고리즘을 사용하였다. 또한 효율적인 모니터링을 위해 비정상적인 ECG신호에 대한 알림기능을 구현하였으며 이러한 감시기능은 상시 모니터링을 하지 않고도 환자의 상태를 알 수 있게 하였다. 본 연구에서 구현된 이러한 시스템기술은 국내의 고령화 문제로 발생되는 의료비용을 크게 감소시킬 수 있을 것으로 예상된다.