• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.519-526
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• 2013

ECG signal has the feature that is repeated in a cycle of P, Q, R, S, and T waves and is sampled at a high sampling frequency in general. By using the feature of periodic ECG signals, maximizing compression efficiency while minimizing the loss of important information for diagnosis is required. However, the periodic characteristics of such amplitude and period is not constant by measuring time and patients. Even though measured at the same time, the patient's characteristics display different periodic intervals. In this paper, an adaptive multi-level coding is provided by coding adaptively the dominant and non-dominant signal interval of the ECG signal. The proposed method can maximize the compression efficiency by using a multi-level code that applies different compression ratios considering information loss associated with the dominant signal intervals and non-dominant signal intervals. For the case of long time measurement, this method has a merit of maximizing compression ratio compared with existing compression methods that do not use the periodicity of the ECG signal and for the lossless compression coding of non-dominant signal intervals, the method has an advantage that can be stored without loss of information. The effectiveness of the ECG signal compression is proved throughout the experiment on ECG signal of MIT-BIH arrhythmia database.

• Progress in Medical Physics
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• v.6 no.2
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• pp.103-109
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• 1995

Power spectral analysis of spontaneous heart rate fluctuations were assessed by use of autooic blocking agents and changes in posture. The total power spectral range of interest is divided amongst the various experiments so that each respiratory pattern contributes a spectral ratio of interval to respiration only over a group of frequencies for which the specific respiratory pattern has substantial, and roughly constant, spectral magnitudes. System hardware is consisted ECG preamplifier, respiratory fluctuation detect, interval time generator and IBC 486PC. High frequency fluctuation, at the respiratiory frequency, are decreased by standing and are mediated solely by the parasympathetic system. Power spectral analysis is a powerful nonivsve tool for quantitying autonomic nervous system activity.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.534-535
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• 2017

With the economic growth, the quality of life of the individual is improving and interest in health is increasing. However, it is not easy for self-care for the modern people who are busy and the elderly who are uncomfortable. The purpose of this study was to develop a healthcare system that can more easily monitor the health condition of the patients. The ECG and pulse wave including the important health information that can be conveniently measured by the general public can be measured and the PTT and to monitor the health status of the circulatory system. To evaluate the performance of the implemented system, we measured PTT according to posture change and evaluated the possibility of monitoring arterial blood flow during daily life.

• Journal of Biomedical Engineering Research
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• v.19 no.3
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• pp.251-260
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• 1998

The Holter monitoring system is a widely used noninvasive diagnostic tool for ambulatory patient who may be at risk from latent life-threatening cardiac abnormalities. In this paper, we design a high performance intelligent holter monitoring system which is characterized by the small-sized and the low-power consumption. The system hardware consists of one-chip microcontroller(68HC11E9), ECG preprocessing circuit, and flash memory card. ECG preprocessing circuit is made of ECG preamplifier with gain of 250, 500 and 1000, the bandpass filter with bandwidth of 0.05-100Hz, the auto-balancing circuit and the saturation-calibrating circuit to eliminate baseline wandering, ECG signal sampled at 240 samples/sec is converted to the digital signal. We use a linear recursive filter and preprocessing algorithm to detect the ECG parameters which are QRS complex, and Q-R-T points, ST-level, HR, QT interval. The long-term acquired ECG signals and diagnostic parameters are compressed by the MFan(Modified Fan) and the delta modulation method. To easily interface with the PC based analyzer program which is operated in DOS and Windows, the compressed data, that are compatible to FFS(flash file system) format, are stored at the flash memory card with SBF(symmetric block format).

• Journal of Navigation and Port Research
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• v.28 no.5
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• pp.449-454
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• 2004

These days ships medical treatment is under unfavorable circumstances, because there is no professional doctor who can diagnose and treat the patients accurately on the ships. Therefore, ship's telemedicine should be urgently actualized to elevate the crew's my of boarding life and welfare. A purpose of this research is to develope the telemedicine system which can acquire the patient's informations like ECG and phonocardiogram used for the diagnosis and transmit those to the doctors of shore medical center. In this paper, we designed the communication part which could transmit the bio-signals acquired from the developed ship's digital ECG and stethoscope based on personal computer by the INMARSAT Also we inspected data errors through the comparison between the sent and received data And we confirmed the possibility and compatibility of the telemedicine using ship's communication system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.5
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• pp.1303-1310
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• 2010

Recently, researches related with automative mechanism have been widely studied to increase the driver's safety by continuously monitoring the driver's health condition to prevent driver's drowsiness. This paper describes the design of wearable chest belt for ECG and reflectance pulse oximetry for SpO2 sensors based on wireless sensor network to monitor the driver's healthcare status. ECG, SpO2 and heart rate signals can be transmitted via wireless sensor node to base station connected to the server. Intelligent monitoring system is designed at the server to analyze the SpO2 and ECG signals. HRV (Heart Rate Variability) signals can be obtained by processing the ECG and PPG signals. HRV signals are further analyzed based on time and frequency domain to determine the driver's drowsiness status.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.05a
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• pp.503-506
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• 2001

There are four factors for patient monitoring : electrocardiography, blood pressure, temperature and respiration. While there are a lot of studies of E.C.C (electro-cardiography) monitoring system in the world, the studies of Respiratory system are not enough and leave much to be desired in the country. In this paper, we developed a respiratory system with the electrical impedance change of the lungs depending on the breath. Using the same electrode, we can monitor E.C.C and Respiration simultaneously, so we can monitor a patient's no-breathing state due to the central nerve paralysis in the emergency room easily. In this monitoring system, the analog part was made separated from the digital part for reducing power source noise and protecting patient from electric shock. The analog part consists of the several parts a high-frequency sine-wave generator, all amplifier for amplifying any impedance change signal, an analog processing part for rectifying and filtering. And the digital parts consists of three parts an AD convertor for converting analog signal to digital signal, digital filter, and a digital part for digital signal processing. This system's merits are using the same electrode with E.C.C and developing the multiple patient monitoring system easily.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.17-23
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• 2011

In this paper, daily life stress monitoring system is proposed. The proposed wireless ECG module, reducing the noise and increasing the size of signal, amplification circuit was designed for. Using HRV(Heart Rate Variability), extracted by measuring R-wave, stress diagnostic algorithms to assess the stress of human emotion were developed. For monitoring the activities, the proposed system is consist of small rectangular size for portable and by simple measurement it is possible to measure at any time. Through experiments, the proposed approach to represent user's stress level can be confirmed. Through that, it can see appropriate structure to obtain R-wave for stress assess as well as high resemblance to the clinical electrocardiogram. In this paper, performed experiments was developed nonrestraint measuring and wearable wireless biometric scanner that is able to monitor the heart's electrical activity of everyday life.Using this, the algorithm system, that is able to assess stress index through time-domain and frequency-domain analysis of the front and the rear of performing stress load protocol, was developed,

• Investigative Magnetic Resonance Imaging
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• v.18 no.3
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• pp.244-252
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• 2014

Purpose : We proposed a multi-physiological signals based real-time intelligent triggering system(MITS) for Cardiac MRI. Induced noise of the system was analyzed. Materials and Methods: MITS makes cardiac MR imaging sequence synchronize to the cardiac motion using ECG, respiratory signal and second order derivative of $SPO_2$signal. Abnormal peaks due to arrhythmia or subject's motion are rejected using the average R-R intervals and R-peak values. Induced eddy currents by gradients switching in cardiac MR imaging are analyzed. The induced eddy currents were removed by hardware and software filters. Results: Cardiac MR images that synchronized to the cardiac and respiratory motion are acquired using MITS successfully without artifacts caused by induced eddy currents of gradient switching or subject's motion or arrhythmia. We showed that the second order derivative of the $SPO_2$ signal can be used as a complement to the ECG signals. Conclusion: The proposed system performs cardiac and respiratory gating with multi-physiological signals in real time. During the cardiac gating, induced noise caused by eddy currents is removed. False triggers due to subject's motion or arrhythmia are rejected. The cardiac MR imaging with free breathing is obtained using MITS.

• Journal of Biomedical Engineering Research
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• v.25 no.2
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• pp.129-135
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• 2004

In the home health management system, we often face the situation to handle biological signals that are frequently measured from normal subjects. In such a case, it is necessary to decide whether the signal at a certain moment is normal or abnormal. Since ECC is one of the most frequently measured biological signals, we describe algorithms that detect QRS-complex and decide whether it is normal or abnormal. The developed QRS detection algorithm is a simplified version of the conventional algorithm providing enough performance for the proposed application. The developed classification algorithm that detects abnormal from mostly normal beats is based on QRS width, R-R interval and QRS shape parameter using Karhunen-Loeve transformation. The simplified QRS detector correctly detected about 99% of all beats in the MTT/BIH ECG database. The classification algorithm correctly classified about 96% of beats as normal or abnormal. The QRS detection and classification algorithm described in this paper could be used in home health management system.