• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.207-212
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• 1996

In this paper, we designed a Holter analysis system using the visual programming method. It differs from the existing analysis system in that the various signal processing algorithms represented by icons were designed by GUI concept which provide unskilled user with easy and convenient analysis environment. In order to analysis ECG signal, we only select the icon representing a algorithm to be applied by mouse and arrange the selected icons upon the order to be processed on screen. As a result it provides a convenient usage and flexibility of analysis. Finally, we can find the optimal algorithm for the ambulatory ECG analysis by comparing the several results obtained from the various analysis configuration.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.6
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• pp.277-283
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• 2023

Vital signals provide essential information regarding the health status of individuals, thereby contributing to health management and medical research. Present monitoring methods, such as ECGs (Electrocardiograms) and smartwatches, demand proximity and fixed postures, which limit their applicability. To address this, Non-contact vital signal measurement methods, such as CW (Continuous-Wave) radar, have emerged as a solution. However, unwanted signal components and a stepwise processing approach lead to errors and limitations in heart rate detection. To overcome these issues, this study introduces an integrated neural network approach that combines noise removal, demodulation, and dominant-frequency detection into a unified process. The neural network employed for signal processing in this research adopts a MLP (Multi-Layer Perceptron) architecture, which analyzes the in-phase and quadrature signals collected within a specified time window, using two distinct input layers. The training of the neural network utilizes CW radar signals and reference heart rates obtained from the ECG. In the experimental evaluation, networks trained on different datasets were compared, and their performance was assessed based on loss and frequency accuracy. The proposed methodology exhibits substantial potential for achieving precise vital signals through non-contact measurements, effectively mitigating the limitations of existing methodologies.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.77.3-77
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• 2002

In this paper, the algorithm for detecting the transient change of ST-segment and the device for measuring ECG from patient without restriction of activity are introduced. ST-segment elevation and depression is considered as the main characteristic in diagnosis of myocardial ischemia, but the change of pattern is also important. To consider all of the former and the latter, we used polynomial approximation for diagnosis of ECG. The feature points(R, S and T are detected through the signal processing processes including wavelet transform, and then R-S and S-T are approximated to polynomial. This method allows comparison of two signals that have different sampling time or different numbers of...

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.5
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• pp.848-852
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• 2001

The biomedical signals such as ECG, EMG, EEG, and etc are very Important information to diagnose patients The signal is hard to filter the noise because that is mixed with a lot of noise and biomedical signal has the properties of nonlinear and time-variance. So, we will filter under the measure environment for system or patient. But the general adaptive fillet has brought on the distortion of signal because the adaptive filter adjust the filter coefficient with the fixed order of filter, that filter has the unsuitable order in each other environment. So we propose the dynamic structure adaptive filter that is used for improving that disadvantage. In experiment, we obtain the optimal order of adaptive filter and have food results.

• Proceedings of the KOSOMBE Conference
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• v.1994 no.05
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• pp.49-52
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• 1994

We have developed a biological signal measurement, archiving, and communication system (SiMACS). The front end of the system is the intelligent data processing unit (IDPU) which includes ECG, EEG, EMG, blood pressure, respiration, temperature measurement modules, module control and data acquisition unit, real-time display and signal processing unit. IDPUS are connected to central data base unit through LAN(Ethernet). Workstations which receive signals from central DB and provide various signal analysis tools are also connected to the network. The developed PC-based SiMACS is described.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.5855-5877
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• 2017

In view of personal health and disease management based on cost effective healthcare services, there is a growing need for real-time monitoring services. The electrocardiogram (ECG) signal is one of the most important of health information and real-time monitoring of the ECG can provide an efficient way to cope with emergency situations, as well as assist in everyday health care. In this system, it is essential to continuously collect and transmit large amount of ECG data within a given time and provide maximum user convenience at the same time. When considering limited wireless capacity and unstable channel conditions, appropriate signal processing and transmission techniques such as compression are required. However, ISO/IEEE 11073 standards for interoperability between personal health devices cannot properly support compressed data transmission. Therefore, in the present study, the problems for handling compressed data are specified and new extended agent and manager are proposed to address the problems while maintaining compatibility with existing devices. Extended devices have two PM-stores enabling compression and a novel transmission scheme. A variety of compression techniques can be applied; in this paper, discrete cosine transformation (DCT) is used. And the priority of information after DCT compression enables new transmission techniques for performance improvement. The performance of the compressed signal and the original uncompressed signal transmitted over the noisy channel are compared in terms of percent root mean square difference (PRD) using our simulation results. Our transmission scheme shows a better performance and complies with 11073 standards.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.176-180
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• 2004

The ST-segment that the beginning part of T wave is the important diagnostic parameter to finding myocardial ischemia. Abnormal ST appears in two types. One is the level change, and the other is the pattern change. In this paper, we describe the monitoring of abnormal ST using PC based system. Hardware of this system consists of transmitter, receiver and PC. The function of transmitter is measuring ECG in three channels which are selected manually and transmitting the data to receiver by digital radio way. Connection with receiver and PC is by RS232C, and the data received on the PC is analyzed automatically by ECG analysis algorithm and saved to file. In the algorithm part for detecting abnormal ST, ST-segments are approximated by a polynomial. This method can detect all of the deviation and pattern change of ST-segment regardless the change in the heart rate or sampling rate. To gain algorithm reliability, the method rejects distorted polynomial approximation by calculation the difference between the approximated ST-segment and original ST-segment. In pre-signal processing, the wavelet transformation separates high frequency bands including QRS complex from the original ECG. Consequently, the process improves the performance of detecting each feature points.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.2
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• pp.111-117
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• 2019

We investigated the variations in the magnetic-field distribution and power transmission efficiency, resulting from changes in the relative positions of the transmitting and receiving coils, for electromagnetic-induction-type wireless power transmission using an elliptical receive coil. Results of simulations using a high-frequency structure simulator were compared to actual measurement results. The simulations showed that the transmission efficiency could be maintained relatively stable even if the alignment between the transmitting and receiving coils was changed to some extent. When the centre of the receiving coil was perfectly aligned with the centre of the transmitting coil, the transmission efficiency was the maximum; however, the degree of decrease in the transmission efficiency was small even if the centre of the receiving coil moved by ± 10mm from the centre of the transmitting coil. Therefore, it is expected that the performance of the wireless power transmission system will not be degraded significantly even if perfect alignment is not maintained. The results suggested a standardized application method of wireless transmission in the utilization of wireless power for implantable sensors.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2006.06a
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• pp.109-112
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• 2006

노약자나 만성질환자를 위하여 가정에서 분산된 무선센서네트워크 노드를 사용하는 무선센서네트워크 기반의 생체신호 모니터링 시스템을 구현하였다. 본 논문에서의 생체신호 모니터링 시스템은 가장 중요한 생체 신호인 ECG와 체온을 계측하도록 구성하였으며, 무선센서 노드를 사용하여 원격지의 병원서버 또는 의사의 PC, PDA에 연결된 베이스스테이션으로 Ad-hoc 네트워크를 통해 환자 또는 노인의 건강정보를 전송하는 시스템 구현에 목적을 두고 있다. 본 시스템을 통해 환자의 의료장비 비용을 절약 할 수 있을 뿐만 아니라 센서 노드는 무선센서네트워크의 강점인 Ad-hoc 통신이 가능하면서 저전력으로 동작하여 배터리의 수명을 연장할 수 있는 특징을 가진다. 또한, 병원의 한층 전체의 환자나 여러 환자가 거주하는 가정 또는 시설에서 하나의 PC(또는 서버컴퓨터)로 시스템 구성이 가능하도록 시스템을 구현함으로서 베이스스테이션에서 멀리 떨어져 있는 환자의 생체 신호도 Ad-hoc 네트워크를 통해 베이스스테이션까지 전송이 가능하였으며, 이동성 제공 및 홈 환경에서 사용자에게 편리함을 가져올 수 있으리라 예상된다.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.887-888
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• 2006

In this paper, we devised mac-yule detection system which provide resting state mac-yule. The devised system composed of signal transformation part, signal processing part, and PC based display part. Hardware part consisit of PPG, ECG, EEG, EMG, and RSP. Also, software system consist of bio-signal processing software which detecting mac-yule. EEG-$\alpha$, $\beta$ wave analysis algorithm that use wavelet transformation, RSP detecting algorithm which used zero-crossing method.