• Journal of Biomedical Engineering Research
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• v.37 no.5
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• pp.161-167
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• 2016

Recent technological advances in sensor fabrication and bio-signal processing enabled non-constraint and non-intrusive measurement of human bio-signals. Especially, non-constraint measurement of ECG makes it available to estimate various human health parameters such as heart rate. Additionally, non-constraint ECG measurement of wheelchair user provides real-time health parameter information for emergency response. For accurate emergency response with low false alarm rate, it is necessary to discriminate quality levels of ECG measured using non-constraint approach. Health parameters acquired from low quality ECG results in inaccurate information. Thus, in this study, a machine learning based approach for three-class classification of ECG quality level is suggested. Three sensors are embedded in the back seat, chest belt, and handle of automatic wheelchair. For the two sensors embedded in back seat and chest belt, capacitively coupled electrodes were used. The accuracy of quality level classification was estimated using Monte Carlo cross validation. The proposed approach demonstrated accuracy of 94.01%, 95.57%, and 96.94% for each channel of three sensors. Furthermore, the implemented algorithm enables classification of user posture by detection of contacted electrodes. The accuracy for posture estimation was 94.57%. The proposed algorithm will contribute to non-constraint and robust estimation of health parameter of wheelchair users.

• The KIPS Transactions:PartB
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• v.18B no.6
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• pp.341-348
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• 2011

ECG(Electrocardiogram), a field of Bio-signal, is generally experimented with classification algorithms most of which are SVM(Support Vector Machine), MLP(Multilayer Perceptron). But this study modified the Random Forest Algorithm along the basis of signal characteristics and comparatively analyzed the accuracies of modified algorithm with those of SVM and MLP to prove the ability of modified algorithm. The R-R interval extracted from ECG is used in this study and the results of established researches which experimented co-equal data are also comparatively analyzed. As a result, modified RF Classifier showed better consequences than SVM classifier, MLP classifier and other researches' results in accuracy category. The Band-pass filter is used to extract R-R interval in pre-processing stage. However, the Wavelet transform, median filter, and finite impulse response filter in addition to Band-pass filter are often used in experiment of ECG. After this study, selection of the filters efficiently deleting the baseline wandering in pre-processing stage and study of the methods correctly extracting the R-R interval are needed.

• Proceedings of the KOSOMBE Conference
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• v.1994 no.05
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• pp.57-59
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• 1994

In this paper, we present the software part of the intelligent data processing unit (IDPU), which plays an important role in SiMACS. The software system processes ECG, EEG, EMG, blood pressure, respiration, temperature signals, and extracts some information about patient conditions. It displays the patient condition information and the signal data synchronously, and manages them together with other patient personal data in a network-based client/server environment. The software system is designed in an object-oriented paradigm, and implemented in C++ as a window-based application program.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.171-175
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• 1997

We have developed a remote diagnosis system using the LAN and MODEM which enables a routine check for a patient remotely. We used $LabVIEW^{TM}$ as the programing development tool and DAQ (Data Aquisition) board from National Instrument for data aquisition. The LAN card and MODEM are used for the transmission of patient's data. A patient data are aquired by DAQ board and signal processing is done by $LabVIEW^{TM}$, which is a graphical prgamming language. Two methods for the data of transmission. One is the Client-Server model using TCP/IP (Transmission Control Protocol / Internet Address) in the LAN (Local Area Network) Another is using MODEM to transmit the measured data from a patient. In this case, the data transmission is accomplished by the FTP (File Transfer Protocol).

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1284-1287
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• 1987

A method of quantitative electrocardiogram analysis, based on concepts drawn from syntactic pattern recognition theories, is described. The algorithm can be used for removing the Interference noises and base line drift as a filter function, and for reducing the number of points representing the digitized ECG waveform. The Parsing is performed with simple finite state automata inferred by experiments and suitable to be updated during experiment execution. Two parameters are utilized for defining the noise and these make the algorithm flexible. The examples for testing the algorithm is real ECG waveforms with noise. Some experimental results lire presented.

• Journal of Biomedical Engineering Research
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• v.17 no.2
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• pp.241-246
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• 1996

This paper describes a new system that detects radial pulse wave and allows the diagnosis of malfunctions of cardiovascular system by analyzing the waveforms with the newly proposed algorithm. The system consists of a sensor part and a data processing part within which a new detection algorithm is incorporated In acquiring radial pulse signal noninvasively, the sensor used in this system is a new combinational fiber-optic sensor which has a detecting Part and a transmitting Part. Also, In order to analyze the characteristics of pulsation quantitatively, the algorithm proposed in this paper is a method that runs in parallel with both the data of ECG and differential pulse simultaneously. these concepts are based upon the idea that thfee Q points of ECG give obious discrimination of one entire period of pulse in any abnormal cases, and newly defined feature lines at the differential counterpart can be used to recogrlize sDme significant points in one period of pulses.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.545-548
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• 2009

Recently, researches related to 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 $SpO_2$ sensors based on wireless sensor network to monitor the driver's healthcare status. ECG, $SpO_2$ 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 $SpO_2$ 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 IEEK Conference
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• 2005.11a
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• pp.493-496
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• 2005

For home healthcare, the unconstrained measurement of physiological signal is highly required to avoid the inconvenience of users. The recording and analysis of the fundamental parameters during sleep like respiration and heart beat provide valuable information on his/her healthcare. Using the air mattress sensor system, the respiration and heart beat movements can be measured without any harness or sensor on the subject's body. The differential measurement technique between two air cells is adopted to enhance the sensitivity. The balancing tube between two air cells is used to increase the robustness against postural changes during the measurement period. The meaningful frequency range could be selected by the pneumatic filter with balancing tube. ECG (Electrocardiography) and respiration sensor (plethysmography) were measured for comparison with the signal from air mattress. To extract the heart beat information from air pressure sensor, digital signal processing technique was used. The accuracy for breathing interval and heart beat monitoring was acceptable. It shows the potentials of air mattress sensor system to be the unconstrained home sleep monitoring system.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2001.05a
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• pp.252-255
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• 2001

The purpose of this study is to realize the real time monitoring ECG telemetry system applied by the telemetry unit, in which transmission is made through the electronic wave and reception is made through the light, and by the wavelet algorithm as well. A light receiver via existing telemetry unit which is based on baseband, the reception length was 50cm, but when the frequency modulation is used, the reception length is extended to 3m. In addition to this, we have found that the full-duplex method of transmission became available by using dual-mechanism.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.05a
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• pp.512-515
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• 2001

The heifer electrocardiograph is a widely progressing research which is used in judgement to existence for a heart disease and analyzes electric potential changes of heart movement during continuous living of everyday after attaching to body portable holler recorder for twenty-four hours. In order to obtain electrocardiogram clearly, it must eliminate that 60Hz power line interference, baseline wandering, noise of muscle constriction. In holter electrocardiogram, the most big problem which is recorded signal of ECG(electrocardiogram) is a baseline wandering elimination, which is occurred by rhythm of respiration and muscle constriction of part from attaching to an electrode. Such baseline is roughly irregular wandering and shaking up and down therefore the part of baseline wandering elimination is very important because it is difficult of ECG diagnosis. In this study, it is stabilized baseline wandering in analog part as implementation f real-time signal processing digital filter so it is applicable to analyze patient's heart disease by way of design of baseline wandering elimination system.