• Title/Summary/Keyword: detecting change points

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Realtime Wireless Monitoring of Abnormal ST in ECG Using PC Based System

  • Jeong, Gu-Young;Yu, Kee-Ho;Kim, Nam-Gyun;Inooka, Hikaru
    • 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.

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Bayesian Inference for Switching Mean Models with ARMA Errors

  • Son, Young Sook;Kim, Seong W.;Cho, Sinsup
    • Communications for Statistical Applications and Methods
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    • v.10 no.3
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    • pp.981-996
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    • 2003
  • Bayesian inference is considered for switching mean models with the ARMA errors. We use noninformative improper priors or uniform priors. The fractional Bayes factor of O'Hagan (1995) is used as the Bayesian tool for detecting the existence of a single change or multiple changes and the usual Bayes factor is used for identifying the orders of the ARMA error. Once the model is fully identified, the Gibbs sampler with the Metropolis-Hastings subchains is constructed to estimate parameters. Finally, we perform a simulation study to support theoretical results.

Non-restricted Measurement and Diagnosis of ECG signals

  • Jeong, Gu-Young;Yu, Kee-Ho
    • 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...

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Fall Situation Recognition by Body Centerline Detection using Deep Learning

  • Kim, Dong-hyeon;Lee, Dong-seok;Kwon, Soon-kak
    • Journal of Multimedia Information System
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    • v.7 no.4
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    • pp.257-262
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    • 2020
  • In this paper, a method of detecting the emergency situations such as body fall is proposed by using color images. We detect body areas and key parts of a body through a pre-learned Mask R-CNN in the images captured by a camera. Then we find the centerline of the body through the joint points of both shoulders and feet. Also, we calculate an angle to the center line and then calculate the amount of change in the angle per hour. If the angle change is more than a certain value, then it is decided as a suspected fall. Also, if the suspected fall state persists for more than a certain frame, then it is determined as a fall situation. Simulation results show that the proposed method can detect body fall situation accurately.

A Study on a Method for Detecting Leak Holes in Respirators Using IoT Sensors

  • Woochang Shin
    • International journal of advanced smart convergence
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    • v.12 no.4
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    • pp.378-385
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    • 2023
  • The importance of wearing respiratory protective equipment has been highlighted even more during the COVID-19 pandemic. Even if the suitability of respiratory protection has been confirmed through testing in a laboratory environment, there remains the potential for leakage points in the respirators due to improper application by the wearer, damage to the equipment, or sudden movements in real working conditions. In this paper, we propose a method to detect the occurrence of leak holes by measuring the pressure changes inside the mask according to the wearer's breathing activity by attaching an IoT sensor to a full-face respirator. We designed 9 experimental scenarios by adjusting the degree of leak holes of the respirator and the breathing cycle time, and acquired respiratory data for the wearer of the respirator accordingly. Additionally, we analyzed the respiratory data to identify the duration and pressure change range for each breath, utilizing this data to train a neural network model for detecting leak holes in the respirator. The experimental results applying the developed neural network model showed a sensitivity of 100%, specificity of 94.29%, and accuracy of 97.53%. We conclude that the effective detection of leak holes can be achieved by incorporating affordable, small-sized IoT sensors into respiratory protective equipment.

A Potts Automata algorithm for Edge detection (Potts Automata를 이용한 영상의 에지 추출)

  • Lee, Seok-Ki;Kim, Seok-Tae;Cho, Sung-Jin
    • Proceedings of the Korea Information Processing Society Conference
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    • 2001.10a
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    • pp.767-770
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    • 2001
  • Edge detection is one of issues with essential importance in the area of image process. An edge in image is a boundary or contour which a significant change occurs in image intensity. In the paper, we process edge detection algorithms which are based on Potts automata. The dynamical behavior of these automata is completely determined by Lyapunov operators for sequential and parallel update. If Potts Automata convergence to fixed points, then it can be used to image processing. From the generalized Potts automata point of view, we propose a Potts Automata technique for detecting edge. Based on the experimental results we discuss the advantage and efficiency.

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Sensorless Drive Circuit of a Switched Reluctance Motor using the Variation of Phase Currents (상전류 변화를 이용한 Switched Reluctance Motor의 Sensorless 구동회로)

  • Lim, J.Y.;Cho, K.Y.;Shin, D.J.;Kim, C.H.;Kim, J.C.
    • Proceedings of the KIEE Conference
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    • 1995.07a
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    • pp.315-317
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    • 1995
  • A simple drive circuit without position sensors for a switched reluctance motor is presented. The turn on and turn off points are determined by detecting the rate of change of the active phase current. The drive circuit consists of a current sensing resistor, RC filter, comparator, OP Amp, and OR gates. It is verified through the experiments that the switched reluctance motor with the proposed sensorless drive circuit is well operated in wide speed ranges.

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Improvement of Accuracy in Moire-type Laser Encoder Using Four Point Method (4점법을 이용한 모아레식 레이저 엔코우더의 정밀 정확도 향상)

  • Jeon, Byeong Wook;Park, Too Won;Lee, Myung Ho
    • Journal of the Korean Society for Precision Engineering
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    • v.12 no.7
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    • pp.19-25
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    • 1995
  • Presently, along with the advance of high-technology, the precise measurement of linear displacement has become a staple requirement, and consequently the high resolution with submicron order has also been required in precise positioning and carriaging. In this paper, we advance a propose on a new type of laser encoder based on the principle of phase analysis of the moire fringes from superimposed two gratings. The phase angle as an information of displacement can be accurately calculated by detecting the change in brighness at four points of the fringes. The actual application of four point method to the moire fringes is performed thru microcomputer for general purpose, and the measuring procedure is also studied in this research. As an experimental result, in the case of using 20 .mu. m-pitch gratings, it is validated that this method has the resolution of 0.01 .mu. m and the accuracy of .+-. 0.15 .mu. m over the setting range of 100mm.

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Exploring the factors responsible for variation in streamflow using different Budyko-base functions

  • Shah, Sabab Ali;Jehanzaib, Muhammad;Kim, Min Ji;Kim, Tae-Woong
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.140-140
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    • 2022
  • Recently an accurate quantification of streamflow under various climatological and anthropogenic factors and separation of their relative contribution remains challenging, because variation in streamflow may result in hydrological disasters. In this study, we evaluated the factors responsible for variation in streamflow in Korean watersheds, quantified separately their contribution using different Budyko-based functions, and identified hydrological breakpoint points. After detecting that the hydrological break point in 1995 and time series were divided into natural period (1966-1995), and disturbed period (1996-2014). During the natural period variation in climate tended to increase change in streamflow. However, in the disturbed period both climate variation and anthropogenic activities tended to increase streamflow variation in the watershed. Subsequently, the findings acquired from different Budyko-based functions were observed sensitive to selection of function. The variation in streamflow was observed in the response of change in climatic parameters ranging 46 to 75% (average 60%). The effects of anthropogenic activities were observed less compared to climate variation accounts 25 to 54% (average 40%). Furthermore, the relative contribution was observed to be sensitive corresponding to Budyko-based functions utilized. Moreover, relative impacts of both factors have capability to enhance uncertainty in the management of water resources. Thus, this knowledge would be essential for the implementation of water management spatial and temporal scale to reduce the risk of hydrological disasters in the watershed.

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Automatic Change Detection of Urban Areas using LIDAR Data (라이다데이터를 이용한 도시지역의 자동변화탐지)

  • Choi, Kyoung-Ah;Lee, Im-Pyeong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.26 no.4
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    • pp.341-350
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    • 2008
  • Change detection has been recognized as one of the most important steps to update city models. In this study, we thus propose a method to detect urban changes from two sets of LIDAR data acquired at different times. The main processes in the proposed method are (1) detecting change areas through subtraction between two DSMs generated from the LIDAR sets, (2) organizing the LIDAR points within the detected areas into surface patches, (3) classifying the class of each patch such as ground, vegetation, and building, and (4) determining the kinds of changes based on the properties and classes of the patches. The results which were obtained from the application of the proposed method to real data were verified as appropriate using the reference data manually acquired from the visual inspection of the orthoimages of the same area. The probability of success in change detection is assessed to 97% on an average. In conclusion, the proposed method is evaluated as a reliable, and efficient approach to change detection and thus the update of city model.