Robust signal extraction for on-line monitoring data

被引:45
|
作者
Davies, PL
Fried, R [1 ]
Gather, U
机构
[1] Univ Essen Gesamthsch, Fachbereich Math, D-45141 Essen, Germany
[2] Univ Dortmund, Fachbereich Stat, D-44221 Dortmund, Germany
关键词
linear regression; signal extraction; level change; trend; outliers; small-sample efficiency;
D O I
10.1016/j.jspi.2003.06.012
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Data from the automatic monitoring of intensive care patients exhibits trends, outliers, and level changes as well as periods of relative constancy. All this is overlaid with a high level of noise and there are dependencies between the different items measured. Current monitoring systems tend to deliver too many false warnings which reduces their acceptability by medical staff. The challenge is to develop a method which allows a fast and reliable denoising of the data and which can separate artefacts from clinical relevant structural changes in the patients condition (Estadistica 53 (2001) 259). A simple median filter works well as long as there is no substantial trend in the data but improvements may be possible by approximating the data by a local linear trend. As a first step in this programme, the paper examines the relative merits of the L-1 regression, the repeated median (Biometrika 68 (1982) 242) and the least median of squares (Bull. Internat. Statist. Inst. 46 (1975) 375; J. Amer. Statist. Assoc. 79 (1984) 871). The question of dependency between different items is a topic for future research. (C) 2003 Elsevier B.V. All rights reserved.
引用
收藏
页码:65 / 78
页数:14
相关论文
共 50 条
  • [1] Voice extraction by on-line signal separation and recovery
    Erten, G
    Salam, FM
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-ANALOG AND DIGITAL SIGNAL PROCESSING, 1999, 46 (07): : 915 - 922
  • [2] On spatiotemporal prediction for on-line monitoring data
    Berke, O
    COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 1998, 27 (09) : 2343 - 2369
  • [3] Wireless Fetal Monitoring at Home with On-Line Signal Analysis
    Wrobel, J.
    Matonia, A.
    Kotas, M.
    Przybyla, T.
    Horoba, K.
    5TH EUROPEAN CONFERENCE OF THE INTERNATIONAL FEDERATION FOR MEDICAL AND BIOLOGICAL ENGINEERING, PTS 1 AND 2, 2012, 37 : 906 - +
  • [4] Noise as a signal for on-line estimation and monitoring of welding process
    Prezelj, J
    Cudina, M
    ACTA ACUSTICA UNITED WITH ACUSTICA, 2003, 89 (02) : 280 - 286
  • [5] Application of Signal Injection Method in on-line Insulation Monitoring
    Xi H.
    Zhou K.
    Zeng Q.
    Rao X.
    Liu L.
    Huang Y.
    Dianwang Jishu/Power System Technology, 2021, 45 (01): : 409 - 416
  • [6] On-line extraction of qualitative movements for monitoring process plants
    Yamashita, Yoshiyuki
    KNOWLEDGE-BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, PT 2, PROCEEDINGS, 2006, 4252 : 595 - 602
  • [7] On-line monitoring and diagnosis for satellite telemetry data
    Long, B
    Song, ZJ
    Jiang, XW
    AIRCRAFT ENGINEERING AND AEROSPACE TECHNOLOGY, 2005, 77 (01): : 42 - 51
  • [8] ON-LINE PROCESS MONITORING USING A ROBUST STATISTICS BASED METHODOLOGY
    Llanos, C. E.
    Chavez Galletti, R. J.
    Sanchez, M. C.
    Maronna, R.
    LATIN AMERICAN APPLIED RESEARCH, 2019, 49 (02) : 111 - 116
  • [9] Data-driven linear decision rule approach for distributionally robust optimization of on-line signal control
    Liu, Hongcheng
    Han, Ke
    Gayah, Vikash V.
    Friesz, Terry L.
    Yao, Tao
    TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2015, 59 : 260 - 277
  • [10] Robust distance measures for on-line monitoring: Why use euclidean?
    Garvey, Dustin R.
    Hines, J. Wesley
    APPLIED ARTIFICIAL INTELLIGENCE, 2006, : 922 - +