• DocumentCode
    3324870
  • Title

    The BCG signal feature extraction and recognition based on the cumulative residual entropy

  • Author

    Zhixin Ma ; Taishan Chu

  • Author_Institution
    Nat. Eng. Res. Center for Broadband Networks & Applic., Shanghai, China
  • fYear
    2013
  • fDate
    23-24 Dec. 2013
  • Firstpage
    526
  • Lastpage
    528
  • Abstract
    In this paper, we use cumulative residual entropy to get the features of Ballistocardiogram (BCG). The data after feature recognition are classified by Support Vector Machine (SVM) algorithm to compare the accuracy. Experimental results indicate that high classification accuracy can be obtained. The method can be used in some disease identification.
  • Keywords
    cardiology; feature extraction; image classification; medical signal processing; support vector machines; BCG signal feature extraction; SVM algorithm; ballistocardiogram; classification accuracy; cumulative residual entropy; disease identification; feature recognition; support vector machine algorithm; Accuracy; Diseases; Entropy; Feature extraction; Heart; Sleep apnea; Support vector machines; Arrhythmia; Ballistocardiogram (BCG); Disease Identification; Support Vector Machine (SVM); cumulative residual entropy; obstructive sleep apnea-hypopnea syndrome (OSAHS);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Instrumentation and Measurement, Sensor Network and Automation (IMSNA), 2013 2nd International Symposium on
  • Conference_Location
    Toronto, ON
  • Type

    conf

  • DOI
    10.1109/IMSNA.2013.6743330
  • Filename
    6743330
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3324870