• DocumentCode
    1894550
  • Title

    Data Preprocessing Method of ECG Indicators When Applied ECG in Driver Mental Workload Research

  • Author

    Xiaoli, Xie ; Jiangbi, Hu ; Xiaoming, Liu ; Shuyun, Wang ; Pingsheng, Li

  • Author_Institution
    Transp. Res. Center, Beijing Univ. of Technol., Beijing, China
  • Volume
    1
  • fYear
    2009
  • fDate
    10-11 Oct. 2009
  • Firstpage
    569
  • Lastpage
    572
  • Abstract
    Electrocardiogram (ECG) indicators are widely used in driver mental workload studies. Because ECG is always recorded continuously in experiments, ECG indicator data often have trend. To make follow-up data analysis faster and more reliable, ECG indicator data should be preprocessed to remove or extract the trend according to the aim of the experiment. However, most researchers tend to ignore this point. Based on time series theories, this paper proposed a set of methods to preprocess ECG indicator data series. In this paper, the data preprocessing method was described in detail. And an example was given to illustrate and prove the validity of the method.
  • Keywords
    behavioural sciences computing; data analysis; driver information systems; electrocardiography; feature extraction; psychology; road traffic; time series; ECG indicator data extraction; data analysis; data preprocessing method; driver mental workload research; electrocardiogram; road traffic engineering; time series theory; Automation; Data analysis; Data preprocessing; Electrocardiography; Fluctuations; Heart; Roads; Testing; Timing; Transportation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
  • Conference_Location
    Changsha, Hunan
  • Print_ISBN
    978-0-7695-3804-4
  • Type

    conf

  • DOI
    10.1109/ICICTA.2009.144
  • Filename
    5287586