Accession number: 20095112564446
Title: Data preprocessing method of ECG indicators when applied ECG in driver mental workload research
Authors: Xiaoli, Xie1 ; Jiangbi, Hu1 ; Xiaoming, Liu1 ; Shuyun, Wang1 ; Pingsheng, Li2
Author affiliation:
1 Transportation Research Center, Beijing University of Technology, Beijing, China
2 National Center of ITS Engineering and Technology, Beijing, China
Corresponding author: Xiaoli, X. (xxl@emails.bjut.edu.cn)
Source title: 2009 2nd International Conference on Intelligent Computing Technology and Automation, ICICTA 2009
Abbreviated source title: Int. Conf. Intelligent Comput. Technol. Autom., ICICTA
Volume: 1
Monograph title: 2009 2nd International Conference on Intelligent Computing Technology and Automation, ICICTA 2009
Issue date: 2009
Publication year: 2009
Pages: 569-572
Article number: 5287586
Language: English
ISBN-13: 9780769538044
Document type: Conference article (CA)
Conference name: 2009 2nd International Conference on Intelligent Computing Technology and Automation, ICICTA 2009
Conference date: October 10, 2009 - October 11, 2009
Conference location: Changsha, Hunan, China
Conference code: 78591
Sponsor: IEEE Intelligent Computation Society; IEEE Computer Society; Res. Assoc. Intelligent Computation Technology and Automation; Changsha University of Science and Technology; Hunan University of Science and Technology
Publisher: IEEE Computer Society, 445 Hoes Lane - P.O.Box 1331, Piscataway, NJ 08855-1331, United States
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. ? 2009 IEEE.
Number of references: 8
Main heading: Electrochromic devices
Controlled terms: Association rules - Automobile drivers - Computer science - Electrocardiography - Experiments - Intelligent computing - Time series
Uncontrolled terms: Data analysis - Data preprocessing - Data series - Mental workload - ON time - Preprocess
Classification code: 922.2 Mathematical Statistics - 912.4 Personnel - 903.1 Information Sources and Analysis - 901.3 Engineering Research - 741.3 Optical Devices and Systems - 723.4 Artificial Intelligence - 723 Computer Software, Data Handling and Applications - 722 Computer Systems and Equipment - 721 Computer Circuits and Logic Elements - 714 Electronic Components and Tubes - 701.1 Electricity: Basic Concepts and Phenomena - 461.6 Medicine and Pharmacology - 432 Highway Transportation
DOI: 10.1109/ICICTA.2009.144
Database: Compendex
Compilation and indexing terms, ? 2010 Elsevier Inc.
全文在EV2和ACM Digital Library里面都没有,我没找到.
