Detecting sustained attention during cognitive work using heart rate variability

Cho Yan Chen, Chi Jen Wang, E. Liang Chen, Chi Keng Wu, Yen Kuang Yang, Jeen Shing Wang, Pau Choo Chung

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)

Abstract

Sustained attention is an important requirement when we are doing vigilant works. The detection of whether a worker is in sustained attention stage is important to maintain the safety of the worker. Thus this paper performs classification of sustained attention and non sustained attention phases based on the heart rate variability (HRV). To achieve this purpose several features are derived from time domain, frequency domain and nonlinear analysis from Electrocardiogram (ECG). Then linear discriminant analysis (LDA) with K-nearest neighbor (KNN) is adopted as the classifier. It was found that the proposed method is promising in classifying the sustained attention and non sustained attention with 98% of accuracy.

Original languageEnglish
Title of host publicationProceedings - 2010 6th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2010
Pages372-375
Number of pages4
DOIs
Publication statusPublished - 2010
Event6th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2010 - Darmstadt, Germany
Duration: 2010 Oct 152010 Oct 17

Publication series

NameProceedings - 2010 6th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2010

Other

Other6th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2010
Country/TerritoryGermany
CityDarmstadt
Period10-10-1510-10-17

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Information Systems
  • Signal Processing

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