Proceedings of the 10th Conference on Man-Machine-Environment System Engineering (MMESE 2010 E-BOOK)

Sanya,China,10.22-10.26,2010

ISBN: 978-1-935068-14-3 Scientific Research Publishing, USA

E-Book 514pp Pub. Date: November 2010

Category: Engineering

Price: $80

Title: Selecting Operator’s Mental Workload Features by Means of HRV Analysis
Source: Proceedings of the 10th Conference on Man-Machine-Environment System Engineering (MMESE 2010 E-BOOK) (pp 12-16)
Author(s): Shaozeng Yang, School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China
Jianhua Zhang, School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China
Xingyu Wang, School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China
Abstract: As a fundamental work in the modeling and classification of Operator Functional State (OFS), the selection of input feature set which can best characterize operators’ mental workload (MWL) is very important. Previous work shows that Heart Rate Variability (HRV) could well characterize MWL. However, there are many HRV indices. To obtain a parsimonious and effective set of HRV indices as model input features, this paper analyzes 11 subjects’ heart rate data by autoregressive modeling (ARM) based spectral analysis method. After computing the correlation coefficients between MWL and HRV indices, the paper selects available indices for each subject. The result shows that each selected index reflects MWL to a certain extent. It also shows that there are comparatively great individual differences among subjects.
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