NDLI: Vigilance detection based on sparse representation of EEG

Content Provider	IEEE Xplore Digital Library
Author	Hongbin Yu Hongtao Lu Tian Ouyang Hongjun Liu Bao-Liang Lu
Copyright Year	2010
Description	Author affiliation: Department of Computer Science and Engineering, Shanghai Jiao Tong University, China (Tian Ouyang; Hongjun Liu) \|\| Department of Computer Science and Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road Min, Hang District, China (Hongbin Yu) \|\| MOE-Microsoft Laboratory for Intelligent Computing and Intelligent Systems, and the Department of Computer Science and Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road Min Hang District, China (Hongtao Lu; Bao-Liang Lu)
Abstract	Electroencephalogram (EEG) based vigilance detection of those people who engage in long time attention demanding tasks such as monotonous monitoring or driving is a key field in the research of brain-computer interface (BCI). However, robust detection of human vigilance from EEG is very difficult due to the low SNR nature of EEG signals. Recently, compressive sensing and sparse representation become successful tools in the fields of signal reconstruction and machine learning. In this paper, we propose to use the sparse representation of EEG to the vigilance detection problem. We first use continuous wavelet transform to extract the rhythm features of EEG data, and then employ the sparse representation method to the wavelet transform coefficients. We collect five subjects' EEG recordings in a simulation driving environment and apply the proposed method to detect the vigilance of the subjects. The experimental results show that the algorithm framework proposed in this paper can successfully estimate driver's vigilance with the average accuracy about 94.22 %. We also compare our algorithm framework with other vigilance estimation methods using different feature extraction and classifier selection approaches, the result shows that the proposed method has obvious advantages in the classification accuracy.
Starting Page	2439
Ending Page	2442
File Size	271408
Page Count	4
File Format	PDF
ISBN	9781424441235
ISSN	1557170X
DOI	10.1109/IEMBS.2010.5626084
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-31
Publisher Place	Argentina
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electroencephalography Feature extraction Accuracy Training Continuous wavelet transforms Sleep Sparse Representation Electroencephalograph (EEG) Vigilance Brain Computer Interface Continuous Wavelet Transform
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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