An EEG monitoring method based on compressed sensing for fatigue driving

Zengnian Xin

Computer Methods in Biomechanics and Biomedical Engineering, 2024, vol. 27, issue 9, 1206-1213

Abstract: In order to reduce the amount of EEG collected by the fatigue driving monitoring system, this paper proposes a new EEG monitoring method based on compressed sensing. According to the driver’s driving duration, the new proposed method adopts different sampling rate to compressive sample the EEG of the driver in different driving stages, and then realizes the accurate reconstruction of the compressed EEG data in the computer of vehicle. The experiment verifies effectiveness of the proposed method by collecting EEG signals from multiple subjects during simulated driving. The experimental results show that, compared with traditional sampling, the new method reduces the amount of sampled data by 3 orders of magnitude. And when the compression ratio is not higher than 70%, the reconstruction error is less than 0.16.

Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/10255842.2024.2308703 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:gcmbxx:v:27:y:2024:i:9:p:1206-1213

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/gcmb20

DOI: 10.1080/10255842.2024.2308703

Access Statistics for this article

Computer Methods in Biomechanics and Biomedical Engineering is currently edited by Director of Biomaterials John Middleton

More articles in Computer Methods in Biomechanics and Biomedical Engineering from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().