Original scientific paper
https://doi.org/10.7307/ptt.v32i4.3303
Phase Fluctuation Analysis in Functional Brain Networks of Scaling EEG for Driver Fatigue Detection
Rongrong Fu
; Key Lab of Hebei Province, Yanshan University, Qinhuangdao, China
Mengmeng Han
orcid.org/0000-0002-0002-9730
; Key Lab of Hebei Province, Yanshan University, Qinhuangdao, China
Bao Yu
; Key Lab of Hebei Province, Yanshan University, Qinhuangdao, China
Peiming Shi
; Key Lab of Hebei Province, Yanshan University, Qinhuangdao, China
Jiangtao Wen
; Key Lab of Hebei Province, Yanshan University, Qinhuangdao, China
Abstract
The characterization of complex patterns arising from electroencephalogram (EEG) is an important problem with significant applications in identifying different mental states. Based on the operational EEG of drivers, a method is proposed to characterize and distinguish different EEG patterns. The EEG measurements from seven professional taxi drivers were collected under different states. The phase characterization method was used to calculate the instantaneous phase from the EEG measurements. Then, the optimization of drivers’ EEG was realized through performing common spatial pattern analysis. The structures and scaling components of the brain networks from optimized EEG measurements are sensitive to the EEG patterns. The effectiveness of the method is demonstrated, and its applicability is articulated.
Keywords
Hrčak ID:
242346
URI
Publication date:
16.7.2020.
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