TY  - JOUR
PY  - 2008//
TI  - Estimating vigilance in driving simulation using probabilistic PCA
JO  - Conference proceedings - IEEE engineering in medicine and biology society
A1  - Li, Mingqiang
A1  - Fu, Jia-Wei
A1  - Lu, Bao-Liang
SP  - 5000
EP  - 5003
VL  - 2008
IS  - 
N2  - In avoiding fatal consequences in accidents behind steering wheel caused by low level vigilance, EEG has shown bright prospects. In this paper, we propose a novel method for discriminating two different vigilance states of the subjects, namely wake state and sleep state, during driving a car in a simulation environment. After filtering the EEG data into a specific frequency band, we use probabilistic principle component analysis (PPCA) to reduce the data dimension. Then we model each vigilance state as a lower dimension Gaussian random variable by applying PPCA again. The feature related to class posterior probability is calculated for classification. The experimental results show satisfying time resolution (< or = 5s) and high accuracy (> or = 96%) across five subjects on both common frequency bands beta (19-26 Hz) and gamma (38-42 Hz), and a broad band (8-30 Hz).<p />  <p>Language: en</p>
LA  - en
SN  - 1557-170X
UR  - http://dx.doi.org/10.1109/IEMBS.2008.4650337
ID  - ref1
ER  -