TY  - JOUR
PY  - 2020//
TI  - Statistical analysis of brain connectivity estimators during distracted driving
JO  - Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
A1  - Perera, Dulan
A1  - Wang, Yu-Kai
A1  - Lin, Chin-Teng
A1  - Zheng, Jinchuan
A1  - Nguyen, Hung T.
A1  - Chai, Rifai
SP  - 3208
EP  - 3211
VL  - 2020
IS  - 
N2  - This paper presents comparison of brain connectivity estimators of distracted drivers and non-distracted drivers based on statistical analysis. Twelve healthy volunteers with more than one year of driving experience participated in this experiment. Lane-keeping tasks and the Math problem-solving task were introduced in the experiment and EEGs (electroencephalogram) were used to record the brain waves. Granger-Geweke causality (GGC), directed transfer function (DTF) and partial directed coherence (PDC) brain connectivity estimation methods were used in brain connectivity analysis. Correlation test and a student's t-test were conducted on the connectivity matrixes. <br><br>RESULTS show a significant difference between the mean of distracted drivers and non-distracted driver's brain connectivity matrixes. GGC and DTF methods student's t-tests shows a p-value below 0.05 with the correlation coefficients varying from 0.62 to 0.38. PDC connectivity estimation method does not show a significant difference between the connectivity matrixes means unless it is compared with lane keeping task and the normal driving task. Furthermore, it shows a strong positive correlation between the connectivity matrixes.<p />  <p>Language: en</p>
LA  - en
SN  - 2375-7477
UR  - http://dx.doi.org/10.1109/EMBC44109.2020.9176240
ID  - ref1
ER  -