TY - GEN
T1 - Neural Signature and Classification of Emergency Braking Intention Based on Effective Connectivity
AU - Wang, Huikang
AU - Fei, Weiiie
AU - Bi, Luzheng
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - In this paper, to further understand the neural mechanism of emergency braking and find new features for emergency braking intention detection, we explore the brain neural correlates of emergency braking intentions by using effective connectivity analysis, which is based on directed transfer function (DTF). Offline analysis shows there exists changes in connectivity between electrodes before and after the onset of emergency. Furthermore, a novel method of emergency braking intention classification was proposed based on connectivity features. Area under curve (AUC) is calculated to evaluate the classification performance of connectivity features. Three preprocessing method were compared. The average AUC of the best method can reach 0.8632, which shows a good classification. This research is of great value for the future development of brain-controlled vehicles.
AB - In this paper, to further understand the neural mechanism of emergency braking and find new features for emergency braking intention detection, we explore the brain neural correlates of emergency braking intentions by using effective connectivity analysis, which is based on directed transfer function (DTF). Offline analysis shows there exists changes in connectivity between electrodes before and after the onset of emergency. Furthermore, a novel method of emergency braking intention classification was proposed based on connectivity features. Area under curve (AUC) is calculated to evaluate the classification performance of connectivity features. Three preprocessing method were compared. The average AUC of the best method can reach 0.8632, which shows a good classification. This research is of great value for the future development of brain-controlled vehicles.
KW - connectivity
KW - electroencephalography (EEG)
KW - emergency
UR - http://www.scopus.com/inward/record.url?scp=85062796240&partnerID=8YFLogxK
U2 - 10.1109/CAC.2018.8623768
DO - 10.1109/CAC.2018.8623768
M3 - Conference contribution
AN - SCOPUS:85062796240
T3 - Proceedings 2018 Chinese Automation Congress, CAC 2018
SP - 2559
EP - 2562
BT - Proceedings 2018 Chinese Automation Congress, CAC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 Chinese Automation Congress, CAC 2018
Y2 - 30 November 2018 through 2 December 2018
ER -