@inproceedings{8f85686745f54d31a209b8fffc5d7a81,
title = "Detection of Driver Emergency Steering Intention Using EMG Signal",
abstract = "In this paper, a method to detect driver emergency-steering intention by using Electromyography (EMG) signals is presented. An emergency driving situation, where a driver tries to avoid collisions by steering alone, is anticipated. EMG signals are acquired from the upper limb, while the driver steers a vehicle under normal and emergency driving situations. A linear discriminant analysis (LDA) and multilayer perceptron (MLP) classifiers are constructed to detect the emergency steering from normal steering during driving. Our experimental results show that the emergency steering situation can be detected from EMG signal at about 607ms after the onset of visual stimuli and before a collision happens with an accuracy of greater than 86\%.",
keywords = "Driver intention, Driving Assistant, Electromyography (EMG), Emergency steering",
author = "Feleke, \{Aberham Genetu\} and Luzheng Bi and Weijie Fei",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020 ; Conference date: 28-09-2020 Through 29-09-2020",
year = "2020",
month = sep,
day = "28",
doi = "10.1109/RCAR49640.2020.9303261",
language = "English",
series = "2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "280--285",
booktitle = "2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020",
address = "United States",
}