The present application is applicable to the field of computer application technology, and provides methods and devices for detecting driver distraction, including: acquiring the EEG data of the driver; preprocessing the EEG data, and then inputting it into a pre-trained distraction detection model to obtain the distraction detection result of the driver; obtaining the distracted detection model by training a preset convolution-recurrent neural network using EEG sample data and corresponding distracted result label; sending the distraction detection result to an in-vehicle terminal associated with the identity information of the driver, wherein the distraction detection result is used to trigger the in-vehicle terminal to generate driving reminder information according to the distraction detection result. When detecting driver distraction, the accuracy and efficiency are improved, thereby reducing the probability of traffic accidents.
METHOD AND DEVICE FOR DETECTING DRIVER DISTRACTION