Prediction of Human-Computer Interaction Intention Based on Eye Movement and Electroencephalograph Characteristics - Qu, Jue; Guo, Hao; Wang, Wei; Dang, Sina (Frontiers in Psychology, 2022)
Current method of predicting human-computer interaction intention is generally subjective, used to do simple prediction task according to single index. In addition, the method cannot do real-time prediction, provide timely and effective information feedback and operation tips. Specially, it cannot be applied to improve the cognitive efficiency of operators so as to improve its operational performance and task efficiency by reducing the operators’ cognitive load. In this paper, a novel method for identifying user’s operational intention and cognitive states in human-computer interaction is proposed. The data of eye movement and EEG was screened to obtain the real-time data of representative indicators that can reflect the operator intention. SVM algorithm was used to perform data classification and validation. Finally, a method of predicting human-computer interaction intention based on eye movement and EEG data was established. This method can accurately predict human-computer interaction intention with high accuracy compared with a single index, and can achieve real-time prediction of human-computer interaction intention.