title: Electroencephalograph (EEG) signal processing method of motor imaginary potential for attention level classification.
abstract: Research of visual attention is one of the important domains of psychology and neurophysiology. In this study, an attention related electroencephalograph (EEG) signal processing method was proposed to distinguish the different levels of people's attention during the imaginary limbs motor. There were two EEG feedback experiments (playing tennis and walking) to measure the different levels of visual attention. Three imaginary motor tasks (attention, inattention, and rest task) were performed with the flash stimulus displayed on the screen in the experiments. A nonlinear dynamics parameter of multi-scale entropy (MSE) was extracted from those EEG data recorded. According to the statistics analysis of 14 subjects, there was an obvious declining tendency of MSE with the level of attention declining, which validated the effectiveness of the proposed method to classify the visual attention level.
authors: Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin 300072, PR China. richardming@tju.edu.cn
authors: Dong
authors: D
authors: Ming
authors: Youyuan
authors: Y
authors: Xi
authors: Mingming
authors: M
authors: Zhang
authors: Hongzhi
authors: H
authors: Qi
authors: Longlong
authors: L
authors: Cheng
authors: Baikun
authors: B
authors: Wan
authors: Liyong
authors: L
authors: Li
mesh_terms: D000328:Adult; D000465:Algorithms; D001288:Attention; D001921:Brain / Q000473:pathology; D001931:Brain Mapping / Q000379:methods; D002490:Central Nervous System / Q000473:pathology; D004569:Electroencephalography / Q000379:methods*; D005246:Feedback; D006801:Humans; D015233:Models, Statistical; D009046:Motor Neurons / Q000502:physiology*; D017711:Nonlinear Dynamics; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors; D016138:Walking