A Subject-Specific Attention Index Based on the Weighted Spectral Power

doi:10.1109/TNSRE.2024.3392242

	A Subject-Specific Attention Index Based on the Weighted Spectral Power
	Guiying Xu 1; Zhenyu Wang 1; Xi Zhao 2; Ruxue Li1,3 ; Ting Zhou 2; Tianheng Xu 1; Honglin Hu 1
	2024
发表期刊	IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING (IF:4.8[JCR-2023],5.4[5-Year])
ISSN	1558-0210
EISSN	1558-0210
卷号	32 页码:1687-1702
发表状态	已发表
DOI	10.1109/TNSRE.2024.3392242
摘要	As an essential cognitive function, attention has been widely studied and various indices based on EEG have been proposed for its convenience and easy availability for real-time attention monitoring. Although existing indices based on spectral power of empirical frequency bands are able to describe the attentional state in some way, the reliability still needs to be improved. This paper proposed a subject-specific attention index based on the weighted spectral power. Unlike traditional indices, the ranges of frequency bands are not empirical but obtained from subject-specific change patterns of spectral power of electroencephalograph (EEG) to overcome the great inter-subject variance. In addition, the contribution of each frequency component in the frequency band is considered different. Specifically, the ratio of power spectral density (PSD) function in attentional and inattentional state is utilized to calculate the weight to enhance the effectiveness of the proposed index. The proposed subject-specific attention index based on the weighted spectral power is evaluated on two open datasets including EEG data of a total of 44 subjects. The results of the proposed index are compared with 3 traditional attention indices using various statistical analysis methods including significance tests and distribution variance measurements. According to the experimental results, the proposed index can describe the attentional state more accurately. The proposed index respectively achieves accuracies of 86.21% and 70.00% at the 1% significance level in both the t-test and Wilcoxon rank-sum test for two datasets, which obtains improvements of 41.38% and 20.00% compared to the best result of the traditional indices. These results indicate that the proposed index provides an efficient way to measure attentional state. © 2001-2011 IEEE.
关键词	Attention index spectral power power spectral density EEG
URL	查看原文
收录类别	EI
语种	英语
出版者	Institute of Electrical and Electronics Engineers Inc.
EI入藏号	20241816002996
EI主题词	Power spectral density
EI分类号	461.1 Biomedical Engineering ; 461.6 Medicine and Pharmacology
原始文献类型	Journal article (JA)
来源库	IEEE
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/372809
专题	信息科学与技术学院信息科学与技术学院_本科生信息科学与技术学院_博士生
作者单位	1.Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, China 2.School of Microelectronics, Shanghai University, Shanghai, China 3.School of Information Science and Technology, ShanghaiTech University, Shanghai, China
推荐引用方式 GB/T 7714	Guiying Xu,Zhenyu Wang,Xi Zhao,et al. A Subject-Specific Attention Index Based on the Weighted Spectral Power[J]. IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING,2024,32:1687-1702.
APA	Guiying Xu.,Zhenyu Wang.,Xi Zhao.,Ruxue Li.,Ting Zhou.,...&Honglin Hu.(2024).A Subject-Specific Attention Index Based on the Weighted Spectral Power.IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING,32,1687-1702.
MLA	Guiying Xu,et al."A Subject-Specific Attention Index Based on the Weighted Spectral Power".IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING 32(2024):1687-1702.