Evaluation of Mental Workload in Working Memory Tasks with Different Information Types Based on EEG

样本熵 脑电图 工作量 计算机科学 熵(时间箭头) 阿尔法(金融) 工作记忆 心理学 人工智能 认知心理学 模式识别(心理学) 语音识别 认知 发展心理学 神经科学 心理测量学 量子力学 结构效度 操作系统 物理
作者
Kai Guan,Xiaoke Chai,Zhimin Zhang,Qian Li,Haijun Niu
标识
DOI:10.1109/embc46164.2021.9630575
摘要

To explore the effectiveness of using Electro- encephalogram (EEG) spectral power and multiscale sample entropy for accessing mental workload in different tasks, working memory tasks with different information types (verbal, object and spatial) and various mental loads were designed based on the N-Back paradigm. Subjective scores, accuracy and response time were used to verify the rationality of the tasks. EEGs from 18 normal adults were acquired when tasks were being performed, an independent component analysis (ICA) based artifact removal method were applied to get clean data. Linear (relative power in Theta and Alpha band, etc.) and nonlinear (multiscale sample entropy) features of EEGs were then extracted. Indices that can effectively reflect mental workload levels were selected by using multivariate analysis of variance statistical approach. Results showed that with the increment of task load, power of frontal Theta, Theta/Alpha ratio and sample entropies at scale more than 10 in parietal regions increased significantly first and decreased slightly then, while the power of central-parietal Alpha decreased significantly first and increased slightly then. Considering the difference between task types, no difference in power of frontal Theta, central-parietal Alpha and sample entropies at scales more than 10 of parietal regions were found between verbal and object tasks, as well as between two spatial tasks. No difference of frontal Theta/Alpha ratio was found in all the four tasks. The results can provide evidence for the mental workload evaluation in tasks with different information types.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
二十五完成签到,获得积分10
1秒前
romeo完成签到,获得积分10
2秒前
kaka完成签到 ,获得积分10
2秒前
Akim应助xialuoke采纳,获得10
2秒前
昏睡的蟠桃应助guoxingliu采纳,获得200
3秒前
慕容松完成签到,获得积分10
4秒前
romeo发布了新的文献求助10
4秒前
ss_hHe完成签到,获得积分10
5秒前
5秒前
6秒前
zjcomposite完成签到,获得积分10
6秒前
nn发布了新的文献求助10
6秒前
css完成签到,获得积分10
6秒前
大橙子发布了新的文献求助10
7秒前
1111完成签到,获得积分10
7秒前
敏er好学完成签到,获得积分10
8秒前
细腻的谷秋完成签到 ,获得积分10
8秒前
独特的易形完成签到,获得积分10
9秒前
yangyangyang完成签到,获得积分0
12秒前
yirenli完成签到,获得积分10
13秒前
叶子完成签到 ,获得积分10
13秒前
angel完成签到,获得积分10
15秒前
正经大善人完成签到,获得积分10
17秒前
动听的秋白完成签到 ,获得积分10
18秒前
汉堡包应助biofresh采纳,获得30
18秒前
自然归尘完成签到 ,获得积分10
19秒前
缓慢海蓝完成签到 ,获得积分10
21秒前
liyiren完成签到,获得积分10
22秒前
22秒前
zhaopeipei完成签到,获得积分10
22秒前
量子星尘发布了新的文献求助10
23秒前
23秒前
调皮的老王头完成签到,获得积分10
24秒前
毅诚菌完成签到,获得积分10
25秒前
昵称完成签到,获得积分10
27秒前
欸嘿完成签到,获得积分10
28秒前
半胱氨酸发布了新的文献求助10
28秒前
31秒前
轻松白桃关注了科研通微信公众号
33秒前
34秒前
高分求助中
【提示信息,请勿应助】关于scihub 10000
Les Mantodea de Guyane: Insecta, Polyneoptera [The Mantids of French Guiana] 3000
徐淮辽南地区新元古代叠层石及生物地层 3000
The Mother of All Tableaux: Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 3000
Handbook of Industrial Diamonds.Vol2 1100
Global Eyelash Assessment scale (GEA) 1000
Picture Books with Same-sex Parented Families: Unintentional Censorship 550
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 4038201
求助须知:如何正确求助?哪些是违规求助? 3575940
关于积分的说明 11373987
捐赠科研通 3305747
什么是DOI,文献DOI怎么找? 1819274
邀请新用户注册赠送积分活动 892662
科研通“疑难数据库(出版商)”最低求助积分说明 815022