EEG-based index for engagement level monitoring during sustained attention

被引:0
|
作者
Coelli, Stefania [1 ]
Sclocco, Roberta [1 ]
Barbieri, Riccardo [2 ]
Reni, Gianluigi [3 ]
Zucca, Claudio [4 ]
Bianchi, Anna Maria [1 ]
机构
[1] Politecn Milan, Dept Elect Informat & Bioengn, I-20133 Milan, Italy
[2] Harvard Univ, Sch Med, Massachusetts Gen Hosp, Dept Anesthesia Crit Care & Pain Med, Cambridge, MA 02138 USA
[3] IRCCS E Medea, Bioengn Lab, Bosisio Parini, Lecco, Italy
[4] IRCCS E Medea, Clin Neurophysiol Unit, Bosisio Parini, Lecco, Italy
关键词
ADAPTIVE AUTOMATION SYSTEM;
D O I
暂无
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
This paper investigates the relation between mental engagement level and sustained attention in 9 healthy adults performing a Conners' "not-X" continuous performance test (CPT), while their electroencephalographic (EEG) activity was simultaneously acquired. Spectral powers were estimated and extracted in the classical EEG frequency bands. The engagement index (beta/alpha) was calculated employing four different cortical montages suggested by the literature. Results show the efficacy of the estimated measures in detecting changes in mental state and its correlation with subject reaction times throughout the test. Moreover, the influence of the recording sites was proved underling the role of frontal cortex in maintaining a constant sustained attention level.
引用
收藏
页码:1512 / 1515
页数:4
相关论文
共 50 条
  • [1] EEG-Based Attention Tracking During Distracted Driving
    Wang, Yu-Kai
    Jung, Tzyy-Ping
    Lin, Chin-Teng
    IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 2015, 23 (06) : 1085 - 1094
  • [2] EEG-based measurement system for monitoring student engagement in learning 4.0
    Andrea Apicella
    Pasquale Arpaia
    Mirco Frosolone
    Giovanni Improta
    Nicola Moccaldi
    Andrea Pollastro
    Scientific Reports, 12
  • [3] EEG-based measurement system for monitoring student engagement in learning 4.0
    Apicella, Andrea
    Arpaia, Pasquale
    Frosolone, Mirco
    Improta, Giovanni
    Moccaldi, Nicola
    Pollastro, Andrea
    SCIENTIFIC REPORTS, 2022, 12 (01)
  • [4] The EEG-based SNAP index: as useful as the BIS index in monitoring depth of anaesthesia?
    Ruiz-Gimeno, P.
    Soro, M.
    Perez-Solaz, A.
    Carrau, M.
    Jover, J. L.
    Aguilar, G.
    Belda, F. J.
    EUROPEAN JOURNAL OF ANAESTHESIOLOGY, 2004, 21 : 33 - 34
  • [5] EEG-based monitoring of the focused attention related to athletic performance in shooters
    Liu, Y.
    Sourina, O.
    Shah, E.
    Chua, J.
    Ivanov, K.
    INTERNATIONAL JOURNAL OF PSYCHOPHYSIOLOGY, 2018, 131 : S55 - S55
  • [6] AttentioNet: Monitoring Student Attention Type in Learning with EEG-Based Measurement System
    Verma, Dhruv
    Bhalla, Sejal
    Santosh, S. V. Sai
    Yadav, Saumya
    Parnami, Aman
    Shukla, Jainendra
    2023 11TH INTERNATIONAL CONFERENCE ON AFFECTIVE COMPUTING AND INTELLIGENT INTERACTION, ACII, 2023,
  • [7] Learning EEG-based Spectral-Spatial Patterns for Attention Level Measurement
    Hamadicharef, Brahim
    Zhang, Haihong
    Guan, Cuntai
    Wang, Chuanchu
    Phua, Kok Soon
    Tee, Keng Peng
    Ang, Kai Keng
    ISCAS: 2009 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOLS 1-5, 2009, : 1465 - 1468
  • [8] Attention with kernels for EEG-based emotion classification
    Kuang, Dongyang
    Michoski, Craig
    NEURAL COMPUTING & APPLICATIONS, 2023, 36 (10): : 5251 - 5266
  • [9] ToTCompute: A Novel EEG-Based TimeOnTask Threshold Computation Mechanism for Engagement Modelling and Monitoring
    Ghergulescu I.
    Muntean C.H.
    International Journal of Artificial Intelligence in Education, 2016, 26 (3) : 821 - 854
  • [10] Attention with kernels for EEG-based emotion classification
    Dongyang Kuang
    Craig Michoski
    Neural Computing and Applications, 2024, 36 : 5251 - 5266