Workload assessment in flight using dense array EEG

被引:0
|
作者
Schnell, Tom [1 ]
Macuda, Todd [2 ]
Poolman, Pieter [3 ]
Keller, Mike [1 ]
机构
[1] Univ Iowa, OPL, Iowa City, IA 52242 USA
[2] Natl Res Council Canada, Ottawa, ON, Canada
[3] Elect Geodes Incorp, Eugene, OR USA
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
As cockpit technologies advance and increase information-rich content is provided to aircrews, and it is possible that we are reaching the cognitive limits of the human operator. With additional layers of automation, crew alertness becomes equally important as high levels of workload. Foundational tools, methods, and technology components to quantitatively assess cognitive limits and to characterize operator state are needed to improve aircraft safety and enable full realization of the Next Generation Air Transport System (NGATS). Over the last two years, we have built up a neural imaging capability onboard our Computerized Airborne Research Platform (CARP) research aircraft, a Beech Bonanza. A similar system shall be deployed on the National Research Council (NRC, Canada) Bell 412 Advanced Systems Research Aircraft (ASRA). Flight trials on the ASRA are slated for November, 2006. We have collected preliminary physiological data using the CARP in flight to demonstrate that minute EEG signals can in fact be collected in the ecologically valid context of real flight. A secondary goal of our work was to develop data synchronization and artifact removal methods. In future research, we hope to automate these methods and collect physiological data to develop sophisticated Operator State Classification and Feedback models. This research program is a collaborative effort between the National Research Council Canada and the Operator Performance Laboratory (OPL).
引用
收藏
页码:1055 / +
页数:2
相关论文
共 50 条
  • [41] Predicting Workload Experienced in a Flight Test by Measuring Workload in a Flight Simulator
    Zheng, Yiyuan
    Lu, Yanyu
    Jie, Yuwen
    Fu, Shan
    AEROSPACE MEDICINE AND HUMAN PERFORMANCE, 2019, 90 (07) : 618 - 623
  • [42] Linear and nonlinear effects of smoking/nicotine on human EEG assessed using dense-array technology
    Sokhadze, E
    Houlihan, ME
    Pritchard, WS
    Guy, TD
    Robinson, JH
    PSYCHOPHYSIOLOGY, 2002, 39 : S78 - S78
  • [43] Mental Workload Estimation using Wireless EEG Signals
    Adewale, Quadri
    Panoutsos, George
    BIOSIGNALS: PROCEEDINGS OF THE 14TH INTERNATIONAL JOINT CONFERENCE ON BIOMEDICAL ENGINEERING SYSTEMS AND TECHNOLOGIES - VOL 4: BIOSIGNALS, 2021, : 200 - 207
  • [44] Measuring driver’s mental workload using EEG
    University of Tübingen, Tübingen, Germany
    不详
    不详
    不详
    ATZ Worldw., 2008, 3 (12-17):
  • [45] Classification of Mental Workload Levels by Using EEG Signals
    Akman Aydin, Eda
    JOURNAL OF POLYTECHNIC-POLITEKNIK DERGISI, 2021, 24 (02): : 681 - 689
  • [46] THE NEW TREND OF LONG-TERM VIDEO EEG MONITORING USING DENSE-ARRAY EEG FOR PATIENTS WITH MEDICALLY REFRACTORY EPILEPSY
    Yamazaki, Madoka
    Fujimoto, A.
    Yamamoto, T.
    EPILEPSIA, 2009, 50 : 16 - 17
  • [47] Geodesic photogrammetry for localizing sensor positions in dense-array EEG
    Russell, GS
    Eriksen, KJ
    Poolman, P
    Luu, P
    Tucker, DA
    CLINICAL NEUROPHYSIOLOGY, 2005, 116 (05) : 1130 - 1140
  • [48] Identifying mental workload using EEG and deep learning
    Zhang, Qiankun
    Yuan, Ziqian
    Chen, He
    Li, Xiaoli
    2019 CHINESE AUTOMATION CONGRESS (CAC2019), 2019, : 1138 - 1142
  • [49] Complexity analysis of dense array EEG signal reveals sex difference
    Pravitha, R
    Sreenivasan, R
    Nampoori, VPN
    INTERNATIONAL JOURNAL OF NEUROSCIENCE, 2005, 115 (04) : 445 - 460
  • [50] Analysis of chaotic dynamics in EEG and its application to assessment of mental workload
    Murata, A
    Iwase, H
    PROCEEDINGS OF THE 20TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOL 20, PTS 1-6: BIOMEDICAL ENGINEERING TOWARDS THE YEAR 2000 AND BEYOND, 1998, 20 : 1579 - 1582