The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Monitoring Task Loading with Multivariate EEG Measures during Complex Forms of Human-Computer Interaction
Abstract
Electroencephalographic (EEG) recordings were made while 16 participants performed versions of a personal-computer-based flight simulation task of low, moderate, or high difficulty. As task difficulty increased, frontal midline theta EEG activity increased and alpha band activity decreased. A participant-specific function that combined multiple EEG features to create a single load index was derived from a sample of each participant's data and then applied to new test data from that participant. Index values were computed for every 4 s of task data. Across participants, mean task load index values increased systematically with increasing task difficulty and differed significantly between the different task versions. Actual or potential applications of this research include the use of multivariate EEG based methods to monitor task loading during naturalistic computer-based work.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research
(1988) · Advances in Psychology · doi:10.1016/s0166-4115(08)62386-9 · Cited by 15,003
The attention system of the human brain
Posner, M. I., & Petersen, S. E. (1990) · Annual Review of Neuroscience · doi:10.1146/annurev.ne.13.030190.000325 · Cited by 8,070
A model for types and levels of human interaction with automation
Parasuraman, R., Sheridan, T. B., & Wickens, C. D. (2000) · IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans · doi:10.1109/3468.844354 · Cited by 4,195 · cited 1×
“…might thus be valuable in task analysis research, in efforts to improve the usability of human-computer interfaces (Raskin, 2000), and in efforts to design appropriate adaptive automation strategies (Byrne & Para-suraman, 1996; Morrison & Gluckman, 1994; Parasuraman, Sheridan, & Wickens, 2000).”
BackgroundPerformance Consequences of Automation-Induced 'Complacency'
Parasuraman, R., Molloy, R., & Singh, I. L. (1993) · The International Journal of Aviation Psychology · doi:10.1207/s15327108ijap0301_1 · Cited by 875 · cited 1×
“It has been used in several prior studies of mental workload and adaptive automation (e.g., Fournier, Wilson, & Swain, 1999; Parasuraman, Molloy, & Singh, 1993; Parasuraman, Mouloua, & Molloy, 1996).”
MethodNeural systems engaged by planning: A PET study of the Tower of London task
Baker, S. C., Rogers, R. D., Owen, A. M., Frith, C. D., Dolan, R. J., Frackowiak, R. S. J., & Robbins, T. W. (1996) · Neuropsychologia · doi:10.1016/0028-3932(95)00133-6 · Cited by 635
Alpha frequency, cognitive load and memory performance
Klimesch, W., Schimke, H., & Pfurtscheller, G. (1993) · Brain Topography · doi:10.1007/bf01128991 · Cited by 530
Medial prefrontal cortex generates frontal midline theta rhythm
Ishii, R., Shinosaki, K., Ukai, S., Inouye, T., Ishihara, T., Yoshimine, T., Hirabuki, N., Asada, H., Kihara, T., Robinson, S. E., et al. (1999) · NeuroReport · doi:10.1097/00001756-199903170-00003 · Cited by 494
Psychophysiology and adaptive automation
Byrne, E. A., & Parasuraman, R. (1996) · Biological Psychology · doi:10.1016/0301-0511(95)05161-9 · Cited by 360 · cited 1×
“…might thus be valuable in task analysis research, in efforts to improve the usability of human-computer interfaces (Raskin, 2000), and in efforts to design appropriate adaptive automation strategies (Byrne & Parasuraman, 1996; Morrison & Gluckman, 1994; Parasuraman, Sheridan, & Wickens, 2000).”
BackgroundA resource model of the neural basis of executive working memory
Bunge, S. A., Klingberg, T., Jacobsen, R. B., & Gabrieli, J. D. E. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.97.7.3573 · Cited by 243
Fournier, L. R., Wilson, G. F., & Swain, C. R. (1999) · International Journal of Psychophysiology · doi:10.1016/s0167-8760(98)00049-x · Cited by 158
Cited by
Fundamentals of physiological computing
Fairclough, S. H. (2009) · Interacting with Computers · doi:10.1016/j.intcom.2008.10.011 · Cited by 608
Frontal-midline theta from the perspective of hippocampal “theta”
Mitchell, D. J., McNaughton, N., Flanagan, D., & Kirk, I. J. (2008) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2008.09.005 · Cited by 549
Berka, C., Levendowski, D. J., Cvetinovic, M. M., Petrovic, M. M., Davis, G., Lumicao, M. N., Zivkovic, V. T., Popovic, M. V., & Olmstead, R. (2004) · International Journal of Human-Computer Interaction · doi:10.1207/s15327590ijhc1702_3 · Cited by 388
Overview of the DARPA Augmented Cognition Technical Integration Experiment
St. John, M., Kobus, D. A., Morrison, J. G., & Schmorrow, D. (2004) · International Journal of Human-Computer Interaction · doi:10.1207/s15327590ijhc1702_2 · Cited by 124
Mazur, L. M., Mosaly, P. R., Moore, C., Comitz, E., Yu, F., Falchook, A. D., Eblan, M. J., Hoyle, L. M., Tracton, G., Chera, B. S., et al. (2016) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocw016 · Cited by 45
Metadata
- Authors
- Smith, M. E., Gevins, A., Brown, H., Karnik, A., & Du, R.
- Venue
- Human Factors: The Journal of the Human Factors and Ergonomics Society
- Publisher
- SAGE Publications
- Published
- 2001-09
- Volume
- 43
- Issue
- 3
- Pages
- 366-380
- ISSN
- 0018-7208 (ISSN-L)
- 1547-8181
- OpenAlex
- W2131180276
- Cited by
- 214
- References
- 10
- FWCI
- 3.26
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Monitoring Task Loading with Multivariate EEG Measures during Complex Forms of Human-Computer Interaction. https://app.cochat.ai/papers/10.1518/001872001775898287
- The paper
- Smith, M. E., Gevins, A., Brown, H., Karnik, A., & Du, R. (2001). Monitoring Task Loading with Multivariate EEG Measures during Complex Forms of Human-Computer Interaction. Human Factors: The Journal of the Human Factors and Ergonomics Society. https://doi.org/10.1518/001872001775898287
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
