Using neurophysiological signals that reflect cognitive or affective state: Six recommendations to avoid common pitfalls

Anne-Marie Brouwer, Thorsten O. Zander, Jan B.F. van Erp, Johannes E. Korteling, Adelbert W. Bronkhorst

    Research output: Contribution to journalArticleAcademicpeer-review

    64 Citations (Scopus)
    67 Downloads (Pure)

    Abstract

    Estimating cognitive or affective state from neurophysiological signals and designing applications that make use of this information requires expertise in many disciplines such as neurophysiology, machine learning, experimental psychology, and human factors. This makes it difficult to perform research that is strong in all its aspects as well as to judge a study or application on its merits. On the occasion of the special topic “Using neurophysiological signals that reflect cognitive or affective state‿ we here summarize often occurring pitfalls and recommendations on how to avoid them, both for authors (researchers) and readers. They relate to defining the state of interest, the neurophysiological processes that are expected to be involved in the state of interest, confounding factors, inadvertently “cheating‿ with classification analyses, insight on what underlies successful state estimation, and finally, the added value of neurophysiological measures in the context of an application. We hope that this paper will support the community in producing high quality studies and well-validated, useful applications.
    Original languageEnglish
    Pages (from-to)136
    Number of pages11
    JournalFrontiers in human neuroscience
    Volume9
    DOIs
    Publication statusPublished - 30 Apr 2015

    Keywords

    • EEG
    • Neuroergonomics
    • Passive BCI
    • Physiological computing
    • Affective Computing
    • Applied neuroscience
    • Mental state estimation

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