Decoding Mental Workload in Virtual Environments: A fNIRS Study using an Immersive n-back Task

F. Putze*, C. Herff, C. Tremmel, T. Schultz, D.J. Krusienski

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

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Abstract

Virtual Reality (VR) has emerged as a novel paradigm for immersive applications in training, entertainment, rehabilitation, and other domains. In this paper, we investigate the automatic classification of mental workload from brain activity measured through functional near-infrared spectroscopy (fNIRS) in VR. We present results from a study which implements the established n-back task in an immersive visual scene, including physical interaction. Our results show that user workload can be detected from fNIRS signals in immersive VR tasks both person-dependently and -adaptively.
Original languageEnglish
Title of host publication2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
PublisherIEEE Xplore
Pages3103-3106
Number of pages4
ISBN (Print)978-1-5386-1312-2
DOIs
Publication statusPublished - 1 Jan 2019

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