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 language | English |
---|---|
Title of host publication | 2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) |
Publisher | IEEE Xplore |
Pages | 3103-3106 |
Number of pages | 4 |
ISBN (Print) | 978-1-5386-1312-2 |
DOIs | |
Publication status | Published - 1 Jan 2019 |