The mind-writing pupil: A human-computer interface based on decoding of covert attention through pupillometry

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1 Laboratoire de Psychologie Cognitive, CNRS / Aix-Marseille University, Marseille, France
2 Department of Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, Netherlands
DOI
10.7287/peerj.preprints.1361v1
Published
Accepted
Subject Areas
Neuroscience, Psychiatry and Psychology
Keywords
human-computer interface, brain-computer interface, pupillometry, covert visual attention
Copyright
© 2015 Mathôt et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
Cite this article
Mathôt S, Melmi J, van der Linden L, Van der Stigchel S. 2015. The mind-writing pupil: A human-computer interface based on decoding of covert attention through pupillometry. PeerJ PrePrints 3:e1361v1

Abstract

We present a new human-computer interface that is based on decoding of attention through pupillometry. Our method builds on the recent finding that covert visual attention affects the pupillary light response: Your pupil constricts when you covertly (without looking at it) attend to a bright, compared to a dark, stimulus. In our method, participants covertly attend to one of several letters with oscillating brightness. Pupil size reflects the brightness of the selected letter, which allows us--with high accuracy and in real time--to determine which letter the participant intends to select. The performance of our method is comparable to the best covert-attention brain-computer interfaces to date, and has several advantages: no movement other than pupil-size change is required; no physical contact is required (i.e. no electrodes); it is easy to use; and it is reliable. Potential applications include: communication with totally locked-in patients, training of sustained attention, and ultra-secure password input.

Author Comment

This is a manuscript in preparation that will be submitted for publication to a peer-reviewed journal.