Abstract
Computer cursor control using electroencephalogram (EEG) signals is a common and well-studied brain-computer interface (BCI). The emphasis of the literature has been primarily on evaluation of the objective measures of assistive BCIs such as accuracy of the neural decoder whereas the subjective measures such as user's satisfaction play an essential role for the overall success of a BCI. As far as we know, the BCI literature lacks a comprehensive evaluation of the usability of the mind-controlled computer cursor in terms of decoder efficiency (accuracy), user experience, and relevant confounding variables concerning the platform for the public use. To fill this gap, we conducted a 2-D EEG-based cursor control experiment among 28 healthy participants. The computer cursor velocity was controlled by the imagery of hand movement using a paradigm presented in the literature named imagined body kinematics with a low-cost wireless EEG headset. In this article, we evaluated the usability of the platform for different objective and subjective measures while we investigated the extent to which the training phase may influence the ultimate BCI outcome. We conducted pre- and post-BCI experiment interview questionnaires to evaluate the usability. Analyzing the questionnaires and the testing phase outcome shows a positive correlation between the individuals' ability of visualization and their level of mental controllability of the cursor. Despite individual differences, analyzing training data shows the significance of electrooculogram on the predictability of the linear model. The results of this work may provide useful insights towards designing a personalized user-centered assistive BCI.
Original language | English |
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Article number | 9093862 |
Pages (from-to) | 287-297 |
Number of pages | 11 |
Journal | IEEE Transactions on Human-Machine Systems |
Volume | 50 |
Issue number | 4 |
DOIs | |
State | Published - Aug 2020 |
Bibliographical note
Funding Information:Manuscript received August 26, 2018; revised March 20, 2019, June 18, 2019, and January 2, 2020; accepted March 8, 2020. Date of publication May 14, 2020; date of current version July 14, 2020. This work was supported in part by the NeuroNET seed grant and in part by the NIH under Grant AG028383 and Grant UL1TR000117. This article was recommended by Associate Editor V. A. Prasad. (R. Abiri and S. Borhani contributed equally to this work.) (Corresponding author: Xiaopeng Zhao.) Reza Abiri is with the Department of Neurology, University of California, San Francisco, San Francisco, CA 94110 USA (e-mail: reza.abiri@ucsf.edu).
Publisher Copyright:
© 2013 IEEE.
Keywords
- Brain-computer interface (BCI)
- confounding variables
- cursor control
- electroencephalogram (EEG)
- imagined body kinematics
- usability
ASJC Scopus subject areas
- Human Factors and Ergonomics
- Control and Systems Engineering
- Signal Processing
- Human-Computer Interaction
- Computer Science Applications
- Computer Networks and Communications
- Artificial Intelligence