Virtual and Actual Humanoid Robot Control with Four-Class Motor-Imagery-Based Optical Brain-Computer Interface
Joint Authors
Ayaz, Hasan
Batula, Alyssa M.
Kim, Youngmoo E.
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-07-18
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Motor-imagery tasks are a popular input method for controlling brain-computer interfaces (BCIs), partially due to their similarities to naturally produced motor signals.
The use of functional near-infrared spectroscopy (fNIRS) in BCIs is still emerging and has shown potential as a supplement or replacement for electroencephalography.
However, studies often use only two or three motor-imagery tasks, limiting the number of available commands.
In this work, we present the results of the first four-class motor-imagery-based online fNIRS-BCI for robot control.
Thirteen participants utilized upper- and lower-limb motor-imagery tasks (left hand, right hand, left foot, and right foot) that were mapped to four high-level commands (turn left, turn right, move forward, and move backward) to control the navigation of a simulated or real robot.
A significant improvement in classification accuracy was found between the virtual-robot-based BCI (control of a virtual robot) and the physical-robot BCI (control of the DARwIn-OP humanoid robot).
Differences were also found in the oxygenated hemoglobin activation patterns of the four tasks between the first and second BCI.
These results corroborate previous findings that motor imagery can be improved with feedback and imply that a four-class motor-imagery-based fNIRS-BCI could be feasible with sufficient subject training.
American Psychological Association (APA)
Batula, Alyssa M.& Kim, Youngmoo E.& Ayaz, Hasan. 2017. Virtual and Actual Humanoid Robot Control with Four-Class Motor-Imagery-Based Optical Brain-Computer Interface. BioMed Research International،Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1133940
Modern Language Association (MLA)
Batula, Alyssa M.…[et al.]. Virtual and Actual Humanoid Robot Control with Four-Class Motor-Imagery-Based Optical Brain-Computer Interface. BioMed Research International No. 2017 (2017), pp.1-13.
https://search.emarefa.net/detail/BIM-1133940
American Medical Association (AMA)
Batula, Alyssa M.& Kim, Youngmoo E.& Ayaz, Hasan. Virtual and Actual Humanoid Robot Control with Four-Class Motor-Imagery-Based Optical Brain-Computer Interface. BioMed Research International. 2017. Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1133940
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1133940