Calibration-free SSVEP-based BCI switch

Sastry, RV and Karthik, S and Adithya, R and Ravi, A and Indrapriyadarsini, S and Panwar, G and Ramakrishnan, AG (2019) Calibration-free SSVEP-based BCI switch. In: 2019 IEEE 16th India Council International Conference (INDICON), 13-15 Dec. 2019, Rajkot, India.

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Abstract

Steady state visually evoked potentials (SSVEP) are periodic responses elicited when a participant looks at a visual stimulus flickering at a particular frequency. Brain computer interfaces (BCI) based on SSVEP have been shown to have consistent responses across most human subjects. We use this property for designing a two-state BCI switch. Canonical correlation analysis (CCA) is used to distinguish between the intentional control and the no control states of the switch. The traditional approach of using CCA for SSVEP detection uses the target frequencies only in the reference templates. This cannot be directly used to realize a BCI switch, since the templates do not incorporate the background EEG activity. To overcome this, we propose a template frequency selection method. The study is carried out on seven healthy participants. The proposed method achieves an average F1-Score of 0.95 (offline) and 0.85 (online). The mean activation time is found to be of 2.09 s (offline) and 3.01 s (online) across participants. These results indicate that the proposed system can be effectively used as a two-state BCI switch to enable control of external applications.

Item Type:	Conference Paper
Publication:	2019 IEEE 16th India Council International Conference, INDICON 2019 - Symposium Proceedings
Publisher:	Institute of Electrical and Electronics Engineers Inc.
Additional Information:	cited By 0; Conference of 16th IEEE India Council International Conference, INDICON 2019 ; Conference Date: 13 December 2019 Through 15 December 2019; Conference Code:158465
Keywords:	Electrophysiology, Calibration free; Canonical correlation analysis; Frequency selection; Periodic response; Reference templates; Steady state visually evoked potentials; Target frequencies; Traditional approaches, Brain computer interface
Department/Centre:	Division of Electrical Sciences > Electrical Engineering
Date Deposited:	23 Sep 2020 05:56
Last Modified:	23 Sep 2020 05:56
URI:	http://eprints.iisc.ac.in/id/eprint/65206

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