The Effect of Duty Cycle and Brightness Variation of Visual Stimuli on SSVEP in Brain Computer Interface Systems

ABSTRACT

Stimulation methods are very significant for the performance of electroencephalogram (EEG)-based brain–computer interface (BCI) systems. This study aims to investigate methods for obtaining higher information transfer rate (ITR) through duty cycle and brightness variation of visual stimuli for steady-state visual evoked potential-based BCI. Although previous studies were concentrated on either duty cycle or brightness of stimuli separately, our study focused on the change of duty cycle and brightness of stimuli at the same time. Duty cycle values of 20%, 40%, 50%, 60%, and 80% were used. During the experiment, 16 flickering stimuli with a frequency range between 5 and 20 Hz were used on liquid crystal display. Subjects gazed to the flickers which had frequencies of 6, 12 and 15 Hz. Canonical correlation analyses (CCA), a multivariate statistical method, was used for channel selection and frequency detection. According to the CCA, the maximum average accuracy of the experiment was 96.88% when the frequency of flicker was in beta band and its duty cycle was 40% with a brightness tuning wave. Under the same conditions stated above, average ITR was improved 25.38% according to the most commonly used flicker model which is square wave and has 50% duty cycle.

KEYWORDS:

• Brain–computer interface
• EEG
• Human computer interaction
• Steady-state visual evoked potential

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work is supported by Department of Scientific Research Projects of Erciyes University, Turkey [grant number 2014-5204 FDK].

Notes on contributors

Zeki Oralhan

Zeki Oralhan received his BEng degree in Electrical Electronics Engineering from Erciyes University, Kayseri, Turkey, in 2008. Currently, he is a PhD student in Electrical and Electronics Engineering at the Institute of Natural and Applied Sciences, Erciyes University, Turkey. His research interests includes: brain–computer interface and signal processing. He is working as an engineer in a company operating in the field of information and communication technology.

E-mail: [email protected]

Mahmut Tokmakçi

Mahmut Tokmakçı is an associate professor in Biomedical Engineering Department and a PhD supervisor in the Institute of Natural and Applied Sciences, Erciyes University, Kayseri, Turkey. He received his B.Eng. M.Eng and PhD degree from Electrical and Electronics Engineering Department from Erciyes University, Kayseri, Turkey in 1994, 1996, and 2003, respectively. His research interests includes: microelectronics, embedded systems, electronics, biomedical, and signal processing.

E-mail: [email protected]