2 Stages-region-based P300 Speller in Brain–Computer Interface

ABSTRACT

Brain–computer interface (BCI) applications present communication model without using peripheral nerves and neuromuscular systems. The P300 waves are used in BCI applications. Signal classification accuracy is a significant parameter for P300 BCI application. In this study, our goal is to investigate P300 speller structure for higher classification accuracy. There are a lot studies about P300 speller variations of stimulus model. This models mostly includes about row–column-based visual or audio stimuli model P300 spellers. But there is not enough study about region-based P300 spellers. This study contributes to region-based P300 spellers researches. Our new paradigm 2-stages region-based P300 speller has different amount of regions and stimulus position. During the experiment also, row–column-based P300 speller was used for comparing accuracy rates with our unique design 2-stages region-based P300 speller. The subject focused on the desired character stimulus. We used the stepwise linear discriminant analysis (SWLDA) method for classification that either included the desired P300 signal or not. According to SWLDA, the maximum mean classification accuracy value of the experiment was 83.33% with 2-stages region-based P300 speller. With this new paradigm, the classification accuracy was improved by 23.89% according to the most commonly used row–column-based P300 speller.

KEYWORDS:

• Brain–computer interface
• EEG
• human–machine systems
• P300

Acknowledgements

The author would like to thank the subjects for participation in the experiments for creation database.

Additional information

Notes on contributors

Zeki Oralhan

Zeki Oralhan was born in Kayseri, Turkey in 1985. He received his BEng and PhD degree in Electrical Electronics Engineering from Erciyes University, Kayseri, Turkey in 2008 and 2016, respectively. From 2008 to 2014 he was senior engineer in a high tech firm. From 2014 to 2017 he was an advisor to Türk Telekom CEO. Since 2018, he has been as Assistant Professor with the Electrical Electronics Engineering Department, Nuh Naci Yazgan University. He also has a technology firm in techno park center of university. His research interests include: brain–computer interface, artificial learning, data mining and signal processing.