Determination of Effective Signal Processing Stages for Brain Computer Interface on BCI Competition IV Data Set 2b: A Review Study

Abstract

Considering the entire BCI system, a big challenge is that information can be extracted from brain signals in a meaningful way. Therefore, most BCI studies are focused on brain signal processing, in which the stages are preprocessing, feature extraction, feature selection, and classification. Since each of the signal processing methods is subject-specific, it is necessary to select a specific subject group, that is, a data set, for an effective signal processing review. In this study, all stages of BCI signal processing studies that used the 2b data set recorded with the EEG method for the BCI Competition IV were compiled and compared comprehensively. To be an effective review, this paper organized into common components and showed how varying the four stages alter classification performance. Classification of performance obtained with the methods in the compiled studies was compared in terms of kappa values. The results demonstrate that combinations of different methods affect and improve the performance. This study presents comprehensive guidance by considering all stages for BCI Competition IV data set 2b. The purpose of the present study was to shed light on research with the aim to enhance BCI performance with signal processing using BCI Competition IV data set 2b.

Keywords:

• Brain computer interface
• Classification performance
• Electroencephalography
• Human-computer interaction
• Motor imagery
• Signal processing

Additional information

Funding

This work is supported by the Department of Scientific Research Projects of Erciyes University, Turkey with number of FDK-2020-9876.

Notes on contributors

Eda Dagdevir

Eda Dagdevir received the BS degree in biomedical engineering and electrical electronical engineering in 2014 and MS degree in biomedical engineering in 2017. Her academic degree is PhD in biomedical engineering, Erciyes University, Turkey in 2021. Her research interests include biomedical signal processing and brain computer interface systems. Email: [email protected]

Mahmut Tokmakci

Mahmut Tokmakci is professor in Biomedical Engineering Department and a PhD supervisor in the Institute of Natural and Applied Sciences, Erciyes University, Kayseri, Turkey. He received his BS, MS and PhD degrees 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. Corresponding author: Email: [email protected]