The brain-computer interface (BCI) has been investigated as a form of communication tool between the brain and external devices. BCIs have been extended beyond communication and control over the years. The 2020 international BCI competition aimed to provide high-quality neuroscientific data for open access that could be used to evaluate the current degree of technical advances in BCI. Although there are a variety of remaining challenges for future BCI advances, we discuss some of more recent application directions: (i) few-shot EEG learning, (ii) micro-sleep detection (iii) imagined speech decoding, (iv) cross-session classification, and (v) EEG(+ear-EEG) detection in an ambulatory environment. Not only did scientists from the BCI field compete, but scholars with a broad variety of backgrounds and nationalities participated in the competition to address these challenges. Each dataset was prepared and separated into three data that were released to the competitors in the form of training and validation sets followed by a test set. Remarkable BCI advances were identified through the 2020 competition and indicated some trends of interest to BCI researchers.
Bibliographical noteFunding Information:
This research was partly supported by an Institute of Information & Communications Technology Planning & Evaluation (IITP) grant, funded by the Korea government (No. 2017-0-00451) and also this work was supported by the research grant of the Chungbuk National University in 2022.
Copyright © 2022 Jeong, Cho, Lee, Lee, Shin, Kweon, Millán, Müller and Lee.
- brain-computer interface (BCI)
- neural decoding
- open datasets
ASJC Scopus subject areas
- Neuropsychology and Physiological Psychology
- Psychiatry and Mental health
- Biological Psychiatry
- Behavioral Neuroscience