Work

Visual tracking brain computer interface

Year: 2023

Type: preprint

Abstract: Brain-computer interfaces (BCIs) offer a way to interact with computers without relying on physical movements. Non-invasive electroencephalography (EEG)-based visual BCIs, known for efficient speed and calibration ease, face limitations in continuous tasks due to discrete stimulus design and decoding methods. To achieve continuous control, we implemented a novel spatial encoding stimulus paradigm and devised a corresponding projection method to enable continuous modulation of decoded velocity. Subsequently, we conducted experiments involving 17 participants and achieved Fitt's ITR of 0.55 bps for the fixed tracking task and 0.37 bps for the random tracking task. The proposed BCI with a high Fitt's ITR was then integrated into two applications, including painting and gaming. In conclusion, this study proposed a visual BCI-based control method to go beyond discrete commands, allowing natural continuous control based on neural activity.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2311.12592

Authors: Huang, Changxing, Shi, Nanlin, Miao, Yining, Chen, Xiaogang, Wang, Yijun, Gao, Xiaorong

Institutions: Institute of Biomedical Engineering, Chinese Academy of Medical Sciences, Chinese Academy of Sciences, State Key Laboratory on Integrated Optoelectronics, Institute of Semiconductors, Tsinghua University

Language: English

Topic: EEG and Brain-Computer Interfaces

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: green

OpenAlex ID: W4388962876

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