The influence of paradigm interface guided by different visual types on MI-BCI performance

Jiang Shao, Yuxin Bai, Jun Yao, Ying Zhang, Fangyuan Tian and Chengqi Xue

Behaviour and Information Technology, 2025, vol. 44, issue 1, 120-130

Abstract: Visual paradigms of Brain-Computer Interfaces (BCI) for motor imagery (MI) tasks are the basis for communication through (electroencephalogram) EEG signals. During the MI-BCI user training process, this study analyzes and summarises four different visual paradigms and compares their impact on the outcomes of MI-BCI training. Four different visual paradigms are experimentally compared through classification outcomes and subjective evaluation. EEG features were extracted via Common Spatial Patterns (CSP) and passed to a Support Vector Machine (SVM) model for their classification. The results show that all four types of visual paradigms have a significant impact on the outcomes of MI-BCI training, with Paradigm Set II having the most significant impact. This is because paradigm set II offers a paradigm interface with relatively low visual complexity on the basis of action observation, and visual guidance with more clarity and more accurate EEG classification.

Date: 2025
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DOI: 10.1080/0144929X.2024.2312436

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