A transplantation of subject-independent model in cross-platform BCI

作者：Zhao, Yawei; Wang, Zhongpeng; Zhang, Zhen; Liu, Jing; Chen, Long; Qi, Hongzhi^*; Jiao, Xuejun; He, Feng; Zhou, Peng; Ming, Dong

来源：International Journal of Machine Learning and Cybernetics, 2018, 9(6): 959-967.

DOI：10.1007/s13042-016-0620-1

• Subject-independent BCI
• ERP
• P300-Speller
• Cross-platform
• LDA

With the development of wearable technology, portable wireless systems have been used gradually for collecting electroencephalogram (EEG) signals. However, the introduction of portable collection devices always means a descent in signal-to-noise ratio (SNR) of EEG. Subject-independent brain-computer interface (BCI) avoids conventional calibration procedure for new users. However, whether subject-independent model can be used in cross-platform BCI has not been discussed so far. This paper transplanted the subject-independent model from a high-SNR platform to a lower one for recognition in P300-Speller. After comparing their EEG features elicited from diverse collection platforms, a model adjustment strategy was proposed to increase recognition accuracy. By model adjustment, the average accuracy was 85.00% in online spell experiments. The results indicate it is feasible for subject-independent model transplantation, especially after model adjustment strategy. It provides technology supported for further development of cross-platform BCI.

• 出版日期2018-6
• 单位天津大学; 中国航天员科研训练中心