 This paper proposes a novel approach to improving the user experience for steady-state visual evoked brain-computer interfaces, SSVPBCI. It uses a combination of user-independent, UI, models, user-dependent, UDT, data, and online adaptation techniques to reduce calibration efforts and increase model performance. The proposed method was tested on both offline and online experiments, where it demonstrated improved performance compared to existing methods. Additionally, the proposed method reduced calibration efforts by up to 160 trials per user while maintaining high prediction accuracy. This article was authored by Nan Linsher, Xiang Li, Bing Chuan Lu, and others.