Tang Zhichuan, Wang Xinyang, Wu Jiayi, Ping Yaqin, Guo Xiaogang, Cui Zhixuan
Industrial Design Institute, Zhejiang University of Technology, Hangzhou, 310023, China; Modern Industrial Design Institute, Zhejiang University, Hangzhou, 310007, China.
Industrial Design Institute, Zhejiang University of Technology, Hangzhou, 310023, China.
Comput Biol Med. 2022 Nov;150:106118. doi: 10.1016/j.compbiomed.2022.106118. Epub 2022 Sep 21.
Brain-computer interfaces (BCIs) can help people with disabilities to communicate with others, express themselves, and even create art. In this paper, a BCI painting system using a hybrid control approach based on steady-state visual evoked potential (SSVEP) and P300 was developed, which can enable simple painting through brain-controlled painting tools. The BCI painting system is composed of two parts: a hybrid stimulus interface and a hybrid electroencephalogram (EEG) signal processing module. The user selects the menus and tools through the SSVEP and P300 stimulus matrices, respectively, and the paintings are displayed in the canvas area of the hybrid stimulus interface in real time. Twenty subjects participated in this study. An offline training experiment was performed to construct the P300 and SSVEP recognition models for each subject; an online painting experiment, which included a copy-painting task and a free-painting task, was performed to evaluate the BCI painting system. The results of the online painting experiment showed that the average tool selection accuracy (88.92 ± 3.94%) of the BCI painting system using the hybrid stimulus interface was slightly higher than that of the traditional brain painting system based on the P300 stimulus interface; the average information transfer rate (ITR) (74.20 ± 5.28 bpm, 71.80 ± 5.15 bpm) in the copy-painting and free-painting tasks of the BCI painting system was significantly higher than that of the traditional brain painting system. Our BCI painting system can effectively help users express their artistic creativity and improve their painting efficiency, and can provide new methods and new ideas for developing BCI-controlled applications.
脑机接口（BCIs）可以帮助残疾人与他人交流、表达自我，甚至进行艺术创作。本文开发了一种基于稳态视觉诱发电位（SSVEP）和P300的混合控制方法的脑机接口绘画系统，该系统能够通过脑控绘画工具实现简单绘画。脑机接口绘画系统由两部分组成：混合刺激界面和混合脑电图（EEG）信号处理模块。用户分别通过SSVEP和P300刺激矩阵选择菜单和工具，绘画会实时显示在混合刺激界面的画布区域。20名受试者参与了本研究。进行了离线训练实验以构建每个受试者的P300和SSVEP识别模型；进行了在线绘画实验，包括临摹绘画任务和自由绘画任务，以评估脑机接口绘画系统。在线绘画实验结果表明，使用混合刺激界面的脑机接口绘画系统的平均工具选择准确率（88.92 ± 3.94%）略高于基于P300刺激界面的传统脑控绘画系统；脑机接口绘画系统在临摹绘画和自由绘画任务中的平均信息传递率（ITR）（74.20 ± 5.28 bpm，71.80 ± 5.15 bpm）显著高于传统脑控绘画系统。我们的脑机接口绘画系统可以有效地帮助用户表达艺术创造力并提高绘画效率，并且可以为开发脑机接口控制的应用程序提供新方法和新思路。
