ERP prototypical matching net: a meta-learning method for zero-calibration RSVP-based image retrieval
文献类型：期刊论文
| 作者 | Wei, Wei1 ; Qiu, Shuang1; Zhang, Yukun1,3; Mao, Jiayu1,3; He, Huiguang1,2
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| 刊名 | JOURNAL OF NEURAL ENGINEERING
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| 出版日期 | 2022-04-01 |
| 卷号 | 19期号:2页码:17 |
| 关键词 | EEG RSVP-based BCI zero-calibration meta-learning prototypical matching |
| ISSN号 | 1741-2560 |
| DOI | 10.1088/1741-2552/ac5eb7 |
| 通讯作者 | He, Huiguang(huiguang.he@ia.ac.cn) |
| 英文摘要 | Objective. A rapid serial visual presentation (RSVP)-based brain-computer interface (BCI) is an efficient information detection technology through detecting event-related potentials (ERPs) evoked by target visual stimuli. The BCI system requires a time-consuming calibration process to build a reliable decoding model for a new user. Therefore, zero-calibration has become an important topic in BCI research. Approach. In this paper, we construct an RSVP dataset that includes 31 subjects, and propose a zero-calibration method based on a metric-based meta-learning: ERP prototypical matching net (EPMN). EPMN learns a metric space where the distance between electroencephalography (EEG) features and ERP prototypes belonging to the same category is smaller than that of different categories. Here, we employ prototype learning to learn a common representation from ERP templates of different subjects as ERP prototypes. Additionally, a metric-learning loss function is proposed for maximizing the distance between different classes of EEG and ERP prototypes and minimizing the distance between the same classes of EEG and ERP prototypes in the metric space. Main results. The experimental results showed that EPMN achieved a balanced-accuracy of 86.34% and outperformed the comparable methods. Significance. Our EPMN can realize zero-calibration for an RSVP-based BCI system. |
| WOS关键词 | SERIAL VISUAL PRESENTATION ; MOTOR IMAGERY ; COMPUTER ; BCI ; POTENTIALS ; MODEL |
| 资助项目 | National Natural Science Foundation of China[62020106015] ; National Natural Science Foundation of China[61976209] ; National Natural Science Foundation of China[U21A20388] ; CAS International Collaboration Key Project[173211KYSB20190024] ; Strategic Priority Research Program of CAS[XDB32040000] ; Beijing Natural Science Foundation[J210010] |
| WOS研究方向 | Engineering ; Neurosciences & Neurology |
| 语种 | 英语 |
| WOS记录号 | WOS:000777811400001 |
| 出版者 | IOP Publishing Ltd |
| 资助机构 | National Natural Science Foundation of China ; CAS International Collaboration Key Project ; Strategic Priority Research Program of CAS ; Beijing Natural Science Foundation |
| 源URL | [http://ir.ia.ac.cn/handle/173211/48240]  |
| 专题 | 类脑智能研究中心_神经计算及脑机交互 |
| 通讯作者 | He, Huiguang |
| 作者单位 | 1.Chinese Acad Sci, Res Ctr Brain Inspired Intelligence, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China 2.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing, Peoples R China 3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wei, Wei,Qiu, Shuang,Zhang, Yukun,et al. ERP prototypical matching net: a meta-learning method for zero-calibration RSVP-based image retrieval[J]. JOURNAL OF NEURAL ENGINEERING,2022,19(2):17. |
| APA | Wei, Wei,Qiu, Shuang,Zhang, Yukun,Mao, Jiayu,&He, Huiguang.(2022).ERP prototypical matching net: a meta-learning method for zero-calibration RSVP-based image retrieval.JOURNAL OF NEURAL ENGINEERING,19(2),17. |
| MLA | Wei, Wei,et al."ERP prototypical matching net: a meta-learning method for zero-calibration RSVP-based image retrieval".JOURNAL OF NEURAL ENGINEERING 19.2(2022):17. |
入库方式： OAI收割
来源：自动化研究所
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