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博士生姚普林参加国际会议回国报告

发布时间:2018-09-04 点击数:

汇报题目:参加在美国夏威夷召开的EMBC2018国际会议

汇报时间201894(星期二) 1400

汇报地点:曲江校区西五楼228会议室

汇报人:姚普林

会议名称40th International Conference of the IEEE Engineering in Medicine and Biology Society

会议时间July 17-21, 2018

会议地点Hawai’i Convention Center in Honolulu, HIUSA

会议简介The IEEE Engineering in Medicine and Biology Society is pleased to announce the 40th International Engineering in Medicine and Biology Conference, to be held in Honolulu, Hawaii from July 17-21, 2018. The theme of the meeting is “Learning from the Past, Looking to the Future”, inspired by the 40th anniversary of the world’s largest international biomedical engineering meeting. Consistent with our theme, we have arranged plenary keynotes from leading industrial and academic scientists, who will give forward looking visions as well as historical perspectives on our field. A broad array of scientific tracks will cover diverse topics of cutting-edge research and innovation in biomedical engineering, healthcare technology R&D, translational clinical research, technology transfer and entrepreneurship, and biomedical engineering education. In addition to the high-profile keynotes, the conference program will feature mini symposia, workshops, invited sessions, oral and poster sessions, sessions for students and young professions, sessions for clinicians and entrepreneurs, and exhibits from vendors and universities.

会议交流工作

Oral Presentation:

报告人:姚普林

参加论文信息

Title: SSVEP Transient Feature Extraction and Rapid Recognition Method Based on Bistable Stochastic Resonance

Author: Pulin Yao, Guanghua Xu, Member, IEEE, Chengcheng Han, Linshan Jia, Qing Zhang, Sicong Zhang and Ailing Luo

Abstract: Steady-state Visual Evoked Potential, SSVEP), as the most commonly used communication paradigm for non-implantable Brain-Computer Interface (BCI), boasts the advantages of no training, noise immunity and obvious periodicity. The traditional SSVEP extraction methods can effectively identify the target frequency contained in original EEG, however, the required data length usually lasts a few seconds. In this paper, bistable stochastic resonance (BSR) is applied to SSVEP extraction. BSR is very sensitive to amplitude mutation and frequency fluctuation of the input signal, making the output difference can be used for the detection of the target frequency. The processing results illustrate that the proposed method not only has a high recognition accuracy, but also effectively shortens the recognition time, thus improving the calculating speed. Therefore, SSVEP extraction based on bistable stochastic resonance has a higher information transfer rate (ITR), which is more suitable for the real-time BCI system.

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