標題: Extracting Patterns of Single-Trial EEG Using an Adaptive Learning Algorithm
作者: Lin, Chin-Teng
Wang, Yu-Kai
Fang, Chieh-Ning
Yu, Yi-Hsin
King, Jung-Tai
資訊工程學系
電控工程研究所
腦科學研究中心
Department of Computer Science
Institute of Electrical and Control Engineering
Brain Research Center
公開日期: 2015
摘要: The improvement of brain imaging technique brings about an opportunity for developing and investigating brain-computer interface (BCI) which is a way to interact with computer and environment. The measured brain activities usually constitute the signals of interest and noises. Applying the portable device and removing noise are the benefits to real-world BCI. In this study, one portable electroencephalogram (EEG) system non-invasively acquired brain dynamics through wireless transmission while six subjects participated in the rapid serial visual presentation (RSVP) paradigm. The event-related potential (ERP) was traditionally estimated by ensemble averaging (EA) to increase the signal-to-noise ratio. One adaptive filter of data-reusing radial basis function network (DR-RBFN) was also utilized as the estimator. The results showed that this portable EEG system stably acquired brain activities. Furthermore, the task-related potentials could be clearly explored from the limited samples of EEG data through DR-RBFN. According to the artifact-free data from the portable device, this study demonstrated the potential to move the BCI from laboratory research to real-life application in the near future.
URI: http://hdl.handle.net/11536/134313
ISBN: 978-1-4244-9270-1
ISSN: 1557-170X
期刊: 2015 37TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
起始頁: 6642
結束頁: 6645
Appears in Collections:Conferences Paper