FPGA implementation of 4-channel ICA for on-line EEG signal separation

Wei Chung Huang*, Shao Hang Hung, Jen Feng Chung, Meng Hsiu Chang, Lan-Da Van, Chin Teng Lin

*此作品的通信作者

研究成果: Conference contribution同行評審

38 引文 斯高帕斯(Scopus)

摘要

Blind source separation of independent sources from their mixtures is a common problem for multi-sensor applications in real world, for example, speech or biomedical signal processing. This paper presents an independent component analysis (ICA) method with information maximiz ation (Infomax) update applied into 4-channel one-line EEG signal separation. This can be implemented on FPGA with a fixed-point number representation, and then the separated signals are transmitted via Bluetooth. As experimental results, the proposed design is faster 56 times than soft performance, and the correlation coefficients at least 80% with the absolute value are compared with off-line processing results. Finally, live demonstration is shown in the DE2 FPGA board, and the design is consisted of 16,605 logic elements.

原文English
主出版物標題2008 IEEE-BIOCAS Biomedical Circuits and Systems Conference, BIOCAS 2008
頁面65-68
頁數4
DOIs
出版狀態Published - 2008
事件2008 IEEE-BIOCAS Biomedical Circuits and Systems Conference, BIOCAS 2008 - Baltimore, MD, United States
持續時間: 20 11月 200822 11月 2008

出版系列

名字2008 IEEE-BIOCAS Biomedical Circuits and Systems Conference, BIOCAS 2008

Conference

Conference2008 IEEE-BIOCAS Biomedical Circuits and Systems Conference, BIOCAS 2008
國家/地區United States
城市Baltimore, MD
期間20/11/0822/11/08

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