A SOC Design of ORICA-based Highly Effective Real-time Multi-channel EEG System

Yun Lung Ho, Yu De Huang, Kai Yen Wang, Wai Chi Fang

研究成果: Conference contribution同行評審

摘要

Independent component analysis (ICA) has been wildly used to improve EEG based application such as brain computer interface (BCI). However, some well know ICA algorithm, such as Infomax ICA, suffering from the problem of convergence latency and make it hard to be apply on real-time application. This paper proposes a highly efficient chip implementation of multi-channel EEG real-time system based on online recursive independent component analysis algorithm (ORICA). The core size of the chip is 1.5525-mm2 using 28nm CMOS technology. The EEG demonstration board will be implemented with the ORICA chip. The operation frequency and power consumption of the chip are 100 MHz and 17.9 mW respectively. The proposed chip was validated with a real-time circuit integrated system and the average correlation coefficient between simulations results and chip processing results is 0.958.

原文English
主出版物標題2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
發行者Institute of Electrical and Electronics Engineers Inc.
頁面4762-4765
頁數4
ISBN(電子)9781538613115
DOIs
出版狀態Published - 七月 2019
事件41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019 - Berlin, Germany
持續時間: 23 七月 201927 七月 2019

出版系列

名字Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN(列印)1557-170X

Conference

Conference41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
國家Germany
城市Berlin
期間23/07/1927/07/19

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