A 16 Channel Real-Time EEG Processing Based on ORICA Algorithm using 28nm CMOS Technology

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, we propose a system-on-chip(SOC) design of highly effective multi-channel real-time EEG signal processing system based on Online-Recursive Independent Component Analysis (ORICA) algorithm implemented using TSMC's 28nm CMOS technology. In this chip, concepts of system-on-chip (SOC) design and effective system integration technique are well-combined together to realize a highly miniaturized real-time EEG processing system. The core area and total power consumption of the chip are respectively 1246∗1246μm2 and 25.03mW. The chip operations were validated by ADVANTEST V93000 PS1600 and the results obtained match with the software simulation. The average correlation coefficient between original source signals and extracted ORICA signals reaches 0.9572. Eye blink artifact, and facial muscle artifact will be removed automatically. Producing a pure EEG signal is beneficial for real-time data analysis; therefore, this chip design can enhance the reliability and feasibility of EEG-related applications, such as BCI, medical diagnosis and depth of anesthesia detection.

Original languageEnglish
Title of host publicationProceedings of the IEEE Workshop on Signal Processing Systems, SiPS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages269-274
Number of pages6
ISBN (Electronic)9781538663189
DOIs
StatePublished - 31 Dec 2018
Event2018 IEEE Workshop on Signal Processing Systems, SiPS 2018 - Cape Town, South Africa
Duration: 21 Oct 201824 Oct 2018

Publication series

NameIEEE Workshop on Signal Processing Systems, SiPS: Design and Implementation
Volume2018-October
ISSN (Print)1520-6130

Conference

Conference2018 IEEE Workshop on Signal Processing Systems, SiPS 2018
CountrySouth Africa
CityCape Town
Period21/10/1824/10/18

Keywords

  • CMOS 28nm tehnology
  • EEG signal processing
  • ORICA algorithm
  • Real Time EEG
  • de-artifact process

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