Title :
An effective chip implementation of a real-time eight-channel EEG signal processor based on on-line recursive ICA algorithm
Author :
Wei-Yeh Shih ; Kuan-Ju Huang ; Chiu-Kuo Chen ; Wai-Chi Fang ; Cauwenberghs, Gert ; Tzyy-Ping Jung
Author_Institution :
Dept. of Electr. Eng. & Inst. of Electron., Nat. Chiao Tung Univ., Hsinchu, Taiwan
Abstract :
This paper presents an effective chip implementation of a real-time eight-channel electroencephalogram signal processor based on on-line recursive independent component analysis (ORICA) algorithm. The system architecture is composed of a memory unit, a whitening unit, an ORICA training unit, and an ORICA computation unit. The proposed architecture is implemented using TSMC 90 nm CMOS technology. It occupies a core area of 800×800 μm2 and consumes 4.18 mW at a core supply voltage of 1.0 V and 50 MHz clock operating frequency. Simulated super and sub-Gaussian signals are used to verify the system. The separated signals match those obtained using off-line Matlab-based analysis.
Keywords :
CMOS integrated circuits; biomedical equipment; electroencephalography; independent component analysis; medical signal processing; source separation; CMOS technology; ORICA computation unit; ORICA training unit; chip implementation; clock operating frequency; frequency 50 MHz; memory unit; off-line Matlab-based analysis; on-line recursive ICA algorithm; on-line recursive independent component analysis; real-time eight-channel EEG signal processor; real-time eight-channel electroencephalogram signal processor; signal separation; simulated subGaussian signals; simulated super signals; size 90 nm; system architecture; voltage 1.0 V; whitening unit; Algorithm design and analysis; Computer architecture; Convergence; Electroencephalography; Independent component analysis; Signal processing algorithms; Training;
Conference_Titel :
Biomedical Circuits and Systems Conference (BioCAS), 2012 IEEE
Conference_Location :
Hsinchu
Print_ISBN :
978-1-4673-2291-1
Electronic_ISBN :
978-1-4673-2292-8
DOI :
10.1109/BioCAS.2012.6418464