TY - GEN
T1 - A VLSI design of singular value decomposition processor used in real-time ICA computation for multi-channel EEG system
AU - Huang, Kuan Ju
AU - Shih, Wei Yeh
AU - Liao, Jui Chieh
AU - Fang, Wai-Chi
PY - 2013
Y1 - 2013
N2 - This paper presents a VLSI design of singular value decomposition (SVD) processor used in real-time independent component analysis (ICA) computation for multi-channel electroencephalography (EEG) system. EEG signals are easily influenced by other artifacts. To acquire artifact free EEG signals, ICA is a popular method for artifact removal. Results obtained after the pre-processing of ICA are often used for further applications such as brain computer interfaces (BCIs). In order to improve the feasibility and convenience of BCIs, a real-time ICA pre-processing is required. Because SVD is used frequently in computations of ICA, a SVD processor used for real-time ICA computation is essential. This paper aims to develop a custom SVD for multi-channel EEG systems based on ICA. During the ICA process, the proposed processor aims to solve the inverse and inverse square root matrices in real time. And the processor obtains a highly accurate result since a novel design concept for renewing data flow and parallel data processing are provided in this research. This processor is developed with TSMC 90nm CMOS technology in an 8-channel EEG system. The performance of the proposed SVD is also provided with the processing result of the EEG system.
AB - This paper presents a VLSI design of singular value decomposition (SVD) processor used in real-time independent component analysis (ICA) computation for multi-channel electroencephalography (EEG) system. EEG signals are easily influenced by other artifacts. To acquire artifact free EEG signals, ICA is a popular method for artifact removal. Results obtained after the pre-processing of ICA are often used for further applications such as brain computer interfaces (BCIs). In order to improve the feasibility and convenience of BCIs, a real-time ICA pre-processing is required. Because SVD is used frequently in computations of ICA, a SVD processor used for real-time ICA computation is essential. This paper aims to develop a custom SVD for multi-channel EEG systems based on ICA. During the ICA process, the proposed processor aims to solve the inverse and inverse square root matrices in real time. And the processor obtains a highly accurate result since a novel design concept for renewing data flow and parallel data processing are provided in this research. This processor is developed with TSMC 90nm CMOS technology in an 8-channel EEG system. The performance of the proposed SVD is also provided with the processing result of the EEG system.
UR - http://www.scopus.com/inward/record.url?scp=84883397033&partnerID=8YFLogxK
U2 - 10.1109/ISCAS.2013.6571868
DO - 10.1109/ISCAS.2013.6571868
M3 - Conference contribution
AN - SCOPUS:84883397033
SN - 9781467357609
T3 - Proceedings - IEEE International Symposium on Circuits and Systems
SP - 413
EP - 416
BT - 2013 IEEE International Symposium on Circuits and Systems, ISCAS 2013
T2 - 2013 IEEE International Symposium on Circuits and Systems, ISCAS 2013
Y2 - 19 May 2013 through 23 May 2013
ER -