Please use this identifier to cite or link to this item: https://doi.org/10.1109/TCSII.2013.2258270
Title: A new system architecture for future long-term high-density neural recording
Authors: Xu, J. 
Wu, T.
Yang, Z. 
Keywords: Dynamic range (DR)
frequency shaping
input impedance
neural recording
Issue Date: 2013
Source: Xu, J., Wu, T., Yang, Z. (2013). A new system architecture for future long-term high-density neural recording. IEEE Transactions on Circuits and Systems II: Express Briefs 60 (7) : 403-406. ScholarBank@NUS Repository. https://doi.org/10.1109/TCSII.2013.2258270
Abstract: This brief presents a new system architecture for neural recording to allow higher recording density and more tolerance to interface degeneration and artifacts. Compared with its conventional counterpart, the proposed architecture has a frequency-dependent gain stage that inherently rejects dc offset and attenuates low-frequency interferences. In the digital domain, frequency compensation is used to restore the signals 'seen' by an electrode. Powered by a switched-capacitor design, the proposed architecture can lead to major improvements on system performance metrics, including input impedance, distortion, and dynamic range. In simulations with different electrode sizes and degeneration levels, the proposed architecture consistently gives high-fidelity recording data. We argue that the proposed architecture is more suitable for long-term high-density invasive brain-computer interface experiments as a replacement to better support a mimicked 'Moore's Law' on recording density. © 2004-2012 IEEE.
Source Title: IEEE Transactions on Circuits and Systems II: Express Briefs
URI: http://scholarbank.nus.edu.sg/handle/10635/54547
ISSN: 15497747
DOI: 10.1109/TCSII.2013.2258270
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

5
checked on Dec 11, 2017

WEB OF SCIENCETM
Citations

4
checked on Dec 11, 2017

Page view(s)

27
checked on Dec 9, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.