By Topic

An analog VLSI implementation of a multi-scale spike detection algorithm for extracellular neural recordings

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
C. L. Rogers ; Sanchez, Florida Univ., Gainesville, FL ; J. G. Harris ; J. C. Principe ; J. C. Sanchez

This paper discusses a multi-scale neural spike detection algorithm for a low-power analog circuit implementation. The key idea is to implement wavelet decomposition and improve spike detection by independently controlling thresholds for each scale. Each thresholded scale is then combined to provide a single output indicating a spike occurrence. This spike detection algorithm shows promising results towards a robust, compact, and unsupervised low power analog spike detection circuit. A low power frontend spike detection circuit can be added to a neural amplifier and dramatically reduce the required data bandwidth for BMI applications

Published in:

Conference Proceedings. 2nd International IEEE EMBS Conference on Neural Engineering, 2005.

Date of Conference:

16-19 March 2005