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

Christy L. Rogers, John G. Harris, Jose C. Principe, Justin C. Sanchez

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

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 front-end spike detection circuit can be added to a neural amplifier and dramatically reduce the required data bandwidth for BMI applications.

Original languageEnglish
Title of host publication2nd International IEEE EMBS Conference on Neural Engineering
Pages213-216
Number of pages4
Volume2005
DOIs
StatePublished - Dec 1 2005
Externally publishedYes
Event2nd International IEEE EMBS Conference on Neural Engineering, 2005 - Arlington, VA, United States
Duration: Mar 16 2005Mar 19 2005

Other

Other2nd International IEEE EMBS Conference on Neural Engineering, 2005
CountryUnited States
CityArlington, VA
Period3/16/053/19/05

ASJC Scopus subject areas

  • Engineering(all)

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    Rogers, C. L., Harris, J. G., Principe, J. C., & Sanchez, J. C. (2005). An analog vlsi implementation of a multi-scale spike detection algorithm for extracellular neural recordings. In 2nd International IEEE EMBS Conference on Neural Engineering (Vol. 2005, pp. 213-216). [1419594] https://doi.org/10.1109/CNE.2005.1419594