An integrated recording system using an asynchronous pulse representation

Sheng Feng Yen, Jie Xu, Manu Rastogi, John G. Harris, Jose C. Principe, Justin C. Sanchez

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

Abstract

A neuronal recording system for brain-machine interfaces (BMI) based on asynchronous biphasic pulse coding is described. It demonstrates the first step in the development of a complete implanted wireless solution with fully integrated circuit architecture. A recording experiment comparing in parallel a commercial recording system (Tucker-Davis Technology (TDT)) and the UF's custom solution (FWIRE) is set up to compare performance. The novel aspect of the UF system is that the analog signal is represented by an asynchronous pulse train, which provides a low-power, low-bandwidth, noise-resistant means for coding and transmission. Taking advantage of neural firing features, the pulse-based approach uses only 3K pulses/second to record a 25 kHz bandwidth signal from a hardware neural simulator.

Original languageEnglish (US)
Title of host publication2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09
Pages399-402
Number of pages4
DOIs
StatePublished - Oct 27 2009
Event2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09 - Antalya, Turkey
Duration: Apr 29 2009May 2 2009

Publication series

Name2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09

Other

Other2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09
CountryTurkey
CityAntalya
Period4/29/095/2/09

ASJC Scopus subject areas

  • Biomedical Engineering
  • Clinical Neurology
  • Neuroscience(all)

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