Real-time spike detection in EEG signals using the wavelet transform and a dedicated digital signal processor card

This paper describes a complete real-time system for EEG signal analysis. Specific software and hardware have been designed to provide biologists with an efficient tool, which allows a complete study of the different states of vigilance as well as the paroxysmal activities. The analysis method which...

Full description

Saved in:
Bibliographic Details
Published inJournal of neuroscience methods Vol. 70; no. 1; pp. 5 - 14
Main Authors Clarençon, Didier, Renaudin, Marc, Gourmelon, Patrick, Kerckhoeve, Arnaud, Catérini, Richard, Boivin, Emmanuel, Ellis, Patrick, Hille, Benjamin, Fatôme, Marc
Format Journal Article
LanguageEnglish
Published Netherlands Elsevier B.V 01.12.1996
Elsevier
Subjects
Algorithms
Animals
Computer Systems
Digital signal processor
Electroencephalogram
Electroencephalography - methods
Engineering Sciences
GABA Antagonists - toxicity
Micro and nanotechnologies
Microcomputers
Microelectronics
Models, Theoretical
Picrotoxin - toxicity
Rats
Rats, Sprague-Dawley
Seizures - chemically induced
Seizures - physiopathology
Signal Processing, Computer-Assisted - instrumentation
Software
Spike and wave
Wavelet analysis
Spike and wave
Wavelet analysis
Electroencephalogram
Digital signal processor
real-time-spike-detection
paroxysmal-activities
dedicated-digital-signal-processor-card
Online AccessGet full text

Cover

More Information
Summary:This paper describes a complete real-time system for EEG signal analysis. Specific software and hardware have been designed to provide biologists with an efficient tool, which allows a complete study of the different states of vigilance as well as the paroxysmal activities. The analysis method which is based on the wavelet transform is first presented and compared to the standard spectral approach. The dedicated digital signal processor card, based on the Motorola 96002 processor chip, that has been designed to support real-time acquisition and real-time processing of EEG signals is then presented. We finally illustrate the proposed method by processing real EEG signals of rats, and show that it opens up new prospects in the domain of EEG-based diagnosis. We propose a new representation, called globalization, that provides a global view and better detection of paroxysmal activities.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0165-0270
1872-678X
DOI:10.1016/S0165-0270(96)00073-8