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EEG Recognition System for Windows

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Editors’ Review

Download.com staff
This Matlab source code facilitates EEG recognition for Brain-Computer Interface applications. It processes electrophysiological signals to determine user intent for various mental activities.

  • Pros

    • Provides Matlab source code for EEG recognition.
    • Supports analysis of electrophysiological signals like P300 and rhythms.
    • Applicable to Brain-Computer Interface research and development.
    • Successfully tested on the UCI EEG Database.
    • Handles data from 64 electrodes sampled at 256 Hz.

  • Cons

    • Requires Matlab environment for execution.
    • Focuses specifically on EEG signal recognition.
    • No information on specific algorithms used.
    • Limited detail on practical implementation guidance.
Icon of program: EEG Recognition System

EEG Recognition System for Windows

Download now

Used EEG Recognition System for Windows?

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Full Specifications

GENERAL
Release
Latest update
Version
1.0
OPERATING SYSTEMS
Platform
Windows
Operating System
  • Windows NT
  • Windows 2000
  • Windows 2003
  • Windows 7
  • Windows Server
  • Windows ME
  • Windows Vista
  • Windows 10
  • Windows 8
  • Windows XP
  • Windows 98
Additional Requirements
Matlab
POPULARITY
Total Downloads
336
Downloads Last Week
0
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Developer’s Description

By Luigi Rosa
Get a Matlab source code for EEG recognition system.
Functional brain imaging techniques that are designed to measure an aspect of brain function can be employed to obtain tangible information related to brain activity. Electroencephalogram (EEG) is one such technique, which measures the electric fields that are produced by the activity in the brain. From EEG measurements, it is possible to extract information and determine the intent of the user for a number of different mental activities (such as motor imagery, motor planning), using a variety of electrophysiological signals such as slow cortical potentials, P300 potentials, and mu or beta rhythms recorded from the scalp, and cortical neuronal activity recorded by implanted electrodes. The use of EEG for the communication of intent is one of the bases of Brain-Computer Interface (BCI) research, which is geared towards the development of systems to afford people with disabilities or severe neuromuscular disorders the capability of basic communication (by operating word processing programs or through neuroprostheses). EEG signals acquired during mental activities can also be used for subject identification to create a more secure environment for applications such as BCIs, game play, or silent communication.Code has been successfully tested on UCI EEG Database. This database contains measurements from 64 electrodes placed on the scalp sampled at 256 Hz (3.9-msec epoch) for 1 second.
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