A genetic algorithm for automatic feature extraction from EEG data
Part 1: project profile
Project name
A genetic algorithm for automatic feature extraction from EEG data
Project short description
The identification of stimula based on EEG-analysis needs a specific software capable to find and select a set of relevant stimula-related features from those EEG. Obviously, this is because everyone's P300 is different from everybody's else. Such an application, based upon an ad-hoc genetic algorithm, has already been developed at Politecnico with excellent results. The goal of this project is producing a c++ version of this software to maximize efficiency and portability.
Dates
- Start date: 2008/10/01
- End date: 2009/04/30
People involved
Project head(s)
Students currently working on the project
Students who worked on the project in the past
Part 2: project description
State of the art
It is currently under development the online component of the identification section of the code and the class to which is delegated the computation of the P300 template.
Preliminary studies and sketches
After a deep analysis of the pre-existing source code, a c++ flavor of an analogous matlab version, we moved towards the current phase of further development and conversion of the application.
Design notes and guidelines
Our attention is focused on portability and efficiency; due to this fact we are currently developing the software in the form of a c++ class.
Experiments (description and results)
After we will have developed the application in its entireness, it's been planned to carry on some experiments related to fitness, genes and parameters tweaking.
Repository
Savane - BioSignal Analysis Toolkit (you must be a registered user to log in the repository of Savane)
Part 3: documents and references
Documents
A Genetic Algorithm for Automatic Feature Extraction in P300 Detection
