AIRWiki - User contributions [en]

A genetic algorithm for automatic feature extraction from EEG data

2009-08-31T10:44:00Z

RiccardoCattaneo: /* Part 3: project status */

== '''Part 1: project profile''' ==

=== Project name ===
A genetic algorithm for automatic feature extraction from EEG data and its application as an online classifier

=== Project short description ===
The identification of sight-related stimuli (typically some sort of flash) based upon EEG-analysis needs a specific software capable to find and extract a set of relevant stimuli-related features from those EEG. In particular we are looking for a stimulus called P300 (a positive deflection found, in an EEG, after more or less 300ms from the stimulation). The application we are further developing aims at finding those features that best describe everyone's partcular P300. Such an application, based upon an ad-hoc genetic algorithm, has already been developed at Politecnico with excellent results. The goals of this project are
*producing a c++ version of this software in order to maximize efficiency and portability
*producing a c++ class that uses the previously detected template to classify any epoch as target or non-target

=== Dates ===

*Start date: 2008/10/01

*End date: 2009/04/30

=== People involved ===

===== Project head(s) =====

*[[User:MatteoMatteucci | Prof. M. Matteucci]]

*[[User:BernardoDalSeno | B. Dal Seno]]

===== Students currently working on the project =====

*[[User:RiccardoCattaneo | Riccardo Cattaneo]]
*[[User:GiuseppeChindemi | Giuseppe Chindemi]]

===== Students who worked on the project in the past =====

*[[User: LuigiDallavalle | Luigi Dallavalle]]
*[[User: FlavioMutti | Flavio Mutti]]

== '''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 =====
[https://savane.elet.polimi.it/ Savane - BioSignal Analysis Toolkit]
(you must be a registered user to log in the repository of Savane)

== '''Part 3: project status''' ==
*14/03/2009 Searching for the weights vector in IClassifier object; searching documentation about IClassifier class
*16/03/2009 Defined the skeleton of the class OnlineClassifier, core of the second part of the project. Defined the prototype of the method TemplateGenerator, with which it's possible to write to filesystem the representation of the template of user's P300.
*17/03/2009 Modified repository; defined where the second module fits in the framework of BCI2000 project; evaluated a possible implementation of the method TemplateGenerator; GenericSignal taken into account as the default way to describe a template/epoch (instead of the ones used in the preexisting code)
*19/03/2009 Written the pseudocode of the function TemplateGenerator. Read the documentation of class GenericSignal of BCI2000. Found the weight vector in IClassifier.
*24/03/2009 Given an implementation of the function TemplateGenerator. First attempts to interface with BCI2000.
*25/03/09-01/04/09 Tried and failed to compile BCI2000 code. Attempts to produce a static library of the same code failed anyway.
*02/04/09-05/04/09 Resolved the matters related to BCI2000.
*03/04/09 Implemented a version of the classify(...) method of OnlineClassifier class.
*08/04/09 Begun changes to fitness function towards its final version
*22/04/09 Implemented the function "kFoldingByLetter()" and the first version of the function "balance()"
*Throughout 05/09-08/09: Implemented the final version of OnLineClassifier, an object aimed at classifing a single epoch or a set of epochs (intended as a selection) given a BCIChromosme/IClassifier pair or a GenericSignal representing the template (respectively: OLIClassifClassifier, OLTemplateClassifier) . Also a new class for calculating the fitness has been developed (BCIFitnessLetter). These classes have been documented for doxygen. Corrections have been apported to large portions of the code to let it code compare the two methods of classifing epochs, better control the way the fitness is evaluated, the prediction is sorted out.

== '''Part 4: documents and references''' ==
===== Documents =====
[http://home.dei.polimi.it/dalseno/papers/2008/ijcnn08.pdf A Genetic Algorithm for Automatic Feature Extraction in P300 Detection]

[http://www.cs.iastate.edu/~honavar/ga_tutorial.pdf A Genetic Algorithm Tutorial]

===== References =====
[http://www.bci2000.org BCI2000 Project Homepage]

A genetic algorithm for automatic feature extraction from EEG data

2009-08-31T10:43:15Z

RiccardoCattaneo: /* Part 3: project status */

== '''Part 1: project profile''' ==

=== Project name ===
A genetic algorithm for automatic feature extraction from EEG data and its application as an online classifier

=== Project short description ===
The identification of sight-related stimuli (typically some sort of flash) based upon EEG-analysis needs a specific software capable to find and extract a set of relevant stimuli-related features from those EEG. In particular we are looking for a stimulus called P300 (a positive deflection found, in an EEG, after more or less 300ms from the stimulation). The application we are further developing aims at finding those features that best describe everyone's partcular P300. Such an application, based upon an ad-hoc genetic algorithm, has already been developed at Politecnico with excellent results. The goals of this project are
*producing a c++ version of this software in order to maximize efficiency and portability
*producing a c++ class that uses the previously detected template to classify any epoch as target or non-target

=== Dates ===

*Start date: 2008/10/01

*End date: 2009/04/30

=== People involved ===

===== Project head(s) =====

*[[User:MatteoMatteucci | Prof. M. Matteucci]]

*[[User:BernardoDalSeno | B. Dal Seno]]

===== Students currently working on the project =====

*[[User:RiccardoCattaneo | Riccardo Cattaneo]]
*[[User:GiuseppeChindemi | Giuseppe Chindemi]]

===== Students who worked on the project in the past =====

*[[User: LuigiDallavalle | Luigi Dallavalle]]
*[[User: FlavioMutti | Flavio Mutti]]

== '''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 =====
[https://savane.elet.polimi.it/ Savane - BioSignal Analysis Toolkit]
(you must be a registered user to log in the repository of Savane)

== '''Part 3: project status''' ==
*14/03/2009 Searching for the weights vector in IClassifier object; searching documentation about IClassifier class
*16/03/2009 Defined the skeleton of the class OnlineClassifier, core of the second part of the project. Defined the prototype of the method TemplateGenerator, with which it's possible to write to filesystem the representation of the template of user's P300.
*17/03/2009 Modified repository; defined where the second module fits in the framework of BCI2000 project; evaluated a possible implementation of the method TemplateGenerator; GenericSignal taken into account as the default way to describe a template/epoch (instead of the ones used in the preexisting code)
*19/03/2009 Written the pseudocode of the function TemplateGenerator. Read the documentation of class GenericSignal of BCI2000. Found the weight vector in IClassifier.
*24/03/2009 Given an implementation of the function TemplateGenerator. First attempts to interface with BCI2000.
*25/03/09-01/04/09 Tried and failed to compile BCI2000 code. Attempts to produce a static library of the same code failed anyway.
*02/04/09-05/04/09 Resolved the matters related to BCI2000.
*03/04/09 Implemented a version of the classify(...) method of OnlineClassifier class.
*08/04/09 Begun changes to fitness function towards its final version
*22/04/09 Implemented the function "kFoldingByLetter()" and the first version of the function "balance()"
*Throughout 05/09-08/09: Implemented the final version of OnLineClassifier, an object aimed at classifing a single epoch or a set of epochs (intended as a selection) given a BCIChromosme/IClassifier pair or a GenericSignal representing the template (respectively: OLIClassifClassifier, OLTemplateClassifier) . Also a new class for calculating the fitness has been developed (BCIFitnessLetter). These classes have been documented for doxygen. Corrections have been apported to large portions of the code to le the code compare the two methods of classifing epochs, better control the way the fitness is evaluated, the prediction is sorted out.

== '''Part 4: documents and references''' ==
===== Documents =====
[http://home.dei.polimi.it/dalseno/papers/2008/ijcnn08.pdf A Genetic Algorithm for Automatic Feature Extraction in P300 Detection]

[http://www.cs.iastate.edu/~honavar/ga_tutorial.pdf A Genetic Algorithm Tutorial]

===== References =====
[http://www.bci2000.org BCI2000 Project Homepage]

A genetic algorithm for automatic feature extraction from EEG data

2009-08-31T10:42:50Z

RiccardoCattaneo: /* Part 3: project status */

== '''Part 1: project profile''' ==

=== Project name ===
A genetic algorithm for automatic feature extraction from EEG data and its application as an online classifier

=== Project short description ===
The identification of sight-related stimuli (typically some sort of flash) based upon EEG-analysis needs a specific software capable to find and extract a set of relevant stimuli-related features from those EEG. In particular we are looking for a stimulus called P300 (a positive deflection found, in an EEG, after more or less 300ms from the stimulation). The application we are further developing aims at finding those features that best describe everyone's partcular P300. Such an application, based upon an ad-hoc genetic algorithm, has already been developed at Politecnico with excellent results. The goals of this project are
*producing a c++ version of this software in order to maximize efficiency and portability
*producing a c++ class that uses the previously detected template to classify any epoch as target or non-target

=== Dates ===

*Start date: 2008/10/01

*End date: 2009/04/30

=== People involved ===

===== Project head(s) =====

*[[User:MatteoMatteucci | Prof. M. Matteucci]]

*[[User:BernardoDalSeno | B. Dal Seno]]

===== Students currently working on the project =====

*[[User:RiccardoCattaneo | Riccardo Cattaneo]]
*[[User:GiuseppeChindemi | Giuseppe Chindemi]]

===== Students who worked on the project in the past =====

*[[User: LuigiDallavalle | Luigi Dallavalle]]
*[[User: FlavioMutti | Flavio Mutti]]

== '''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 =====
[https://savane.elet.polimi.it/ Savane - BioSignal Analysis Toolkit]
(you must be a registered user to log in the repository of Savane)

== '''Part 3: project status''' ==
*14/03/2009 Searching for the weights vector in IClassifier object; searching documentation about IClassifier class
*16/03/2009 Defined the skeleton of the class OnlineClassifier, core of the second part of the project. Defined the prototype of the method TemplateGenerator, with which it's possible to write to filesystem the representation of the template of user's P300.
*17/03/2009 Modified repository; defined where the second module fits in the framework of BCI2000 project; evaluated a possible implementation of the method TemplateGenerator; GenericSignal taken into account as the default way to describe a template/epoch (instead of the ones used in the preexisting code)
*19/03/2009 Written the pseudocode of the function TemplateGenerator. Read the documentation of class GenericSignal of BCI2000. Found the weight vector in IClassifier.
*24/03/2009 Given an implementation of the function TemplateGenerator. First attempts to interface with BCI2000.
*25/03/09-01/04/09 Tried and failed to compile BCI2000 code. Attempts to produce a static library of the same code failed anyway.
*02/04/09-05/04/09 Resolved the matters related to BCI2000.
*03/04/09 Implemented a version of the classify(...) method of OnlineClassifier class.
*08/04/09 Begun changes to fitness function towards its final version
*22/04/09 Implemented the function "kFoldingByLetter()" and the first version of the function "balance()"
*Throughout 05/09-08/09: Implemented the final version of OnLineClassifier, an object aimed at classifing a single epoch or a set of epochs (intended as a selection) give a BCIChromosme/IClassifier pair or a GenericSignal representing the template (respectively: OLIClassifClassifier, OLTemplateClassifier) . Also a new class for calculating the fitness has been developed (BCIFitnessLetter). These classes have been documented for doxygen. Corrections have been apported to large portions of the code to le the code compare the two methods of classifing epochs, better control the way the fitness is evaluated, the prediction is sorted out.

== '''Part 4: documents and references''' ==
===== Documents =====
[http://home.dei.polimi.it/dalseno/papers/2008/ijcnn08.pdf A Genetic Algorithm for Automatic Feature Extraction in P300 Detection]

[http://www.cs.iastate.edu/~honavar/ga_tutorial.pdf A Genetic Algorithm Tutorial]

===== References =====
[http://www.bci2000.org BCI2000 Project Homepage]

Talk:A genetic algorithm for automatic feature extraction from EEG data

2009-06-29T20:11:19Z

RiccardoCattaneo: /* Todo */

==Objectives==
* Training with letter-counting fitness
* Online classifier

==Todo==
* Scrivere funzione per folding che non 'rompe' le lettere. Mantenere la vecchia funzione di folding.
* Fare la funzione di bilanciamento deterministica. Si veda anche <tt>bci/common/matlab/balance_training_bci2_2b.m</tt> su AirBAT. Per ogni ripetizione, tra le stimolazioni non target viene presa la seconda stimolazione colonna e la penultima stimolazione riga (che non sono necessariamente la seconda colonna e la penultima riga).
* Scrivere la funzione di fitness, che viene calcolata 1 volta per ogni cromosoma su tutto l'insieme di addestramento. Mantenere anche la vecchia funzione di folding.
* La selezione delle funzioni di folding e di fitness va fatta tramite un parametro (o puntatore) nella main().
* Commenti per: classi, metodi, attributi. Preferibilmente con doxygen.

* cambiare bias a 1 (fatto)
* sommare l'ultimo elemento del vettore dei pesi dopo avere verificato che sia l'ultimo (controlla come viene creato il vettore delle features) (fatto)
* testare coi due template generati nei due modi diversi (TODO)
* cambiare il nome del metodo predictletter -> testletter (WIP)
* usare la predict_probability invece che la prediction nel codice di BCIChromosome::predict_letter + sommare invece che un uno per ogni colonna/riga, somma il valore di probabilità che esce dalla predict_probability (terzo parametro) (WIP)
* cambiare la getWeightVector - mettere una push_back (fatto)
* push_back e pop_back diventano at (WIP)
* verificare che sull'insieme di test funzioni tutto - indovina tutte le lettere di test (TO DO)
* --- calcolare il numero di ripetizioni necessarie per il 100% (TO DO)
* salvato il w0 su file per essere processato dal classificatore online (fatto)
* scambiato il template con -template (fatto)

==Info==
Il metodo di classificazione finale dovrà avere questo prototipo:
double classify( const GenericSignal &epoch );
<tt>GenericSignal</tt> è la classe dei segnali di BCI2000 che memorizza una matrice bidimensionale; è definita in <tt>src/shared/types/GenericSignal.h</tt>.

Formato per i dati dovrebbe essere "%.17g" (assicurarsi che il numero di cifre significative sia sufficiente a rappresentare tutti i bit della mantissa)

Tesisti precedenti: Luigi Dallavalle, Flavio Mutti

Talk:A genetic algorithm for automatic feature extraction from EEG data

2009-06-29T19:52:22Z

RiccardoCattaneo: /* Todo */

==Objectives==
* Training with letter-counting fitness
* Online classifier

==Todo==
* Scrivere funzione per folding che non 'rompe' le lettere. Mantenere la vecchia funzione di folding.
* Fare la funzione di bilanciamento deterministica. Si veda anche <tt>bci/common/matlab/balance_training_bci2_2b.m</tt> su AirBAT. Per ogni ripetizione, tra le stimolazioni non target viene presa la seconda stimolazione colonna e la penultima stimolazione riga (che non sono necessariamente la seconda colonna e la penultima riga).
* Scrivere la funzione di fitness, che viene calcolata 1 volta per ogni cromosoma su tutto l'insieme di addestramento. Mantenere anche la vecchia funzione di folding.
* La selezione delle funzioni di folding e di fitness va fatta tramite un parametro (o puntatore) nella main().
* Commenti per: classi, metodi, attributi. Preferibilmente con doxygen.

* cambiare bias a 1
* sommare l'ultimo elemento del vettore dei pesi dopo avere verificato che sia l'ultimo (controlla come viene creato il vettore delle features)
* testare coi due template generati nei due modi diversi
* cambiare il nome del metodo predictletter -> testletter
* usare la predict_probability invece che la prediction nel codice di BCIChromosome::predict_letter + sommare invece che un uno per ogni colonna/riga, somma il valore di probabilità che esce dalla predict_probability (terzo parametro)
* cambiare la getWeightVector - mettere una push_back
* push_back e pop_back diventano at
* verificare che sull'insieme di test funzioni tutto - indovina tutte le lettere di test
* --- calcolare il numero di ripetizioni necessarie per il 100%

==Info==
Il metodo di classificazione finale dovrà avere questo prototipo:
double classify( const GenericSignal &epoch );
<tt>GenericSignal</tt> è la classe dei segnali di BCI2000 che memorizza una matrice bidimensionale; è definita in <tt>src/shared/types/GenericSignal.h</tt>.

Formato per i dati dovrebbe essere "%.17g" (assicurarsi che il numero di cifre significative sia sufficiente a rappresentare tutti i bit della mantissa)

Tesisti precedenti: Luigi Dallavalle, Flavio Mutti

Talk:A genetic algorithm for automatic feature extraction from EEG data

2009-06-22T14:41:28Z

RiccardoCattaneo: /* Todo */

==Objectives==
* Training with letter-counting fitness
* Online classifier

==Todo==
* Scrivere funzione per folding che non 'rompe' le lettere. Mantenere la vecchia funzione di folding.
* Fare la funzione di bilanciamento deterministica. Si veda anche <tt>bci/common/matlab/balance_training_bci2_2b.m</tt> su AirBAT. Per ogni ripetizione, tra le stimolazioni non target viene presa la seconda stimolazione colonna e la penultima stimolazione riga (che non sono necessariamente la seconda colonna e la penultima riga).
* Scrivere la funzione di fitness, che viene calcolata 1 volta per ogni cromosoma su tutto l'insieme di addestramento. Mantenere anche la vecchia funzione di folding.
* La selezione delle funzioni di folding e di fitness va fatta tramite un parametro (o puntatore) nella main().
* Commenti per: classi, metodi, attributi. Preferibilmente con doxygen.

* cambiare bias a 1
* sommare l'ultimo elemento del vettore dei pesi dopo avere verificato
che sia l'ultimo (controlla come viene creato il vettore delle features)
* testare coi due template generati nei due modi diversi
* cambiare il nome del metodo predictletter -> testletter
* usare la predict_probability invece che la prediction nel codice di
BCIChromosome::predict_letter + sommare invece che un uno per ogni
colonna/riga, somma il valore di probabilità che esce dalla predict_probability
(terzo parametro)
* cambiare la getWeightVector - mettere una push_back
* push_back e pop_back diventano at
* verificare che sull'insieme di test funzioni tutto - indovina tutte le lettere di test
* --- calcolare il numero di ripetizioni necessarie per il 100%

==Info==
Il metodo di classificazione finale dovrà avere questo prototipo:
double classify( const GenericSignal &epoch );
<tt>GenericSignal</tt> è la classe dei segnali di BCI2000 che memorizza una matrice bidimensionale; è definita in <tt>src/shared/types/GenericSignal.h</tt>.

Formato per i dati dovrebbe essere "%.17g" (assicurarsi che il numero di cifre significative sia sufficiente a rappresentare tutti i bit della mantissa)

Tesisti precedenti: Luigi Dallavalle, Flavio Mutti

A genetic algorithm for automatic feature extraction from EEG data

2009-04-14T20:08:45Z

RiccardoCattaneo: /* Part 4: documents and references */

== '''Part 1: project profile''' ==

=== Project name ===
A genetic algorithm for automatic feature extraction from EEG data and its application as an online classifier

=== Project short description ===
The identification of sight-related stimuli (typically some sort of flash) based upon EEG-analysis needs a specific software capable to find and extract a set of relevant stimuli-related features from those EEG. In particular we are looking for a stimulus called P300 (a positive deflection found, in an EEG, after more or less 300ms from the stimulation). The application we are further developing aims at finding those features that best describe everyone's partcular P300. Such an application, based upon an ad-hoc genetic algorithm, has already been developed at Politecnico with excellent results. The goals of this project are
*producing a c++ version of this software in order to maximize efficiency and portability
*producing a c++ class that uses the previously detected template to classify any epoch as target or non-target

=== Dates ===

*Start date: 2008/10/01

*End date: 2009/04/30

=== People involved ===

===== Project head(s) =====

*[[User:MatteoMatteucci | Prof. M. Matteucci]]

*[[User:BernardoDalSeno | B. Dal Seno]]

===== Students currently working on the project =====

*[[User:RiccardoCattaneo | Riccardo Cattaneo]]
*[[User:GiuseppeChindemi | Giuseppe Chindemi]]

===== Students who worked on the project in the past =====

*[[User: LuigiDallavalle | Luigi Dallavalle]]
*[[User: FlavioMutti | Flavio Mutti]]

== '''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 =====
[https://savane.elet.polimi.it/ Savane - BioSignal Analysis Toolkit]
(you must be a registered user to log in the repository of Savane)

== '''Part 3: project status''' ==
*14/03/2009 Searching for the weights vector in IClassifier object; searching documentation about IClassifier class
*16/03/2009 Defined the skeleton of the class OnlineClassifier, core of the second part of the project. Defined the prototype of the method TemplateGenerator, with which it's possible to write to filesystem the representation of the template of user's P300.
*17/03/2009 Modified repository; defined where the second module fits in the framework of BCI2000 project; evaluated a possible implementation of the method TemplateGenerator; GenericSignal taken into account as the default way to describe a template/epoch (instead of the ones used in the preexisting code)
*19/03/2009 Written the pseudocode of the function TemplateGenerator. Read the documentation of class GenericSignal of BCI2000. Found the weight vector in IClassifier.
*24/03/2009 Given an implementation of the function TemplateGenerator. First attempts to interface with BCI2000.
*25/03/09-01/04/09 Tried and failed to compile BCI2000 code. Attempts to produce a static library of the same code failed anyway.
*02/04/09-05/04/09 Resolved the matters related to BCI2000.
*03/04/09 Implemented a version of the classify(...) method of OnlineClassifier class.
*08/04/09 Begun changes to fitness function towards its final version

== '''Part 4: documents and references''' ==
===== Documents =====
[http://home.dei.polimi.it/dalseno/papers/2008/ijcnn08.pdf A Genetic Algorithm for Automatic Feature Extraction in P300 Detection]

[http://www.cs.iastate.edu/~honavar/ga_tutorial.pdf A Genetic Algorithm Tutorial]

===== References =====
[http://www.bci2000.org BCI2000 Project Homepage]

A genetic algorithm for automatic feature extraction from EEG data

2009-04-14T20:07:28Z

RiccardoCattaneo: /* Part 4: documents and references */

== '''Part 1: project profile''' ==

=== Project name ===
A genetic algorithm for automatic feature extraction from EEG data and its application as an online classifier

=== Project short description ===
The identification of sight-related stimuli (typically some sort of flash) based upon EEG-analysis needs a specific software capable to find and extract a set of relevant stimuli-related features from those EEG. In particular we are looking for a stimulus called P300 (a positive deflection found, in an EEG, after more or less 300ms from the stimulation). The application we are further developing aims at finding those features that best describe everyone's partcular P300. Such an application, based upon an ad-hoc genetic algorithm, has already been developed at Politecnico with excellent results. The goals of this project are
*producing a c++ version of this software in order to maximize efficiency and portability
*producing a c++ class that uses the previously detected template to classify any epoch as target or non-target

=== Dates ===

*Start date: 2008/10/01

*End date: 2009/04/30

=== People involved ===

===== Project head(s) =====

*[[User:MatteoMatteucci | Prof. M. Matteucci]]

*[[User:BernardoDalSeno | B. Dal Seno]]

===== Students currently working on the project =====

*[[User:RiccardoCattaneo | Riccardo Cattaneo]]
*[[User:GiuseppeChindemi | Giuseppe Chindemi]]

===== Students who worked on the project in the past =====

*[[User: LuigiDallavalle | Luigi Dallavalle]]
*[[User: FlavioMutti | Flavio Mutti]]

== '''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 =====
[https://savane.elet.polimi.it/ Savane - BioSignal Analysis Toolkit]
(you must be a registered user to log in the repository of Savane)

== '''Part 3: project status''' ==
*14/03/2009 Searching for the weights vector in IClassifier object; searching documentation about IClassifier class
*16/03/2009 Defined the skeleton of the class OnlineClassifier, core of the second part of the project. Defined the prototype of the method TemplateGenerator, with which it's possible to write to filesystem the representation of the template of user's P300.
*17/03/2009 Modified repository; defined where the second module fits in the framework of BCI2000 project; evaluated a possible implementation of the method TemplateGenerator; GenericSignal taken into account as the default way to describe a template/epoch (instead of the ones used in the preexisting code)
*19/03/2009 Written the pseudocode of the function TemplateGenerator. Read the documentation of class GenericSignal of BCI2000. Found the weight vector in IClassifier.
*24/03/2009 Given an implementation of the function TemplateGenerator. First attempts to interface with BCI2000.
*25/03/09-01/04/09 Tried and failed to compile BCI2000 code. Attempts to produce a static library of the same code failed anyway.
*02/04/09-05/04/09 Resolved the matters related to BCI2000.
*03/04/09 Implemented a version of the classify(...) method of OnlineClassifier class.

== '''Part 4: documents and references''' ==
===== Documents =====
[http://home.dei.polimi.it/dalseno/papers/2008/ijcnn08.pdf A Genetic Algorithm for Automatic Feature Extraction in P300 Detection]

[http://www.cs.iastate.edu/~honavar/ga_tutorial.pdf A Genetic Algorithm Tutorial]

===== References =====
[http://www.bci2000.org BCI2000 Project Hompegae]

A genetic algorithm for automatic feature extraction from EEG data

2009-04-06T09:20:32Z

RiccardoCattaneo: /* Part 3: project status */

== '''Part 1: project profile''' ==

=== Project name ===
A genetic algorithm for automatic feature extraction from EEG data and its application as an online classifier

=== Project short description ===
The identification of sight-related stimuli (typically some sort of flash) based upon EEG-analysis needs a specific software capable to find and extract a set of relevant stimuli-related features from those EEG. In particular we are looking for a stimulus called P300 (a positive deflection found, in an EEG, after more or less 300ms from the stimulation). The application we are further developing aims at finding those features that best describe everyone's partcular P300. Such an application, based upon an ad-hoc genetic algorithm, has already been developed at Politecnico with excellent results. The goals of this project are
*producing a c++ version of this software in order to maximize efficiency and portability
*producing a c++ class that uses the previously detected template to classify any epoch as target or non-target

=== Dates ===

*Start date: 2008/10/01

*End date: 2009/04/30

=== People involved ===

===== Project head(s) =====

*[[User:MatteoMatteucci | Prof. M. Matteucci]]

*[[User:BernardoDalSeno | B. Dal Seno]]

===== Students currently working on the project =====

*[[User:RiccardoCattaneo | Riccardo Cattaneo]]
*[[User:GiuseppeChindemi | Giuseppe Chindemi]]

===== Students who worked on the project in the past =====

*[[User: LuigiDallavalle | Luigi Dallavalle]]
*[[User: FlavioMutti | Flavio Mutti]]

== '''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 =====
[https://savane.elet.polimi.it/ Savane - BioSignal Analysis Toolkit]
(you must be a registered user to log in the repository of Savane)

== '''Part 3: project status''' ==
*14/03/2009 Searching for the weights vector in IClassifier object; searching documentation about IClassifier class
*16/03/2009 Defined the skeleton of the class OnlineClassifier, core of the second part of the project. Defined the prototype of the method TemplateGenerator, with which it's possible to write to filesystem the representation of the template of user's P300.
*17/03/2009 Modified repository; defined where the second module fits in the framework of BCI2000 project; evaluated a possible implementation of the method TemplateGenerator; GenericSignal taken into account as the default way to describe a template/epoch (instead of the ones used in the preexisting code)
*19/03/2009 Written the pseudocode of the function TemplateGenerator. Read the documentation of class GenericSignal of BCI2000. Found the weight vector in IClassifier.
*24/03/2009 Given an implementation of the function TemplateGenerator. First attempts to interface with BCI2000.
*25/03/09-01/04/09 Tried and failed to compile BCI2000 code. Attempts to produce a static library of the same code failed anyway.
*02/04/09-05/04/09 Resolved the matters related to BCI2000.
*03/04/09 Implemented a version of the classify(...) method of OnlineClassifier class.

== '''Part 4: documents and references''' ==
===== Documents =====
[http://home.dei.polimi.it/dalseno/papers/2008/ijcnn08.pdf A Genetic Algorithm for Automatic Feature Extraction in P300 Detection]

[http://www.cs.iastate.edu/~honavar/ga_tutorial.pdf A Genetic Algorithm Tutorial]

A genetic algorithm for automatic feature extraction from EEG data

2009-03-25T11:55:51Z

RiccardoCattaneo: /* Part 3: project status */

== '''Part 1: project profile''' ==

=== Project name ===
A genetic algorithm for automatic feature extraction from EEG data and its application as an online classifier

=== Project short description ===
The identification of sight-related stimuli (typically some sort of flash) based upon EEG-analysis needs a specific software capable to find and extract a set of relevant stimuli-related features from those EEG. In particular we are looking for a stimulus called P300 (a positive deflection found, in an EEG, after more or less 300ms from the stimulation). The application we are further developing aims at finding those features that best describe everyone's partcular P300. Such an application, based upon an ad-hoc genetic algorithm, has already been developed at Politecnico with excellent results. The goals of this project are
*producing a c++ version of this software in order to maximize efficiency and portability
*producing a c++ class that uses the previously detected template to classify any epoch as target or non-target

=== Dates ===

*Start date: 2008/10/01

*End date: 2009/04/30

=== People involved ===

===== Project head(s) =====

*[[User:MatteoMatteucci | Prof. M. Matteucci]]

*[[User:BernardoDalSeno | B. Dal Seno]]

===== Students currently working on the project =====

*[[User:RiccardoCattaneo | Riccardo Cattaneo]]
*[[User:GiuseppeChindemi | Giuseppe Chindemi]]

===== Students who worked on the project in the past =====

*[[User: LuigiDallavalle | Luigi Dallavalle]]
*[[User: FlavioMutti | Flavio Mutti]]

== '''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 =====
[https://savane.elet.polimi.it/ Savane - BioSignal Analysis Toolkit]
(you must be a registered user to log in the repository of Savane)

== '''Part 3: project status''' ==
*14/03/2009 Searching for the weights vector in IClassifier object; searching documentation about IClassifier class
*16/03/2009 Defined the skeleton of the class OnlineClassifier, core of the second part of the project. Defined the prototype of the method TemplateGenerator, with which it's possible to write to filesystem the representation of the template of user's P300.
*17/03/2009 Modified repository; defined where the second module fits in the framework of BCI2000 project; evaluated a possible implementation of the method TemplateGenerator; GenericSignal taken into account as the default way to describe a template/epoch (instead of the ones used in the preexisting code)
*19/03/2009 Written the pseudocode of the function TemplateGenerator. Read the documentation of class GenericSignal of BCI2000. Found the weight vector in IClassifier.
*24/03/2009 Given an implementation of the function TemplateGenerator. First attempts to interface with BCI2000.

== '''Part 4: documents and references''' ==
===== Documents =====
[http://home.dei.polimi.it/dalseno/papers/2008/ijcnn08.pdf A Genetic Algorithm for Automatic Feature Extraction in P300 Detection]

[http://www.cs.iastate.edu/~honavar/ga_tutorial.pdf A Genetic Algorithm Tutorial]

A genetic algorithm for automatic feature extraction from EEG data

2009-03-18T00:52:44Z

RiccardoCattaneo:

== '''Part 1: project profile''' ==

=== Project name ===
A genetic algorithm for automatic feature extraction from EEG data and its application as an online classifier

=== Project short description ===
The identification of sight-related stimuli (typically some sort of flash) based upon EEG-analysis needs a specific software capable to find and extract a set of relevant stimuli-related features from those EEG. In particular we are looking for a stimulus called P300 (a positive deflection found, in an EEG, after more or less 300ms from the stimulation). The application we are further developing aims at finding those features that best describe everyone's partcular P300. Such an application, based upon an ad-hoc genetic algorithm, has already been developed at Politecnico with excellent results. The goals of this project are
*producing a c++ version of this software in order to maximize efficiency and portability
*producing a c++ class that uses the previously detected template to classify any epoch as target or non-target

=== Dates ===

*Start date: 2008/10/01

*End date: 2009/04/30

=== People involved ===

===== Project head(s) =====

*[[User:MatteoMatteucci | Prof. M. Matteucci]]

*[[User:BernardoDalSeno | B. Dal Seno]]

===== Students currently working on the project =====

*[[User:RiccardoCattaneo | Riccardo Cattaneo]]
*[[User:GiuseppeChindemi | Giuseppe Chindemi]]

===== Students who worked on the project in the past =====

*[[User: LuigiDallavalle | Luigi Dallavalle]]
*[[User: FlavioMutti | Flavio Mutti]]

== '''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 =====
[https://savane.elet.polimi.it/ Savane - BioSignal Analysis Toolkit]
(you must be a registered user to log in the repository of Savane)

== '''Part 3: project status''' ==
*14/03/2009 Searching for the weights vector in IClassifier object; searching documentation about IClassifier class
*16/03/2009 Defined the skeleton of the class OnlineClassifier, core of the second part of the project. Defined the prototype of the method TemplateGenerator, with which it's possible to write to filesystem the representation of the template of user's P300.
*17/03/2009 Modified repository; defined where the second module fits in the framework of BCI2000 project; evaluated a possible implementation of the method TemplateGenerator; GenericSignal taken into account as the default way to describe a template/epoch (instead of the ones used in the preexisting code)

== '''Part 4: documents and references''' ==
===== Documents =====
[http://home.dei.polimi.it/dalseno/papers/2008/ijcnn08.pdf A Genetic Algorithm for Automatic Feature Extraction in P300 Detection]

[http://www.cs.iastate.edu/~honavar/ga_tutorial.pdf A Genetic Algorithm Tutorial]

A genetic algorithm for automatic feature extraction from EEG data

2009-03-18T00:47:52Z

RiccardoCattaneo: /* Part 3: project status */

== '''Part 1: project profile''' ==

=== Project name ===
A genetic algorithm for automatic feature extraction from EEG data

=== Project short description ===
The identification of sight-related stimuli (typically some sort of flash) based upon EEG-analysis needs a specific software capable to find and extract a set of relevant stimuli-related features from those EEG. In particular we are looking for a stimulus called P300 (a positive deflection found, in the EEG, after more or less 300ms from the stimulation). The application we are further developing aims at finding those features that best describe everyone's partcular P300. 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 in order to maximize efficiency and portability.

=== Dates ===

*Start date: 2008/10/01

*End date: 2009/04/30

=== People involved ===

===== Project head(s) =====

*[[User:MatteoMatteucci | Prof. M. Matteucci]]

*[[User:BernardoDalSeno | B. Dal Seno]]

===== Students currently working on the project =====

*[[User:RiccardoCattaneo | Riccardo Cattaneo]]
*[[User:GiuseppeChindemi | Giuseppe Chindemi]]

===== Students who worked on the project in the past =====

*[[User: LuigiDallavalle | Luigi Dallavalle]]
*[[User: FlavioMutti | Flavio Mutti]]

== '''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 =====
[https://savane.elet.polimi.it/ Savane - BioSignal Analysis Toolkit]
(you must be a registered user to log in the repository of Savane)

== '''Part 3: project status''' ==
*14/03/2009 Searching for the weights vector in IClassifier object; searching documentation about IClassifier class
*16/03/2009 Defined the skeleton of the class OnlineClassifier, core of the second part of the project. Defined the prototype of the method TemplateGenerator, with which it's possible to write to filesystem the representation of the template of user's P300.
*17/03/2009 Modified repository; defined where the second module fits in the framework of BCI2000 project; evaluated a possible implementation of the method TemplateGenerator; GenericSignal taken into account as the default way to describe a template/epoch (instead of the ones used in the preexisting code)

== '''Part 4: documents and references''' ==
===== Documents =====
[http://home.dei.polimi.it/dalseno/papers/2008/ijcnn08.pdf A Genetic Algorithm for Automatic Feature Extraction in P300 Detection]

[http://www.cs.iastate.edu/~honavar/ga_tutorial.pdf A Genetic Algorithm Tutorial]

A genetic algorithm for automatic feature extraction from EEG data

2009-03-18T00:46:49Z

RiccardoCattaneo: /* Part 3: project status */

== '''Part 1: project profile''' ==

=== Project name ===
A genetic algorithm for automatic feature extraction from EEG data

=== Project short description ===
The identification of sight-related stimuli (typically some sort of flash) based upon EEG-analysis needs a specific software capable to find and extract a set of relevant stimuli-related features from those EEG. In particular we are looking for a stimulus called P300 (a positive deflection found, in the EEG, after more or less 300ms from the stimulation). The application we are further developing aims at finding those features that best describe everyone's partcular P300. 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 in order to maximize efficiency and portability.

=== Dates ===

*Start date: 2008/10/01

*End date: 2009/04/30

=== People involved ===

===== Project head(s) =====

*[[User:MatteoMatteucci | Prof. M. Matteucci]]

*[[User:BernardoDalSeno | B. Dal Seno]]

===== Students currently working on the project =====

*[[User:RiccardoCattaneo | Riccardo Cattaneo]]
*[[User:GiuseppeChindemi | Giuseppe Chindemi]]

===== Students who worked on the project in the past =====

*[[User: LuigiDallavalle | Luigi Dallavalle]]
*[[User: FlavioMutti | Flavio Mutti]]

== '''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 =====
[https://savane.elet.polimi.it/ Savane - BioSignal Analysis Toolkit]
(you must be a registered user to log in the repository of Savane)

== '''Part 3: project status''' ==
*14/03/2009 Searching for the weights vector in IClassifier object; searching documentation about IClassifier class
*16/03/2009 Defined the skeleton of the class OnlineClassifier, core of the second part of the project. Defined the prototype of the method TemplateGenerator, with which it's possible to write to filesystem the representation of the template of user's P300.
*17/03/2009 Modified repository; defined where the module fits in the framework of BCI2000 project; evaluated a possible implementation of the method TemplateGenerator; GenericSignal taken into account as the default way to describe a template/epoch (instead of the ones used in the preexisting code)

== '''Part 4: documents and references''' ==
===== Documents =====
[http://home.dei.polimi.it/dalseno/papers/2008/ijcnn08.pdf A Genetic Algorithm for Automatic Feature Extraction in P300 Detection]

[http://www.cs.iastate.edu/~honavar/ga_tutorial.pdf A Genetic Algorithm Tutorial]

A genetic algorithm for automatic feature extraction from EEG data

2009-03-16T14:43:09Z

RiccardoCattaneo: /* Part 3: project status */

== '''Part 1: project profile''' ==

=== Project name ===
A genetic algorithm for automatic feature extraction from EEG data

=== Project short description ===
The identification of sight-related stimuli (typically some sort of flash) based upon EEG-analysis needs a specific software capable to find and extract a set of relevant stimuli-related features from those EEG. In particular we are looking for a stimulus called P300 (a positive deflection found, in the EEG, after more or less 300ms from the stimulation). The application we are further developing aims at finding those features that best describe everyone's partcular P300. 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 in order to maximize efficiency and portability.

=== Dates ===

*Start date: 2008/10/01

*End date: 2009/04/30

=== People involved ===

===== Project head(s) =====

*[[User:MatteoMatteucci | Prof. M. Matteucci]]

*[[User:BernardoDalSeno | B. Dal Seno]]

===== Students currently working on the project =====

*[[User:RiccardoCattaneo | Riccardo Cattaneo]]
*[[User:GiuseppeChindemi | Giuseppe Chindemi]]

===== Students who worked on the project in the past =====

*[[User: LuigiDallavalle | Luigi Dallavalle]]
*[[User: FlavioMutti | Flavio Mutti]]

== '''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 =====
[https://savane.elet.polimi.it/ Savane - BioSignal Analysis Toolkit]
(you must be a registered user to log in the repository of Savane)

== '''Part 3: project status''' ==
*14/03/2009 Searching for the weights vector in IClassifier object; searching documentation about IClassifier class
*16/03/2009 Defined the skeleton of the class OnlineClassifier, core of the second part of the project. Defined the prototype of the method TemplateGenerator, with which it's possible to write to filesystem the representation of the template of user's P300.

== '''Part 4: documents and references''' ==
===== Documents =====
[http://home.dei.polimi.it/dalseno/papers/2008/ijcnn08.pdf A Genetic Algorithm for Automatic Feature Extraction in P300 Detection]

[http://www.cs.iastate.edu/~honavar/ga_tutorial.pdf A Genetic Algorithm Tutorial]

A genetic algorithm for automatic feature extraction from EEG data

2009-03-14T19:56:57Z

RiccardoCattaneo:

== '''Part 1: project profile''' ==

=== Project name ===
A genetic algorithm for automatic feature extraction from EEG data

=== Project short description ===
The identification of sight-related stimuli (typically some sort of flash) based upon EEG-analysis needs a specific software capable to find and extract a set of relevant stimuli-related features from those EEG. In particular we are looking for a stimulus called P300 (a positive deflection found, in the EEG, after more or less 300ms from the stimulation). The application we are further developing aims at finding those features that best describe everyone's partcular P300. 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 in order to maximize efficiency and portability.

=== Dates ===

*Start date: 2008/10/01

*End date: 2009/04/30

=== People involved ===

===== Project head(s) =====

*[[User:MatteoMatteucci | Prof. M. Matteucci]]

*[[User:BernardoDalSeno | B. Dal Seno]]

===== Students currently working on the project =====

*[[User:RiccardoCattaneo | Riccardo Cattaneo]]
*[[User:GiuseppeChindemi | Giuseppe Chindemi]]

===== Students who worked on the project in the past =====

*[[User: LuigiDallavalle | Luigi Dallavalle]]
*[[User: FlavioMutti | Flavio Mutti]]

== '''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 =====
[https://savane.elet.polimi.it/ Savane - BioSignal Analysis Toolkit]
(you must be a registered user to log in the repository of Savane)

== '''Part 3: project status''' ==
*14/03/2009 Searching for the weights vector in IClassifier object; searching documentation about IClassifier class

== '''Part 4: documents and references''' ==
===== Documents =====
[http://home.dei.polimi.it/dalseno/papers/2008/ijcnn08.pdf A Genetic Algorithm for Automatic Feature Extraction in P300 Detection]

[http://www.cs.iastate.edu/~honavar/ga_tutorial.pdf A Genetic Algorithm Tutorial]

A genetic algorithm for automatic feature extraction from EEG data

2009-03-12T01:52:28Z

RiccardoCattaneo: /* Part 1: project profile */

== '''Part 1: project profile''' ==

=== Project name ===
A genetic algorithm for automatic feature extraction from EEG data

=== Project short description ===
The identification of sight-related stimuli (typically some sort of flash) based upon EEG-analysis needs a specific software capable to find and extract a set of relevant stimuli-related features from those EEG. In particular we are looking for a stimulus called P300 (a positive deflection found, in the EEG, after more or less 300ms from the stimulation). The application we are further developing aims at finding those features that best describe everyone's partcular P300. 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 in order to maximize efficiency and portability.

=== Dates ===

*Start date: 2008/10/01

*End date: 2009/04/30

=== People involved ===

===== Project head(s) =====

*[[User:MatteoMatteucci | Prof. M. Matteucci]]

*[[User:BernardoDalSeno | B. Dal Seno]]

===== Students currently working on the project =====

*[[User:RiccardoCattaneo | Riccardo Cattaneo]]
*[[User:GiuseppeChindemi | Giuseppe Chindemi]]

===== Students who worked on the project in the past =====

*[[User: LuigiDallavalle | Luigi Dallavalle]]
*[[User: FlavioMutti | Flavio Mutti]]

== '''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 =====
[https://savane.elet.polimi.it/ Savane - BioSignal Analysis Toolkit]
(you must be a registered user to log in the repository of Savane)
== '''Part 3: documents and references''' ==
===== Documents =====
[http://home.dei.polimi.it/dalseno/papers/2008/ijcnn08.pdf A Genetic Algorithm for Automatic Feature Extraction in P300 Detection]

[http://www.cs.iastate.edu/~honavar/ga_tutorial.pdf A Genetic Algorithm Tutorial]

A genetic algorithm for automatic feature extraction from EEG data

2009-03-12T01:39:09Z

RiccardoCattaneo: /* Project short description */

== '''Part 1: project profile''' ==

=== Project name ===
A genetic algorithm for automatic feature extraction from EEG data

=== Project short description ===
The identification of sight-related stimuli (typically some sort of flash) based upon EEG-analysis needs a specific software capable to find and extract a set of relevant stimuli-related features from those EEG. In particular we are looking for a stimulus called P300 (a positive deflection found, in the EEG, after more or less 300ms from the stimulation). The application we are further developing aims at finding those features that best describe everyone's partcular P300. 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 in order to maximize efficiency and portability.

=== Dates ===

*Start date: 2008/10/01

*End date: 2009/04/30

=== People involved ===

===== Project head(s) =====

*[[User:MatteoMatteucci | Prof. M. Matteucci]]

*[[User:BernardoDalSeno | B. Dal Seno]]

===== Students currently working on the project =====

*[[User:RiccardoCattaneo | Riccardo Cattaneo]]
*[[User:GiuseppeChindemi | Giuseppe Chindemi]]

== '''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 =====
[https://savane.elet.polimi.it/ Savane - BioSignal Analysis Toolkit]
(you must be a registered user to log in the repository of Savane)
== '''Part 3: documents and references''' ==
===== Documents =====
[http://home.dei.polimi.it/dalseno/papers/2008/ijcnn08.pdf A Genetic Algorithm for Automatic Feature Extraction in P300 Detection]

[http://www.cs.iastate.edu/~honavar/ga_tutorial.pdf A Genetic Algorithm Tutorial]

A genetic algorithm for automatic feature extraction from EEG data

2009-03-12T00:50:02Z

RiccardoCattaneo: /* Documents */

== '''Part 1: project profile''' ==

=== Project name ===
A genetic algorithm for automatic feature extraction from EEG data

=== Project short description ===
The identification of stimuli 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) =====

*[[User:MatteoMatteucci | Prof. M. Matteucci]]

*[[User:BernardoDalSeno | B. Dal Seno]]

===== Students currently working on the project =====

*[[User:RiccardoCattaneo | Riccardo Cattaneo]]
*[[User:GiuseppeChindemi | Giuseppe Chindemi]]

== '''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 =====
[https://savane.elet.polimi.it/ Savane - BioSignal Analysis Toolkit]
(you must be a registered user to log in the repository of Savane)
== '''Part 3: documents and references''' ==
===== Documents =====
[http://home.dei.polimi.it/dalseno/papers/2008/ijcnn08.pdf A Genetic Algorithm for Automatic Feature Extraction in P300 Detection]

[http://www.cs.iastate.edu/~honavar/ga_tutorial.pdf A Genetic Algorithm Tutorial]

A genetic algorithm for automatic feature extraction from EEG data

2009-03-12T00:49:45Z

RiccardoCattaneo: /* Documents */

== '''Part 1: project profile''' ==

=== Project name ===
A genetic algorithm for automatic feature extraction from EEG data

=== Project short description ===
The identification of stimuli 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) =====

*[[User:MatteoMatteucci | Prof. M. Matteucci]]

*[[User:BernardoDalSeno | B. Dal Seno]]

===== Students currently working on the project =====

*[[User:RiccardoCattaneo | Riccardo Cattaneo]]
*[[User:GiuseppeChindemi | Giuseppe Chindemi]]

== '''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 =====
[https://savane.elet.polimi.it/ Savane - BioSignal Analysis Toolkit]
(you must be a registered user to log in the repository of Savane)
== '''Part 3: documents and references''' ==
===== Documents =====
[http://home.dei.polimi.it/dalseno/papers/2008/ijcnn08.pdf | A Genetic Algorithm for Automatic Feature Extraction in P300 Detection]

[http://www.cs.iastate.edu/~honavar/ga_tutorial.pdf | A Genetic Algorithm Tutorial]

A genetic algorithm for automatic feature extraction from EEG data

2009-03-12T00:39:46Z

RiccardoCattaneo: /* Project short description */

== '''Part 1: project profile''' ==

=== Project name ===
A genetic algorithm for automatic feature extraction from EEG data

=== Project short description ===
The identification of stimuli 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) =====

*[[User:MatteoMatteucci | Prof. M. Matteucci]]

*[[User:BernardoDalSeno | B. Dal Seno]]

===== Students currently working on the project =====

*[[User:RiccardoCattaneo | Riccardo Cattaneo]]
*[[User:GiuseppeChindemi | Giuseppe Chindemi]]

== '''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 =====
[https://savane.elet.polimi.it/ Savane - BioSignal Analysis Toolkit]
(you must be a registered user to log in the repository of Savane)
== '''Part 3: documents and references''' ==
===== Documents =====
[[Media:Ga.pdf | A Genetic Algorithm for Automatic Feature Extraction in P300 Detection]]

[[Media:Ga_tutorial.pdf | A Genetic Algorithm Tutorial]]

User:RiccardoCattaneo

2009-03-12T00:34:53Z

RiccardoCattaneo: New page: {{Student | firstname=Riccardo | lastname=Cattaneo | email=riccardo1(dot)cattaneo(at)mail(dot)polimi(dot)it | advisor=MatteoMatteucci; BernardoDalSeno | projectpage=A genetic algorith...

{{Student
| firstname=Riccardo
| lastname=Cattaneo
| email=riccardo1(dot)cattaneo(at)mail(dot)polimi(dot)it
| advisor=MatteoMatteucci; BernardoDalSeno
| projectpage=A genetic algorithm for automatic feature extraction from EEG data
| photo=Rc.jpg
}}

'''Riccardo Cattaneo'''

nato a Lodi il 29-09-1987

'''Istruzione e formazione'''

Frequenta il corso di Ingegneria Informatica al Politecnico di Milano.

File:Rc.jpg

2009-03-12T00:26:17Z

RiccardoCattaneo: RiccardCattaneo

RiccardCattaneo

A genetic algorithm for automatic feature extraction from EEG data

2009-03-11T23:59:47Z

RiccardoCattaneo:

== '''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) =====

*[[User:MatteoMatteucci | Prof. M. Matteucci]]

*[[User:BernardoDalSeno | Prof. B. Dal Seno]]

===== Students currently working on the project =====

*[[User:RiccardoCattaneo | Riccardo Cattaneo]]
*[[User:GiuseppeChindemi | Giuseppe Chindemi]]

== '''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 =====
[https://savane.elet.polimi.it/ Savane - BioSignal Analysis Toolkit]
(you must be a registered user to log in the repository of Savane)
== '''Part 3: documents and references''' ==
===== Documents =====
[[Media:Ga.pdf | A Genetic Algorithm for Automatic Feature Extraction in P300 Detection]]

[[Media:Ga_tutorial.pdf | A Genetic Algorithm Tutorial]]

A genetic algorithm for automatic feature extraction from EEG data

2009-03-11T23:58:13Z

RiccardoCattaneo: New page: == '''Part 1: project profile''' == === Project name === A genetic algorithm for automatic feature extraction from EEG data === Project short description === The identification of stimul...

== '''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) =====

*[[User:MatteoMatteucci | Prof. M. Matteucci]]

*[[User:BernardoDalSeno | Prof. B. Dal Seno]]

===== Students currently working on the project =====

*[[User:RiccardoCattaneo | Riccardo Cattaneo]]
*[[User:GiuseppeChindemi | Giuseppe Chindemi]]

===== Students who worked on the project in the past =====

*[[User:VittoriaIttima | Vittoria Ittima]]

== '''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 =====
[https://savane.elet.polimi.it/ Savane - BioSignal Analysis Toolkit]
(you must be a registered user to log in the repository of Savane)
== '''Part 3: documents and references''' ==
===== Documents =====
[[Media:Ga.pdf | A Genetic Algorithm for Automatic Feature Extraction in P300 Detection]]

[[Media:Ga_tutorial.pdf | A Genetic Algorithm Tutorial]]

User:GiuseppeChindemi

2009-03-09T11:17:54Z

RiccardoCattaneo:

{{Student
| firstname=Giuseppe
| lastname=Chindemi
| email=giuseppe.chindemi(at)mail(dot)polimi(dot)it
| advisor=MatteoMatteucci;BernardoDalSeno
| projectpage=A genetic algorithm for automatic feature extraction from EEG data
| photo=Giuseppec.jpg
}}

'''Giuseppe Chindemi'''

nato a Reggio Calabria il 23-03-1988

'''Istruzione e formazione'''

'''Attualmente''' studente di Ing. Informatica al Politecnico di Milano