Difference between revisions of "Affective VideoGames"

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{{Project
 
{{Project
| title=Affective VideoGames
+
|title=Affective VideoGames
| tutor=SimoneTognetti;AndreaBonarini;MatteoMatteucci
+
|coordinator=AndreaBonarini;MatteoMatteucci
| students=AndreaTommasoBonanno
+
|tutor=SimoneTognetti; MaurizioGarbarino
| resarea=BioSignal Analysis
+
|students=GiorgioPrini;LucaDelGiudice;
| restopic=Affective Computing
+
|resarea=Affective Computing
| start=2008/11/14
+
|restopic=Affective Computing And BioSignals
| end=2009/06/09
+
|start=2008/11/14
| level=Ms
+
|end=2011/07/23
| type=Thesis
+
|status=Closed
| status=Active
+
|level=Ms
| image=
+
 
}}
 
}}
 
 
=== Project  description ===
 
=== Project  description ===
In this project we try to develop a software that can adapt a behaviour of an interactive videogame (a car game like TORCS or a similar parametrizable game), to do this we will use some measure based on excitement of the player, analizing biological signal to valuate the emotional state.
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The aim of this projects is to develop a software that can adapt a behaviour of an interactive videogame (a car game like TORCS or a similar parametrizable game) according to an evaluation of his/her emotional state. We will start by analizing biological signals to evaluate the emotional state.
The goal is to maximize the fun and reducing the boring of the player, adapting the difficulty of the videogame.
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The goal is to maximize the engagement of the player, making her/him staying as long as possible in the "flow" state , by adapting the parameters of the videogame to her/his real emotional state.
  
The first part of the project will consist of the analysis of a set of VideoGames. In particular two/three different available open source games will be studied in order to receive feedbacks from the player(in terms of excitement), finding out which one is the most suitable for the goal of the project: the one potentially affecting most the player's emotions.  
+
The first part of the project consisted of the analysis of a set of VideoGames. In particular three different available open source games have been studied in order to receive feedbacks from the player (in terms of excitement), finding out which one is the most suitable for the goal of the project: the one potentially affecting most the player's emotions.  
The games that will be analyzed for this first stage of the project will be the following:
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The games that have been analyzed for this first stage of the project have been the following:
  
 
- a puzzle/action 3d game called Beaver Valley;
 
- a puzzle/action 3d game called Beaver Valley;
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- the music video game called Frets on Fire.
 
- the music video game called Frets on Fire.
  
These games will be studied through their source code and configurations in order to identify how and where to change the key parameters of the game in response to player's emotions.
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TORCS has been selected and experiments with it have been done in October 2009, leading to the definition of a methodology to face experiments and some preliminary results.  
In order to perform this study the ProComp sensing system will be used in order to analize biological signals and then to evaluate the emotional state of the player.
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 +
Here is an example of this experiment. The player is sitting in front of a desktop computer equipped with a keyboard. During the game the biological signal of the subject are acquired by sensors on the fingers and the [[Biofeedback_and_neurofeedback_systems|ProComp Infiniti]] system.
 +
 
 +
{{#ev:youtube|XD8C19BUVUg}}
 +
 
 +
*[http://www.youtube.com/watch?v=XD8C19BUVUg External link]
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 +
Following this methodology, in March 2010 a new set of experiments have been performed with 80 volunteers. In these experiments, images from two cameras have also been recorded to allow the [[Gestures in Videogames|analysis of gestures and facial expressions]]. [[user:GiorgioPrini|Giorgio Prini]] is working on these data and on biophysical data to establish relationships between the two.
 +
 
 +
From April 2010 [[user:BarbaraBruno|Barbara Bruno]] and [[user:AntonellaBelfatto|Antonella Belfatto]] have collected new data and [[Videogame adaptation|adapting the videogame behavior]] to the detected user preferences.
 +
 
 +
From May 2010 [[user:GianmarcoZaccaria|Giovanni Marco Zaccaria]] worked on the [[Videogame adaptation|adapting the videogame behavior]] project. His specific role is to write a part of the opponents’s AI algorithms in C language so that they can receive a feedback from data-acquired biosignals processed. The result is to balance in real-time the game difficulty in order to make sure the human player’s enjoyment.
 +
 
 +
More details on the project are available under the discussion tab, accessible by involved airwiki users.
 +
 
 +
===== Students that worked on the project in the past =====
 +
 
 +
*[[User:AndreaCampana | Andrea Campana]] (Project work - Sep 2009)
  
More details on the project are available under the discussion tab.
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*[[User:AndreaTommasoBonanno|Andrea Tommaso Bonanno]] (MS Thesis - Dec 2009)
  
===== Students that worked on the project =====
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* [[user:BarbaraBruno|Barbara Bruno]] and [[user:AntonellaBelfatto|Antonella Belfatto]] (BS Thesis - September 2010)
  
Andrea Campana [[User:AndreaCampana]] (project work)
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* [[user:GianmarcoZaccaria|Giovanni Marco Zaccaria] (BS Thesis - September 2010)
  
=== Laboratory work and risk analysis ===
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====Laboratory work and risk analysis ====
  
Laboratory work for this project will be mainly performed at AIRLab/Lambrate.  
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Laboratory work for this project will be mainly performed at AIRLab/DEI. The only risks are related to the use of computers and data acquisition devices
It will include significant amounts of mechanical work as well as of electrical and electronic activity.
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Potentially risky activities are the following:
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* Use of high-voltage circuits. Special gloves and a current limiter will be used.
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Latest revision as of 16:55, 3 October 2011

Affective VideoGames
Coordinator: AndreaBonarini (andrea.bonarini@polimi.it), MatteoMatteucci (matteo.matteucci@polimi.it)
Tutor: SimoneTognetti (tognetti@elet.polimi.it), MaurizioGarbarino (garbarino@elet.polimi.it)
Collaborator:
Students: GiorgioPrini (giorgio.prini@mail.polimi.it), LucaDelGiudice (delgiudiceluca@gmail.com)
Research Area: Affective Computing
Research Topic: Affective Computing And BioSignals
Start: 2008/11/14
End: 2011/07/23
Status: Closed
Level: Ms

Project description

The aim of this projects is to develop a software that can adapt a behaviour of an interactive videogame (a car game like TORCS or a similar parametrizable game) according to an evaluation of his/her emotional state. We will start by analizing biological signals to evaluate the emotional state. The goal is to maximize the engagement of the player, making her/him staying as long as possible in the "flow" state , by adapting the parameters of the videogame to her/his real emotional state.

The first part of the project consisted of the analysis of a set of VideoGames. In particular three different available open source games have been studied in order to receive feedbacks from the player (in terms of excitement), finding out which one is the most suitable for the goal of the project: the one potentially affecting most the player's emotions. The games that have been analyzed for this first stage of the project have been the following:

- a puzzle/action 3d game called Beaver Valley;

- TORCS (driving simulator);

- the music video game called Frets on Fire.

TORCS has been selected and experiments with it have been done in October 2009, leading to the definition of a methodology to face experiments and some preliminary results.

Here is an example of this experiment. The player is sitting in front of a desktop computer equipped with a keyboard. During the game the biological signal of the subject are acquired by sensors on the fingers and the ProComp Infiniti system.

Following this methodology, in March 2010 a new set of experiments have been performed with 80 volunteers. In these experiments, images from two cameras have also been recorded to allow the analysis of gestures and facial expressions. Giorgio Prini is working on these data and on biophysical data to establish relationships between the two.

From April 2010 Barbara Bruno and Antonella Belfatto have collected new data and adapting the videogame behavior to the detected user preferences.

From May 2010 Giovanni Marco Zaccaria worked on the adapting the videogame behavior project. His specific role is to write a part of the opponents’s AI algorithms in C language so that they can receive a feedback from data-acquired biosignals processed. The result is to balance in real-time the game difficulty in order to make sure the human player’s enjoyment.

More details on the project are available under the discussion tab, accessible by involved airwiki users.

Students that worked on the project in the past
  • [[user:GianmarcoZaccaria|Giovanni Marco Zaccaria] (BS Thesis - September 2010)

Laboratory work and risk analysis

Laboratory work for this project will be mainly performed at AIRLab/DEI. The only risks are related to the use of computers and data acquisition devices