Affective VideoGames
Affective VideoGames
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| Coordinator: | |
| Tutor: | SimoneTognetti (tognetti@elet.polimi.it), AndreaBonarini (andrea.bonarini@polimi.it), MatteoMatteucci (matteo.matteucci@polimi.it) |
| Collaborator: | |
| Students: | AndreaTommasoBonanno (andreat.bonanno@gmail.com) |
| Research Area: | BioSignal Analysis |
| Research Topic: | Affective Computing |
| Start: | 2008/11/14 |
| End: | 2009/12/23 |
| Status: | Active |
| Level: | Ms |
| Type: | Thesis |
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. The goal is to maximize the fun and reducing the boring of the player, adapting the difficulty of the videogame.
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 games that will be analyzed for this first stage of the project will be the following:
- a puzzle/action 3d game called Beaver Valley;
- TORCS (driving simulator);
- 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. 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.
More details on the project are available under the discussion tab.
Students that worked on the project
Andrea Campana User:AndreaCampana (project work)
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
