Difference between revisions of "Master Level Theses"

Tools and instruments

Matlab, BCI2000, C++

Bibliography

E. Donchin, K.M. Spencer, R. Wijesinghe. The Mental Prosthesis: Assessing the Speed of a P300-Based Brain-Computer Interface [1]

Tools and instruments

Matlab, BCI2000

Knowledge of C++ may be useful

Bibliography

J.R. Wolpaw et al. Brain-computer interfaces for communication and control [2]

Tools and instruments

Matlab, BCI2000, C++

Bibliography

J.R. Wolpaw et al. Brain-computer interfaces for communication and control [3]

R.J. Croff, R.J. Barry. Removal of ocular artifact from the EEG: a review [4]

Tools and instruments

Matlab, BCI2000, C++

Bibliography

J.R. Wolpaw et al. Brain-computer interfaces for communication and control [5]

A genetic algorithm (GA) for ERP feature extraction has been developed at the Airlab. The GA has been proved to work, but there different ways that can explored to further develop this algorithm and expand its application field.

Tools and instruments

C++, Matlab, BCI2000

Bibliography

B. Dal Seno, M. Matteucci, L. Mainardi. A Genetic Algorithm for Automatic Feature Extraction in P300 Detection [6]

Up to this moment research in this kind of environments, which can be formalized as Partially Observable Stochastic Games, has been more from a game theoretic point of view, thus focusing on the pursue of optimality and equilibrium, with no attention to payoff maximization, which may be more interesting in many real-world contexts.

On the other hand Reinforcement Learning techniques demonstrated to be successful in solving both fully observable problems, single and multi-agent, and single-agent partially observable ones, while lacking application to the partially observable multi-agent framework.

This research aims at studying the solution of Partially Observable Stochastic Games, analyzing the possibility to combine the Opponent Modeling concept with the well proven Reinforcement Learning solution techniques to solve problems in this framework, adopting Poker as testbed.

Project phases:

• Design and implementation of the game (it is possible to start form avaliable open source game)
• Design of experimental protocol used to stimulate particolar emotions.
• Data acquisition by usign biological sensors during the playing experience.
• Off-line classification of data with avaliable tools.
• Desing and develop of on-line classifier sistem for emotion recognition
• Closed loop control: the game reacts to the user emotional state changing its behaviour.

These projects allow to experiment with biological-data acquisition tools and videogames design.

The project consists on the realization of one or more phases depending on the difficulty/cfu to be achieved and to the competences of the candidate(s)

Project phases:

• Design and implementation of the multimedia application.
• Design of experimental protocol used to stimulate particolar emotions.
• Data acquisition by usign biological sensors during the multimedia experience.
• Off-line classification of data with avaliable tools.
• Desing and develop of on-line classifier sistem for emotion recognition
• Closed loop control: the multimedia application will provide contents according to your enjoyment .

These projects allow to experiment with biological-data acquisition tools and multimedia application design.

The project consists on the realization of one or more phases depending on the difficulty/cfu to be achieved and to the competences of the candidate(s)

Project phases:

• Design and implementation of the robotic game on the avaliable robot.
• Design of experimental protocol used to stimulate particolar emotions.
• Data acquisition by usign biological sensors during the interaction with the robot.
• Off-line classification of data with avaliable tools.
• Desing and develop of on-line classifier sistem for emotion recognition
• Closed loop control: the thrapy will be adapted to the patient's needs.

These projects allow to experiment with biological-data acquisition tools, robots and videogame design.

The project consists on the realization of one or more phases depending on the difficulty/cfu to be achieved and to the competences of the candidate(s)

Project phases:

• Design of experimental protocol used to stimulate particolar emotions.
• Data acquisition by usign biological sensors while driving in different conditions (city, highway, country ..)
• Off-line classification of data with avaliable tools.
• Desing and develop of on-line classifier sistem for emotion recognition
• Closed loop control: the car will give audio/visual feedbacks to the user letting him know its phisiological state

These projects allow to experiment with biological-data acquisition tools, robots and videogame design.

The project consists on the realization of one or more phases depending on the difficulty/cfu to be achieved and to the competences of the candidate(s)

Projects are available in different areas:

• Design and implementation of the game on one of the available robots and extension of the robot functionalities
• Design and implementation of the game and a new suitable robot
• Evaluation of the game with users (in collaboration with Franca Garzotto)

These projects allow to experiment with real mobile robots and real interaction devices.

Parts of these projects can be considered as course projects. These projects can also be extended to cover course projects.