Difference between revisions of "First Level Theses"

Tools and instruments

Matlab, BCI2000, C++

EEG system

Bibliography

J.R. Wolpaw et al. Brain-computer interfaces for communication and control [1]

R.J. Croff, R.J. Barry. Removal of ocular artifact from the EEG: a review [2]

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

Good programming skill required

EEG system

Bibliography

B. Dal Seno, M. Matteucci, L. Mainardi. A Genetic Algorithm for Automatic Feature Extraction in P300 Detection [3]

Tools and instruments

C++, C, BCI2000, Matlab

Linux

EEG system

Lurch wheelchair

Bibliography

R. Blatt et al. Brain Control of a Smart Wheelchair [4]

The work will be validated with live experiments.

Tools and instruments

C++, BCI2000, Matlab

EEG system

Bibliography

E. Donchin, K.M. Spencer, R. Wijesinghe. The Mental Prosthesis: Assessing the Speed of a P300-Based Brain-Computer Interface [5]

The project aims at reproducing algorithms for ErrP detection from the literature.

Tools and instruments

Matlab, BCI2000

EEG system

Bibliography

P.W. Ferrez, J. Millán. You Are Wrong! Automatic Detection of Interaction Errors from Brain Waves [6]

G. Schalk et al. EEG-based communication: presence of an error potential [7]

Such an extension can be partially developed by porting an existing Java API for TORCS that already provides a lot of functionalities for machine learning approaches.

The goal of this project is to apply machine learning techniques for the generation of customized tracks in TORCS, a state-of-the-art open source racing simulator. The project include different activities: the automatic generation of tracks, the section of relevant features to characterize a track and the analysis of an interest measure.

The goal of this project is to apply any machine learning technique to develop a successfull controller following the competition rules (available here)

• Building the physical model of the manipulator
• Implementing the forward and inverse kinematic routines
• Implementing the trajectory planning routines
• Implementing the control modules
• Implementing an interface to control the robot movements

This project allows to put into practice what has been explained during the first part of the course of Robotics.

The project can be turned into a thesis, by using the simulated manipulator to perform some learning experiments.

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.

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)