First Level Theses

Here you can find proposals for first level thesis (7.5 CFU for each student)

BioSignal Analysis

Brain-Computer Interface

Title:	Real-time removal of ocular artifact from EEG
Description:	In a BCI based on electroencephalogram (EEG), one of the most important sources of noise is related to ocular movements. Algorithms have been devised to cancel the effect of such artifacts. The project consists in the in the implementation in real time of an existing algorithm (or one newly developed) in order to improve the performance of a BCI. 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]
Tutor:	Matteo Matteucci (email), Bernardo Dal Seno (email)
Start:	Anytime
Number of students:	1
CFU:	10-20

Title:	Development of an existing genetic algorithm for ERP-based BCIs
Description:	Different event-related potentials (ERPs) are used in BCIs, e.g., P300 and error potentials. 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]
Tutor:	Matteo Matteucci (email), Bernardo Dal Seno (email)
Start:	Anytime
Number of students:	1
CFU:	5-20

Title:	Driving an autonomous wheelchair with a P300-based BCI
Description:	This project pulls together different Airlab projects with the aim to drive an autonomous wheelchair (LURCH) with a BCI, through the development of key software modules. The work will be validated with live experiments. Tools and instruments C++, C, BCI2000, Matlab Linux EEG system Lurch wheelchair Bibliography R. Blatt et al. Brain Control of a Smart Wheelchair [4]
Tutor:	Matteo Matteucci, Bernardo Dal Seno
Start:	November 2008
Number of students:	1
CFU:	5-20

Title:	Online automatic tuning of the number of repetitions in a P300-based BCI
Description:	In a P300-based BCI, (visual) stimuli are presented to the user, and the intention of the user is recognized when a P300 potential is recognized in response of the desired stimulus. In order to improve accuracy, many stimulation rounds are usually performed before making a decision. The exact number of repetitions depends on the user and the goodness of the classifier, but it is usually fixed a-priori. The aim of this project is to adapt the number of repetitions to changing conditions, so as to achieve the maximum accuracy with the minimum time. 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]
Tutor:	Matteo Matteucci, Bernardo Dal Seno
Start:	Anytime
Number of students:	1
CFU:	5-20

Title:	Reproduction of an algorithm for the recognition of error potentials
Description:	Error potentials (ErrPs) are event-related potentials present in the EEG (electroencephalogram) when a subject makes a mistake or when the machine a subject is interacting with works in an expected way. They could be used in the BCI field to improve the performance of a BCI by automatically detecting classification errors. 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]
Tutor:	Matteo Matteucci, Bernardo Dal Seno
Start:	Anytime
Number of students:	1
CFU:	5-15

Machine Learning

Title:	Learning API for TORCS
Description:	TORCS is a state-of-the-art open source racing simulator that represents an ideal bechmark for machine learning techniques. We already organized two successfull competitions based on TORCS where competitors have been asked to develop a controller using their preferred machine learning techniques. The goal of this project is to extend the existing C++ API (available here) to simplify the development of controller using a learning framework. 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.
Tutor:	Daniele Loiacono (loiacono-AT-elet-DOT-polimi-DOT-it)
Start:	Anytime
Number of students:	1 to 2
CFU:	5 to 12.5

Title:	EyeBot
Description:	TORCS is a state-of-the-art open source racing simulator that represents an ideal bechmark for machine learning techniques. We already organized two successfull competitions based on TORCS where competitors have been asked to develop a controller using their preferred machine learning techniques. So far, the controller developed for TORCS used as input only information extracted directly from the state of the game. The goal of this project is to extend the existing controller API (see here) to use the visual information (e.g. the screenshots of the game) as input to the controllers. A successfull project will include both the development of the API and some basic imaga preprocessing to extract information from the images.
Tutor:	Daniele Loiacono (loiacono-AT-elet-DOT-polimi-DOT-it), Alessandro Giusti (giusti-AT-elet-DOT-polimi-DOT-it), and Pierluigi Taddei (taddei-AT-elet-DOT-polimi-DOT-it)
Start:	Anytime
Number of students:	1 to 2
CFU:	5 to 12.5

Title:	SmarTrack
Description:	The generation of customized game content for each player is an attractive direction to improve the game experience in the next-generation computer games. In this scenario, Machine Learning could play an important role to provide automatically such customized game content. 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.
Tutor:	Daniele Loiacono (loiacono-AT-elet-DOT-polimi-DOT-it)
Start:	Anytime
Number of students:	1 to 2
CFU:	5 to 12.5

Title:	TORCS competition
Description:	TORCS is a state-of-the-art open source racing simulator that represents an ideal bechmark for machine learning techniques. We already organized two successfull competitions based on TORCS where competitors have been asked to develop a controller using their preferred machine learning techniques. The goal of this project is to apply any machine learning technique to develop a successfull controller following the competition rules (available here)
Tutor:	Daniele Loiacono (loiacono-AT-elet-DOT-polimi-DOT-it)
Start:	Anytime
Number of students:	1 to 2
CFU:	5 to 12.5

Robotics

Title:	Simulation of 6-DOF Robot Manipulator
Description:	The goal of this project is to develop a simulator for a 6-DOF robot manipulator, using the ode (open dynamics engine) library for simulating the rigid body dynamics. The project involves three different phases: 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.
Tutor:	Marcello Restelli (restelli-AT-elet-DOT-polimi-DOT-it)
Start:	Anytime
Number of students:	2-3
CFU:	10-15

Title:	Calibration of IMU-camera system
Description:	This work is about the problem to calibrate a system composed by an XSense Inertial Measurement Unit and a Fire-i Camera. The pro ject will be focus on the problem to estimate both unknown rotation between the two devices and the extrinsic/intrinsic parameters of the camera. This algorithm allows to use the system for SLAM or robotics applications, like a wereable device for autonomous navigation or augmented reality. Tools and instruments Matlab/C++ Links Matlab Toolbox for mutual calibration [8] List of pubblications[9]
Tutor:	Matteo Matteucci, Davide Migliore
Start:	Anytime
Number of students:	1
CFU:	5-20

Title:	Robot games
Description:	The goal of this activity is to develop an interactive game with robots using commercial devices such as the WII Mote (see the Robogames page) 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.
Tutor:	Andrea Bonarini (bonarini-AT-elet-DOT-polimi-DOT-it)
Start:	Anytime
Number of students:	1-2
CFU:	7.5-12.5

Affective Computing

Title:	Affective VideoGames
Description:	The goal of this activity is to develop an interactive video game (Car game, Shoot them up, Strategic game ..) able to adapt its behaviour in order to maximize your enjoyment. The game will measure your excitement by analizing your biological signals, which mirror your emotional state. The system will be able to adjust some parameters (i.e difficulty of car game circuits, opponets strength ...) in order to keep you egnagemet constant: "In your flow zone!". 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)
Tutor:	Cristiano Alessandro (alessandro-AT-elet-DOT-polimi-DOT-it), Simone Tognetti (togetti-AT-elet-DOT-polimi-DOT-it)
Start:	Anytime
Number of students:	1 to 3
CFU:	2.5 to 20

Title:	Affective recognition in multimedia contexts
Description:	The goal of this activity is to develop an interactive multimedia application (advertisement, e-learning, reccomenadation system) able to capture your emotional state (interests, excitement, anger, joy) while whatching to images, sounds etc. The application will measure your excitement by analizing your biological signals, which mirror your emotional state. The system could be used to give feedback on the quality of multimedia content (i.e goodness of the advertisement, enjoyment of the movie ...) 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)
Tutor:	Cristiano Alessandro (alessandro-AT-elet-DOT-polimi-DOT-it), Simone Tognetti (togetti-AT-elet-DOT-polimi-DOT-it)
Start:	Anytime
Number of students:	1 to 3
CFU:	2.5 to 20

Title:	Affective robotics
Description:	The goal of this activity is to develop an rehabilitation robotic game able to capture your emotional state (interests, excitement, anger, joy, stress) while intereacting with the robot. The application will measure your excitement by analizing your biological signals, which mirror your emotional state. The system could be used to adapt the therapy (executed by the game) according to the patien's needs. We believe the quality of the theraphy is related to the subject's emotional state. The long term goal is to keep the user into a specific emotional state in order to maximize the theraphy efficacy. 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)
Tutor:	Cristiano Alessandro (alessandro-AT-elet-DOT-polimi-DOT-it), Simone Tognetti (togetti-AT-elet-DOT-polimi-DOT-it)
Start:	Anytime
Number of students:	1 to 3
CFU:	2.5 to 20

Title:	Driving companions
Description:	The goal of this activity is to develop an application that is able to capture your emotional state (stress, attention level .. ) while driving standard cars. The application will measure the driver's stress level by analizing his biological signals, which mirror the phisiological state, and could be used to give feedbacks to the driver in dangerous situations. 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)
Tutor:	Cristiano Alessandro (alessandro-AT-elet-DOT-polimi-DOT-it), Simone Tognetti (togetti-AT-elet-DOT-polimi-DOT-it)
Start:	Anytime
Number of students:	1 to 3
CFU:	2.5 to 20