Difference between revisions of "BioSignal Analysis"

Title: Aperiodic visual stimulation in a VEP-based BCI
Description: Visual-evoked potentials (VEPs) are a possible way to drive the a Brain-Computer Interface (BCI). This projects aims at maximizing the discrimination between different stimuli by using numerical codes derived from techniques of digital telecommunications.

• J.R. Wolpaw et al. Brain-computer interfaces for communication and control (http://tinyurl.com/yhq27pq)
• Erich E. Sutter. The brain response interface: communication through visually-induced electrical brain responses (http://tinyurl.com/yfqvwp6)
  

Tutor: MatteoMatteucci
Additional Info: CFU 5 / Bachelor of Science / Course, Thesis

Title: Creation of new EEG training by introduction of noise
Description: A Brain-Computer Interface (BCI) must be trained on the individual user in order to be effective. This training phase require recording data in long sessions, which is time consuming and boring for the user. The aim of this project is to develop algorithm to create new training EEG (electroencephalography) data from existing ones, so as to speed up the training phase.

• J.R. Wolpaw et al. Brain-computer interfaces for communication and control (http://tinyurl.com/yhq27pq)
  

Tutor: MatteoMatteucci
Additional Info: CFU 5 - 20 / Bachelor of Science, Master of Science / Course, Thesis

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. Depending on the effort the student is willing to put into it, the project can grow to a full experimental thesis.
Tutor: MatteoMatteucci
Additional Info: CFU 5 - 20 / Bachelor of Science, Master of Science / Course

Title: Exploratory data analysis by genetic feature extraction
Description: Understanding the waves in EEG signals is an hard task and psicologists often need automatic tools to perform this task. In this project we are interested in using a genetic algorithm developed for P300 feature extraction in order to extract useful informations from Error Potentials. The project is a collaboration with the psicology department od Padua University.

• B. Dal Seno, M. Matteucci, and L. Mainardi. "A genetic algorithm for automatic feature extraction in P300 detection" (http://home.dei.polimi.it/dalseno/papers/2008/ijcnn08.pdf)
• B. Dal Seno, M. Matteucci, L. Mainardi, F. Piccione, and S. Silvoni. "Single-trial P300 detection in healthy and ALS subjects by means of a genetic algorithm" (http://home.dei.polimi.it/dalseno/papers/2008/grazGa08.pdf)
  

Tutor: MatteoMatteucci
Additional Info: CFU 5 - 20 / Master of Science / Course, Thesis

Title: Multimodal GUI for driving an autonomous wheelchair
Description: This project pulls together different Airlab projects with the aim to drive an autonomous wheelchair (LURCH - The autonomous wheelchair) with a multi modal interface (Speech Recognition, Brain-Computer Interface, etc.), through the development of key software modules. The work will be validated with live experiments.

• R. Blatt et al. Brain Control of a Smart Wheelchair (http://tinyurl.com/ygldwun)
  

Tutor: MatteoMatteucci, SimoneCeriani, DavideMigliore
Additional Info: CFU 5 - 10 / Bachelor of Science, Master of Science / Course

Title: P300 BCI for ALS patient
Description: Recovery, integration and adaptation of P300 BCI (hardware and software) stubs to generate a working interface for a speller. The aim is to develop a working prototype for an ALS affected patient.
Tutor: MatteoMatteucci
Additional Info: CFU 2 - 20 / Master of Science, PhD / Thesis

Title: Real-time removal of ocular artifact from EEG
Description: In a Brain-Computer Interface (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.

• J.R. Wolpaw et al. Brain-computer interfaces for communication and control (http://tinyurl.com/yhq27pq)
• R.J. Croff, R.J. Barry. Removal of ocular artifact from the EEG: a review (http://tinyurl.com/ykk6ks9)
  

Tutor: MatteoMatteucci
Additional Info: CFU 2.5 - 5 / Bachelor of Science, Master of Science / Course

Title: Aperiodic visual stimulation in a VEP-based BCI
Description: Visual-evoked potentials (VEPs) are a possible way to drive the a Brain-Computer Interface (BCI). This projects aims at maximizing the discrimination between different stimuli by using numerical codes derived from techniques of digital telecommunications.

• J.R. Wolpaw et al. Brain-computer interfaces for communication and control (http://tinyurl.com/yhq27pq)
• Erich E. Sutter. The brain response interface: communication through visually-induced electrical brain responses (http://tinyurl.com/yfqvwp6)
  

Tutor: MatteoMatteucci
Additional Info: CFU 5 / Bachelor of Science / Course, Thesis

Title: Creation of new EEG training by introduction of noise
Description: A Brain-Computer Interface (BCI) must be trained on the individual user in order to be effective. This training phase require recording data in long sessions, which is time consuming and boring for the user. The aim of this project is to develop algorithm to create new training EEG (electroencephalography) data from existing ones, so as to speed up the training phase.

• J.R. Wolpaw et al. Brain-computer interfaces for communication and control (http://tinyurl.com/yhq27pq)
  

Tutor: MatteoMatteucci
Additional Info: CFU 5 - 20 / Bachelor of Science, Master of Science / Course, Thesis

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. Depending on the effort the student is willing to put into it, the project can grow to a full experimental thesis.
Tutor: MatteoMatteucci
Additional Info: CFU 5 - 20 / Bachelor of Science, Master of Science / Course

Title: Exploratory data analysis by genetic feature extraction
Description: Understanding the waves in EEG signals is an hard task and psicologists often need automatic tools to perform this task. In this project we are interested in using a genetic algorithm developed for P300 feature extraction in order to extract useful informations from Error Potentials. The project is a collaboration with the psicology department od Padua University.

• B. Dal Seno, M. Matteucci, and L. Mainardi. "A genetic algorithm for automatic feature extraction in P300 detection" (http://home.dei.polimi.it/dalseno/papers/2008/ijcnn08.pdf)
• B. Dal Seno, M. Matteucci, L. Mainardi, F. Piccione, and S. Silvoni. "Single-trial P300 detection in healthy and ALS subjects by means of a genetic algorithm" (http://home.dei.polimi.it/dalseno/papers/2008/grazGa08.pdf)
  

Tutor: MatteoMatteucci
Additional Info: CFU 5 - 20 / Master of Science / Course, Thesis

Title: Multimodal GUI for driving an autonomous wheelchair
Description: This project pulls together different Airlab projects with the aim to drive an autonomous wheelchair (LURCH - The autonomous wheelchair) with a multi modal interface (Speech Recognition, Brain-Computer Interface, etc.), through the development of key software modules. The work will be validated with live experiments.

• R. Blatt et al. Brain Control of a Smart Wheelchair (http://tinyurl.com/ygldwun)
  

Tutor: MatteoMatteucci, SimoneCeriani, DavideMigliore
Additional Info: CFU 5 - 10 / Bachelor of Science, Master of Science / Course

Title: P300 BCI for ALS patient
Description: Recovery, integration and adaptation of P300 BCI (hardware and software) stubs to generate a working interface for a speller. The aim is to develop a working prototype for an ALS affected patient.
Tutor: MatteoMatteucci
Additional Info: CFU 2 - 20 / Master of Science, PhD / Thesis

Title: Real-time removal of ocular artifact from EEG
Description: In a Brain-Computer Interface (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.

• J.R. Wolpaw et al. Brain-computer interfaces for communication and control (http://tinyurl.com/yhq27pq)
• R.J. Croff, R.J. Barry. Removal of ocular artifact from the EEG: a review (http://tinyurl.com/ykk6ks9)
  

Tutor: MatteoMatteucci
Additional Info: CFU 2.5 - 5 / Bachelor of Science, Master of Science / Course