BioSignal Analysis

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We develop systems to analyze biological signals to understand high-level features of people producing them.

Projects

Project Proposals

Wiki Page: Aperiodic visual stimulation in a VEP-based BCI
Bci arch.png
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.
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Start: 1 October 2009
Students: 1
CFU: 5
Research Area: BioSignal Analysis
Research Topic: Brain-Computer Interface
Level: Bachelor of Science
Type: Course, Thesis
Wiki Page: Creation of new EEG training by introduction of noise
Bci arch.png
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.
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Start: 1 October 2009
Students: 1 - 2
CFU: 5 - 20
Research Area: BioSignal Analysis
Research Topic: Brain-Computer Interface
Level: Bachelor of Science, Master of Science
Type: Course, Thesis
Wiki Page: Driving an autonomous wheelchair with a P300-based BCI
LURCH wheelchair.jpg
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.
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Start: 1 November 2008
Students: 1
CFU: 5 - 20
Research Area: BioSignal Analysis
Research Topic: Brain-Computer Interface
Level: Bachelor of Science, Master of Science
Type: Course
Wiki Page: Exploratory data analysis by genetic feature extraction
Evolve1at300dpi.gif
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.
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Start: 1 October 2009
Students: 1 - 2
CFU: 5 - 20
Research Area: BioSignal Analysis
Research Topic: Brain-Computer Interface
Level: Master of Science
Type: Course, Thesis
Wiki Page: Multimodal GUI for driving an autonomous wheelchair
LURCH wheelchair.jpg
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.
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Start: 1 October 2009
Students: 1 - 2
CFU: 5 - 10
Research Area: BioSignal Analysis
Research Topic: Brain-Computer Interface
Level: Bachelor of Science, Master of Science
Type: Course
Wiki Page: P300 BCI
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.
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Start: 1 April 2011
Students: 1 - 3
CFU: 2 - 20
Research Area: BioSignal Analysis
Research Topic: EEG analysis, classification algorithms
Level: Master of Science, PhD
Type: Thesis
Wiki Page: Real-time removal of ocular artifact from EEG
B bci.jpg
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.
Tutor: [[MatteoMatteucci | ]] (, , , , , , , , , , , , , , , , , , … further resultswarning.png
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Start: 1 October 2009
Students: 1 - 2
CFU: 2.5 - 5
Research Area: BioSignal Analysis
Research Topic: Brain-Computer Interface
Level: Bachelor of Science, Master of Science
Type: Course


People


Past Projects

Useful Resources

  • AirBAT is a repository containing software developed in projects related to this area. See instructions here.
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