BioSignal Analysis

Analysis of biological signals to understand high-level features of people producing them.

Click here for a brief description of the Research Area, taken from the AIRLab website.

Projects

• Affective Computing - Analysis of biological signals to understand human emotions

• Brain-Computer Interface - Analysis of EEG data to control or interact with artificial devices

  • Characterization of the NIA signal
  • Stimulus tagging using aperiodic visual stimulation in a VEP-based BCI

• Analysis of the Olfactory Signal - Analysis of the olfactory signal by an electronic nose

• Automatic Detection Of Sleep Stages

• Classification of EMG signals - Increase the effectiveness of active hand prostheses with EMG signals

Project Proposals

• Affective Computing

• Brain-Computer Interface

  • Multimodal GUI for driving an autonomous wheelchair
  • Exploratory data analysis by genetic feature extraction
  • Aperiodic visual stimulation in a VEP-based BCI
  • Creation of new EEG training by introduction of noise
  • Real-time removal of ocular artifact from EEG
  • Driving an autonomous wheelchair with a P300-based BCI

• Analysis of the Olfactory Signal

People

• EmanueleDeBernardi
• GiuseppinaGini
• MatteoMatteucci
• MaurizioGarbarino
• RossellaBlatt
• SimoneTognetti

Useful Resources

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