Research topic: Improving EEG information extraction for diagnostics and continuous brain monitoring. Improving brain machine interface using a single EEG electrode. Analyzing and modeling the computation properties of bio-sonar animals.
Research methods: Development of machine learning time/frequency methods for EEG localization and signal decomposition for the purpose of information extraction, detection and classification. Relying on concurrent fMRI/EEG for improving spatial and temporal brain scanning resolution. Development of novel signal processing and machine learning methods for creation of super-resolution and super-accuracy in bio-sonar, inspired by bat and dolphin sonar research.
Main projects in the lab include:
- Single EEG feature extraction for Epilepsy, Attention and other brain pathologies.
- Development of neuro-feedback techniques.
- Analysis of EEG networks of activity from EEG/fMRI concurrent recording.
- Modeling of super resolution and accuracy from real and simulated bat recorded data.