Evaluation of classification algorithms for Brain Computer Interfaces
Summary
New machine learning algorithms that can be used to classify the brain signals are been evaluated and new applications developed.
Supervisor(s)
Dr Rafael A. Calvo, Dr Craig Jin
Research Location
Electrical and Information Engineering
Program Type
Synopsis
Electroencephalography is the neurophysiologic measurement of the electrical activity of the brain by recording from electrodes placed on the scalp. Electroencephalograms (EEGs) can be used to recognize specific patterns in brain activity. We can currently use the brain signals produced by a user of our BCI system to move a cursor on a screen, for example to play Pong.
Want to find out more?
Contact Research Expert to find out more about participating in this opportunity.
Browse for other opportunities within the Electrical and Information Engineering .
Keywords
Biomedical Instrumentation, Signal Processing, Data Mining, Classification
Opportunity ID
The opportunity ID for this research opportunity is: 281
Other opportunities with Dr Rafael A. Calvo
- Semantic awareness in collaborative writing
- Automatic mapping of concepts and relationships
- Social network visualization in collaborative work and learning
- Multimodal emotion recognition
- Multimodal approaches for detecting attention in Human-Computer Interaction
Other opportunities with Dr Craig Jin
- Pattern analysis techniques for sound synthesis
- Interpolation of binaural impulse responses for virtual auditory displays
- Sound field recording and recreation
- Beamforming with acoustic vector sensors - Multiple acoustic source localisation using acoustic vector sensor arrays
- Speech separation and localisation using particle filtering
- Mapping 2D Images to 3D Shape
- New technique for studying human brain activity
- Next Generation Audio Coding
- Spherical multi-modal scene analysis
- Statistical models of ear shape and ear acoustics
- Binaural signal processing algorithms for hearing aids
- Electrical Impedance Tomography for stroke, biophysical monitoring and medical device design
- Impedance tomography for cardiac imaging: high speed tomography
- Medical diagnostics for neonates in the developing world
- FPGA-based Low Latency Trading
- Floating Point FPGA Architectures
- Placement-aware Hardware Description Languages
- Scalable vision machines
- Modelling Parkinson's disease using control models
- Novel Electrodes for rapid electrophysiological recording