A steady-state visually evoked potential based brain-computer interface system for control of electric wheelchairs.

Description

M. Tech. Electrical Engineering / Determines whether Hidden Markov models (HMM) can be used to classify steady state visual evoked electroencephalogram signals in a BCI system. This is for the purpose of aiding disabled people in driving a wheelchair.

Links & Downloads

1. http://encore.tut.ac.za/iii/cpro/DigitalItemViewPage.external?sp=1001343

Tags

Dissertations, Academic -- South Africa.

Hidden Markov models.

Markov processes.

Electroencephalography.

Computer vision.

Brain-computer interfaces.

Electric wheelchairs.

Control theory.

Additional Fields

Identifer	oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:tut/oai:encore.tut.ac.za:d1001343
Date	January 2012
Creators	Stamps, Kenyon.
Source Sets	South African National ETD Portal
Language	English
Detected Language	English
Type	Text
Format	PDF